{"type": "node", "id": "p2:axis:agents", "kind": "axis", "label": "Agentic orchestration & multi-agent frameworks", "url": "https://arxiv.org/list/cs.LG/recent", "source": "pass2-harvest", "axis": "agents", "layer": 1}
{"type": "node", "id": "p2:axis:energy", "kind": "axis", "label": "Energy-proportional / carbon-aware ML tooling", "url": "https://arxiv.org/list/cs.LG/recent", "source": "pass2-harvest", "axis": "energy", "layer": 1, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:surface:energy", "kind": "surface", "label": "SZL surface: energy", "url": "https://a-11-oy.com", "source": "szl-estate", "axis": "energy", "layer": 3, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:axis:qec", "kind": "axis", "label": "Quantum error correction decoders (incl. neural)", "url": "https://arxiv.org/list/cs.LG/recent", "source": "pass2-harvest", "axis": "qec", "layer": 1, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:surface:qhall", "kind": "surface", "label": "SZL surface: qhall", "url": "https://a-11-oy.com", "source": "szl-estate", "axis": "qec", "layer": 3, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:axis:fusion", "kind": "axis", "label": "Multi-sensor fusion", "url": "https://arxiv.org/list/cs.LG/recent", "source": "pass2-harvest", "axis": "fusion", "layer": 1}
{"type": "node", "id": "p2:axis:defense", "kind": "axis", "label": "Counter-UAS / defense sensing", "url": "https://arxiv.org/list/cs.LG/recent", "source": "pass2-harvest", "axis": "defense", "layer": 1}
{"type": "node", "id": "p2:axis:attention", "kind": "axis", "label": "FlashAttention core-kernel family + hybrid Transformer-SSM", "url": "https://arxiv.org/list/cs.LG/recent", "source": "pass2-harvest", "axis": "attention", "layer": 1, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:surface:ringattn", "kind": "surface", "label": "SZL surface: ringattn", "url": "https://a-11-oy.com", "source": "szl-estate", "axis": "attention", "layer": 3, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:langgenius--dify", "kind": "repo", "label": "langgenius/dify (148027\u2605) \u2014 Production-ready platform for agentic workflow development.", "url": "https://github.com/langgenius/dify", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:labring--fastgpt", "kind": "repo", "label": "labring/FastGPT (28849\u2605) \u2014 FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letti", "url": "https://github.com/labring/FastGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:builderz-labs--mission-control", "kind": "repo", "label": "builderz-labs/mission-control (5634\u2605) \u2014 Self-hosted AI agent orchestration platform: dispatch tasks, run multi-agent workflows, monitor spend, and govern operations from one mission control dashboard.", "url": "https://github.com/builderz-labs/mission-control", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:iflytek--astron-agent", "kind": "repo", "label": "iflytek/astron-agent (8611\u2605) \u2014 Enterprise-grade, commercial-friendly agentic workflow platform for building next-generation SuperAgents.", "url": "https://github.com/iflytek/astron-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:deepset-ai--haystack", "kind": "repo", "label": "deepset-ai/haystack (25841\u2605) \u2014 Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, m", "url": "https://github.com/deepset-ai/haystack", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jnmetacode--agency-agents-zh", "kind": "repo", "label": "jnMetaCode/agency-agents-zh (16797\u2605) \u2014 \ud83c\udfad 266 \u4e2a\u5373\u63d2\u5373\u7528\u7684 AI \u4e13\u5bb6\u89d2\u8272 \u2014 \u652f\u6301 Hermes Agent/Claude Code/Cursor/Copilot \u7b49 18 \u79cd\u5de5\u5177\uff0c\u8986\u76d6\u5de5\u7a0b/\u8bbe\u8ba1/\u8425\u9500/\u91d1\u878d\u7b49 20 \u4e2a\u90e8\u95e8\u3002\u542b 50 \u4e2a\u4e2d\u56fd\u5e02\u573a\u539f\u521b\u667a\u80fd\u4f53\uff08\u5c0f\u7ea2\u4e66/\u6296\u97f3/\u5fae\u4fe1/\u98de\u4e66/\u9489\u9489\u7b49\uff09\u3002\u642d\u914d\u7f16\u6392\u5668 agency-orchestrator\uff0c\u4e00\u53e5\u8bdd\u5373\u53ef\u8ba9\u591a\u4f4d\u4e13\u5bb6\u6309 DAG \u81ea\u52a8\u534f\u4f5c\u3002", "url": "https://github.com/jnMetaCode/agency-agents-zh", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:weibocom--rill-flow", "kind": "repo", "label": "weibocom/rill-flow (410\u2605) \u2014  Rill Flow is a high-performance, scalable workflow orchestration engine for distributed workloads and LLMs", "url": "https://github.com/weibocom/rill-flow", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:bytechefhq--bytechef", "kind": "repo", "label": "bytechefhq/bytechef (900\u2605) \u2014 Open-source platform that unifies AI agent orchestration and workflow automation \u2014 autonomy and precision in one platform.", "url": "https://github.com/bytechefhq/bytechef", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:graniet--llm", "kind": "repo", "label": "graniet/llm (355\u2605) \u2014 A powerful Rust library and CLI tool to unify and orchestrate multiple LLM, Agent and voice backends (OpenAI, Claude, Gemini, Ollama, ElevenLabs...) with a single, extensible API. Build, chain, evalua", "url": "https://github.com/graniet/llm", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:liweiphys--layra", "kind": "repo", "label": "liweiphys/layra (898\u2605) \u2014 LAYRA\u2014an enterprise-ready, out-of-the-box solution\u2014unlocks next-generation intelligent systems powered by visual RAG and limitless visual multi-step agent workflow orchestration.", "url": "https://github.com/liweiphys/layra", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:lofcz--llmtornado", "kind": "repo", "label": "lofcz/LLMTornado (621\u2605) \u2014 The .NET library to build AI agents with 30+ built-in connectors.", "url": "https://github.com/lofcz/LLMTornado", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:thibautmelen--agentic-ai-systems", "kind": "repo", "label": "ThibautMelen/agentic-ai-systems (282\u2605) \u2014 \ud83d\udc14 Agentic systems explained with chickens. Workflows, agents & orchestration made simple. Mermaid diagrams included", "url": "https://github.com/ThibautMelen/agentic-ai-systems", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:rocketride-org--rocketride-server", "kind": "repo", "label": "rocketride-org/rocketride-server (4978\u2605) \u2014 High-performance AI pipeline engine with a C++ core and 50+ Python-extensible nodes. Build, debug, and scale LLM workflows with 13+ model providers, 8+ vector databases, and agent orchestration, all f", "url": "https://github.com/rocketride-org/rocketride-server", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:imfeh2--flowent", "kind": "repo", "label": "ImFeH2/flowent (248\u2605) \u2014 A workflow orchestration platform for multi-agent collaboration", "url": "https://github.com/ImFeH2/flowent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:pipelex--pipelex", "kind": "repo", "label": "Pipelex/pipelex (687\u2605) \u2014 Declarative language for composable Al workflows. Devtool for agents and mere humans.", "url": "https://github.com/Pipelex/pipelex", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:dataelement--bisheng", "kind": "repo", "label": "dataelement/bisheng (11501\u2605) \u2014 BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SF", "url": "https://github.com/dataelement/bisheng", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:zhnt--loushang", "kind": "repo", "label": "zhnt/loushang (530\u2605) \u2014 AI-native agent harness for coding workflows by python: multi-model LLM orchestration, stateful sessions, tool governance,   traceable delivery, and provider routing for GPT, Claude, DeepSeek, Qwen, K", "url": "https://github.com/zhnt/loushang", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:agenticgokit--agenticgokit", "kind": "repo", "label": "AgenticGoKit/AgenticGoKit (163\u2605) \u2014 Open-source Agentic AI framework in Go for building, orchestrating, and deploying intelligent agents. LLM-agnostic, event-driven, with multi-agent workflows, MCP tool discovery, and production-grade o", "url": "https://github.com/AgenticGoKit/AgenticGoKit", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:xorbitsai--xagent", "kind": "repo", "label": "xorbitsai/xagent (264\u2605) \u2014 Build personal agents and enterprise AI workforces that plan, delegate, use tools, and deliver real work \u2014 without brittle workflows.", "url": "https://github.com/xorbitsai/xagent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:linora-u--agentloom", "kind": "repo", "label": "linora-u/AgentLoom (89\u2605) \u2014 Simple, flexible workflow orchestration for multi-agent AI apps, with YAML configuration, runtime safety, observability, and resume support.", "url": "https://github.com/linora-u/AgentLoom", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:i365dev--llm_agent", "kind": "repo", "label": "i365dev/llm_agent (27\u2605) \u2014 An abstraction library for building domain-specific intelligent agents based on Large Language Models (LLMs). LLMAgent provides a core architecture and behavior definitions that simplify the developme", "url": "https://github.com/i365dev/llm_agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:swarmauri--swarmauri-sdk", "kind": "repo", "label": "swarmauri/swarmauri-sdk (104\u2605) \u2014 Modular Python SDK and monorepo for AI agents, LLM integrations, tools, parsers, embeddings, vector stores, and extensible application workflows.", "url": "https://github.com/swarmauri/swarmauri-sdk", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:alexli18--binex", "kind": "repo", "label": "Alexli18/binex (62\u2605) \u2014 Debuggable runtime for AI agent workflows. DAG pipelines, artifact lineage, and replayable runs.", "url": "https://github.com/Alexli18/binex", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:yx-fan--multi-agent-orchestration-framework", "kind": "repo", "label": "yx-fan/multi-agent-orchestration-framework (27\u2605) \u2014 Modular multi-agent orchestration framework powered by LangGraph and FastAPI.", "url": "https://github.com/yx-fan/multi-agent-orchestration-framework", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:azure--intelligent-app-workshop", "kind": "repo", "label": "Azure/intelligent-app-workshop (204\u2605) \u2014 Immersive workshop showcasing the remarkable potential of integrating SoTA foundation models to enhance product experiences and streamline backend workflows. Leverages Microsoft's Copilot stack, Micro", "url": "https://github.com/Azure/intelligent-app-workshop", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:xeloxa--temodar-agent", "kind": "repo", "label": "xeloxa/temodar-agent (58\u2605) \u2014 Temodar Agent is an AI-powered WordPress plugin and theme security analysis platform built for security researchers, product security teams, auditors, and defenders. It combines AI agent workflows, mu", "url": "https://github.com/xeloxa/temodar-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:hereandnowai--master-langgraph-workflows-in-python-20-real-world-agent-projects-by-hereandnow-ai", "kind": "repo", "label": "hereandnowai/master-langgraph-workflows-in-python-20-real-world-agent-projects-by-hereandnow-ai (45\u2605) \u2014 Unlock the power of LangGraph v0.5.3 with 20 bite\u2011sized, beginner\u2011friendly agent projects\u2014from chatbots and finance bots to multi-agent orchestrations. Developed by HERE AND NOW AI, this hands\u2011on ", "url": "https://github.com/hereandnowai/master-langgraph-workflows-in-python-20-real-world-agent-projects-by-hereandnow-ai", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:lostbean--jido_composer", "kind": "repo", "label": "lostbean/jido_composer (30\u2605) \u2014 Composable multi-agent workflows and LLM orchestrators with human-in-the-loop, checkpointing, and OpenTelemetry observability", "url": "https://github.com/lostbean/jido_composer", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ces-ltd--titanx", "kind": "repo", "label": "CES-Ltd/TitanX (41\u2605) \u2014 Enterprise AI Agent Orchestration Platform \u2014 Secure, Observable, Configurable. Multi-agent teams with IAM policies, n8n workflows, LangChain memory, LangSmith traces, NemoClaw security, OpenTelemetry,", "url": "https://github.com/CES-Ltd/TitanX", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:redhat-community-ai-tools--unifai", "kind": "repo", "label": "redhat-community-ai-tools/UnifAI (40\u2605) \u2014 Production-grade multi-agent orchestration engine. Compose agentic workflows from a pluggable catalog of Agents, LLMs, tools, and retrievers. Execute locally with LangGraph or distributed with Tempora", "url": "https://github.com/redhat-community-ai-tools/UnifAI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:pipelex--pipelex-cookbook", "kind": "repo", "label": "Pipelex/pipelex-cookbook (38\u2605) \u2014 Cookbook for Pipelex, the declarative language for composable Al workflows. Devtool for agents and mere humans.", "url": "https://github.com/Pipelex/pipelex-cookbook", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:juglans-ai--juglans", "kind": "repo", "label": "juglans-ai/juglans (12\u2605) \u2014 AI workflow orchestration DSL \u2014 compiler, runtime & CLI", "url": "https://github.com/juglans-ai/juglans", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:llm-use--llm-use", "kind": "repo", "label": "llm-use/llm-use (42\u2605) \u2014 LLM orchestration toolkit for agent workflows: planner + workers + synthesis, optional router (LLM + learned   fallback), supports OpenAI/Anthropic/Ollama/llama.cpp, real scraping with caching, MCP se", "url": "https://github.com/llm-use/llm-use", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:fzn0x--watchtower", "kind": "repo", "label": "fzn0x/watchtower (147\u2605) \u2014 Watchtower is a simple AI-powered penetration testing automation CLI tool that leverages LLMs and LangGraph to orchestrate agentic workflows that you can use to test your websites locally. Generate us", "url": "https://github.com/fzn0x/watchtower", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:pinkpixel-dev--mindbridge-mcp", "kind": "repo", "label": "pinkpixel-dev/mindbridge-mcp (34\u2605) \u2014 MindBridge is an AI orchestration MCP server that lets any app talk to any LLM \u2014 OpenAI, Anthropic, DeepSeek, Ollama, and more \u2014 through a single unified API. Route queries, compare models, get second", "url": "https://github.com/pinkpixel-dev/mindbridge-mcp", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:kaivyy--kabot", "kind": "repo", "label": "kaivyy/kabot (20\u2605) \u2014 Next-Gen Autonomous AI Engineer. Ditch the stateless chatbots. Kabot brings Stateful Hybrid Memory, zero-hallucination workflows, and persistent multi-agent orchestration to your local machine. \ud83e\udd8a\ud83d\ude80\ud83d\udee1\ufe0f ", "url": "https://github.com/kaivyy/kabot", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aksingh-0704--team_agents", "kind": "repo", "label": "AKSINGH-0704/Team_Agents (15\u2605) \u2014 Multi-agent AI system. Autonomous agents coordinating task execution, decision routing, and workflow orchestration using LangChain and LLM Model.", "url": "https://github.com/AKSINGH-0704/Team_Agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:anurmatov--phleet", "kind": "repo", "label": "anurmatov/phleet (16\u2605) \u2014 Open-source autonomous multi-agent AI platform. Dockerized agents driven by Claude or Codex, orchestrated with Temporal workflows and coordinated via Telegram.", "url": "https://github.com/anurmatov/phleet", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:projectliminality--interbrain", "kind": "repo", "label": "ProjectLiminality/InterBrain (23\u2605) \u2014 Open-source protocol integrating collective and artificial intelligence \u2014 LLM orchestration, agentic workflows, and RAG in a cross-platform TypeScript/Tauri app.", "url": "https://github.com/ProjectLiminality/InterBrain", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:reworkd--agentgpt", "kind": "repo", "label": "reworkd/AgentGPT (36256\u2605) \u2014 \ud83e\udd16 Assemble, configure, and deploy autonomous AI Agents in your browser.", "url": "https://github.com/reworkd/AgentGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:e2b-dev--awesome-ai-agents", "kind": "repo", "label": "e2b-dev/awesome-ai-agents (28644\u2605) \u2014 A list of AI autonomous agents", "url": "https://github.com/e2b-dev/awesome-ai-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:elricliu--autogpt-next-web", "kind": "repo", "label": "ElricLiu/AutoGPT-Next-Web (2999\u2605) \u2014 \ud83e\udd16 Assemble, configure, and deploy autonomous AI Agents in your browser.\u4e00\u952e\u514d\u8d39\u90e8\u7f72\u4f60\u7684\u79c1\u4ebaAutoGPT \u7f51\u9875\u5e94\u7528", "url": "https://github.com/ElricLiu/AutoGPT-Next-Web", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:idosal--agentllm", "kind": "repo", "label": "idosal/AgentLLM (469\u2605) \u2014 AgentLLM is a PoC for browser-native autonomous agents", "url": "https://github.com/idosal/AgentLLM", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:scarletpan--awesome-autonomous-gpt", "kind": "repo", "label": "ScarletPan/awesome-autonomous-gpt (283\u2605) \u2014 A curated list of awesome projects and resources related to autonomous AI agents.", "url": "https://github.com/ScarletPan/awesome-autonomous-gpt", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jbesomi--awesome-autonomous-agents", "kind": "repo", "label": "jbesomi/awesome-autonomous-agents (41\u2605) \u2014 Curated list of tools, frameworks and resources to work with autonomous agents (autoGPT)", "url": "https://github.com/jbesomi/awesome-autonomous-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:intelligenzaartificiale--free-auto-gpt", "kind": "repo", "label": "IntelligenzaArtificiale/Free-Auto-GPT (2532\u2605) \u2014 Free Auto GPT with NO paids API is a repository that offers a simple version of Auto GPT, an autonomous AI agent capable of performing tasks independently. Unlike other versions, our implementation do", "url": "https://github.com/IntelligenzaArtificiale/Free-Auto-GPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:alexk1919--mackgpt", "kind": "repo", "label": "alexk1919/MackGPT (29\u2605) \u2014 Create, customize, and launch autonomous AI Agents in your browser. \ud83e\udd16\ud83d\ude80", "url": "https://github.com/alexk1919/MackGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:curated-awesome-lists--awesome-auto-gpt", "kind": "repo", "label": "Curated-Awesome-Lists/Awesome-Auto-GPT (41\u2605) \u2014 A curated list of awesome projects related to AutoGPT, an autonomous AI agent that can perform tasks independently using ChatGPT.", "url": "https://github.com/Curated-Awesome-Lists/Awesome-Auto-GPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:edmar--whenx", "kind": "repo", "label": "edmar/whenx (52\u2605) \u2014 Event-Driven Autonomous Agents. create alerts in the form of \"When X happens, then do Y\". In this initial version, we are only supporting email alerts in the form of \"When X happens, send me an email ", "url": "https://github.com/edmar/whenx", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:iskandarreza--ai-worker-js", "kind": "repo", "label": "iskandarreza/ai-worker-js (10\u2605) \u2014 Implementation of autonomous AI agent(s) in JS using Webworkers", "url": "https://github.com/iskandarreza/ai-worker-js", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:fredsiika--gpt-vector-agent", "kind": "repo", "label": "fredsiika/gpt-vector-agent (8\u2605) \u2014 \ud83e\udde9 Interfacing with different LLMs-chains, vectorstore databases, and autonomous agents.", "url": "https://github.com/fredsiika/gpt-vector-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:0xmerl99--agent-world-protocol", "kind": "repo", "label": "0xMerl99/Agent-World-Protocol (39\u2605) \u2014 The open world for autonomous AI agents on Solana Trade. Build. Fight. Earn. Explore. Connect your AI agent to a persistent shared world. Trade real SOL, build structures, form guilds, fight for terri", "url": "https://github.com/0xMerl99/Agent-World-Protocol", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:web007-spec--autogpt-next-web", "kind": "repo", "label": "web007-spec/AutoGPT-Next-Web (5\u2605) \u2014 \ud83e\udd16 Assemble, configure, and deploy autonomous AI Agents in your browser.", "url": "https://github.com/web007-spec/AutoGPT-Next-Web", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:iskandarreza--loopgpt-next", "kind": "repo", "label": "iskandarreza/loopgpt-next (7\u2605) \u2014 UI frontend for loopgpt self-prompting autonomous AI agent, to aid in debugging initial prompts ", "url": "https://github.com/iskandarreza/loopgpt-next", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:naveen123bh--autogpt", "kind": "repo", "label": "naveen123bh/autogpt (0\u2605) \u2014 autonomous agent", "url": "https://github.com/naveen123bh/autogpt", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:javierlozo--langchain-autogpt", "kind": "repo", "label": "Javierlozo/langchain-autogpt (0\u2605) \u2014  Autonomous Agent | AutoGPT", "url": "https://github.com/Javierlozo/langchain-autogpt", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:spyderrex--squadai", "kind": "repo", "label": "SpyderRex/SquadAI (3\u2605) \u2014 An autonomous agent program based on crewAI and seeks to be a cross between crewAI and AutoGPT", "url": "https://github.com/SpyderRex/SquadAI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:bchip--chippt", "kind": "repo", "label": "BChip/ChipPT (0\u2605) \u2014 Research on autonomous agents, langchain, autogpt, etc", "url": "https://github.com/BChip/ChipPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:bobmhong--autogpt-work", "kind": "repo", "label": "bobmhong/autogpt-work (0\u2605) \u2014 Instructions and settings for use with Auto-GPT autonomous agents", "url": "https://github.com/bobmhong/autogpt-work", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ksen27--deploy-autonomous-ai-agents-in-your-browser.-autogpt-", "kind": "repo", "label": "ksen27/Deploy-autonomous-AI-Agents-in-your-browser.-AutoGPT- (0\u2605)", "url": "https://github.com/ksen27/Deploy-autonomous-AI-Agents-in-your-browser.-AutoGPT-", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ratnakar1009--autonomous-ai-task-agent-autogpt-crewai-style-", "kind": "repo", "label": "Ratnakar1009/Autonomous-AI-Task-Agent-AutoGPT-CrewAI-Style- (0\u2605)", "url": "https://github.com/Ratnakar1009/Autonomous-AI-Task-Agent-AutoGPT-CrewAI-Style-", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:api-evangelist--autogpt", "kind": "repo", "label": "api-evangelist/autogpt (0\u2605) \u2014 AutoGPT is an autonomous AI agent framework that chains LLM calls to accomplish complex tasks independently.", "url": "https://github.com/api-evangelist/autogpt", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:d68864767--autogpt-master-edition-fully-autonomous-desktop-agent-for-google-chrome", "kind": "repo", "label": "d68864767/AutoGPT-Master-Edition-Fully-Autonomous-Desktop-Agent-for-Google-Chrome (0\u2605)", "url": "https://github.com/d68864767/AutoGPT-Master-Edition-Fully-Autonomous-Desktop-Agent-for-Google-Chrome", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sunny-raj-sah--replit-agent-v1-a-mini-autonomous-ai-agent", "kind": "repo", "label": "sunny-raj-sah/Replit-Agent-v1-A-Mini-Autonomous-AI-Agent (0\u2605) \u2014 This project is a **reverse-engineered implementation** of a real-world AI agent architecture inspired by systems like **Replit Agent**, **Devin**, **Cursor Agents**, and **AutoGPT**.", "url": "https://github.com/sunny-raj-sah/Replit-Agent-v1-A-Mini-Autonomous-AI-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:dick2450121353-dot--autonomous-problem-solving", "kind": "repo", "label": "dick2450121353-dot/autonomous-problem-solving (0\u2605) \u2014 AI Agent \u81ea\u4e3b\u95ee\u9898\u5904\u7406\u65b9\u6cd5\u8bba \u2014 \u878d\u5408 ReAct + Reflexion + Plan-and-Solve + AutoGPT + Self-Refine", "url": "https://github.com/dick2450121353-dot/autonomous-problem-solving", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aiblogfirst--autonomous-ai-comparison", "kind": "repo", "label": "Aiblogfirst/autonomous-ai-comparison (0\u2605) \u2014 Add up to 350 characters describing the repository, e.g., \"A comprehensive comparison of AutoGPT, BabyAGI, and GodMode autonomous AI agents.\"", "url": "https://github.com/Aiblogfirst/autonomous-ai-comparison", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:chhunt17--autonomous-ai-agent", "kind": "repo", "label": "ChhunT17/Autonomous-AI-Agent (1\u2605) \u2014 \ud83e\udd16 Monitor $BTB on Twitter, engage with the community, and provide real-time information using AI-powered responses for BTB Finance.", "url": "https://github.com/ChhunT17/Autonomous-AI-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:adithi-md--autogpt-ollama-qwen", "kind": "repo", "label": "adithi-md/AutoGPT-Ollama-Qwen (0\u2605) \u2014 Agentic AI project built using AutoGPT, Docker, Ollama, and the Qwen2.5:7B large language model. This project demonstrates the deployment of an autonomous AI agent platform with workflow-based task ex", "url": "https://github.com/adithi-md/AutoGPT-Ollama-Qwen", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:udayteja21--autogpt", "kind": "repo", "label": "UdayTeja21/Autogpt (1\u2605) \u2014 AutoGPT is an AI-powered automation system that can independently plan, reason, and execute tasks with minimal human input. It integrates large language models with real-world tools (APIs, web automat", "url": "https://github.com/UdayTeja21/Autogpt", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aiwaves-cn--agents", "kind": "repo", "label": "aiwaves-cn/agents (5938\u2605) \u2014 An Open-source Framework for Data-centric, Self-evolving Autonomous Language Agents", "url": "https://github.com/aiwaves-cn/agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:agentuniverse-ai--agentuniverse", "kind": "repo", "label": "agentuniverse-ai/agentUniverse (2293\u2605) \u2014 agentUniverse is a LLM multi-agent framework that allows developers to easily build multi-agent applications. ", "url": "https://github.com/agentuniverse-ai/agentUniverse", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:transformeroptimus--superagi", "kind": "repo", "label": "TransformerOptimus/SuperAGI (17605\u2605) \u2014 <\u26a1\ufe0f> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.", "url": "https://github.com/TransformerOptimus/SuperAGI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aielte-research--hacksynth", "kind": "repo", "label": "aielte-research/HackSynth (309\u2605) \u2014 LLM Agent and Evaluation Framework for Autonomous Penetration Testing ", "url": "https://github.com/aielte-research/HackSynth", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aaronjmars--aeon", "kind": "repo", "label": "aaronjmars/aeon (571\u2605) \u2014 The most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever.", "url": "https://github.com/aaronjmars/aeon", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:wanshuiyin--auto-claude-code-research-in-sleep", "kind": "repo", "label": "wanshuiyin/Auto-claude-code-research-in-sleep (13092\u2605) \u2014 ARIS \u2694\ufe0f (Auto-Research-In-Sleep) \u2014 Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in \u2014 works wi", "url": "https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:undertone0809--promptulate", "kind": "repo", "label": "Undertone0809/promptulate (512\u2605) \u2014 \ud83d\ude80Lightweight Large language model automation and Autonomous Language Agents development framework. Build your LLM Agent Application in a pythonic way!", "url": "https://github.com/Undertone0809/promptulate", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mervinpraison--praisonai", "kind": "repo", "label": "MervinPraison/PraisonAI (8354\u2605) \u2014 PraisonAI \ud83e\udd9e \u2014 Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with buil", "url": "https://github.com/MervinPraison/PraisonAI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jatingargiitk--saas-builder", "kind": "repo", "label": "jatingargiitk/saas-builder (222\u2605) \u2014 AI-native SaaS framework that builds full-stack apps using autonomous AI agents", "url": "https://github.com/jatingargiitk/saas-builder", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:swarmclawai--swarmclaw", "kind": "repo", "label": "swarmclawai/swarmclaw (605\u2605) \u2014 Open-source self-hosted AI agent runtime and multi-agent framework for autonomous agent swarms. Agent memory, MCP tools, schedules, delegation, and 23+ LLM providers (Claude, GPT, Gemini, OpenRouter, ", "url": "https://github.com/swarmclawai/swarmclaw", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jwentong--wirelessagent_r1", "kind": "repo", "label": "jwentong/WirelessAgent_R1 (46\u2605) \u2014 We introduce WirelessAgent, a novel framework that harnesses large language models (LLMs) to create autonomous AI agents for diverse wireless network tasks. ", "url": "https://github.com/jwentong/WirelessAgent_R1", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:cordum-io--cordum", "kind": "repo", "label": "cordum-io/cordum (489\u2605) \u2014 The open agent control plane. Govern autonomous AI agents with pre-execution policy enforcement, approval gates, and audit trails. Works with LangChain, CrewAI, MCP, and any framework.", "url": "https://github.com/cordum-io/cordum", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aviralgarg05--agentunit", "kind": "repo", "label": "aviralgarg05/agentunit (7\u2605) \u2014 AgentUnit is a pytest-inspired evaluation harness for autonomous agents and retrieval-augmented generation (RAG) workflows. It helps you describe repeatable scenarios, connect them to your agent stack", "url": "https://github.com/aviralgarg05/agentunit", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sagentic-ai--sagentic-af", "kind": "repo", "label": "sagentic-ai/sagentic-af (78\u2605) \u2014 \ud83d\ude0e Sagentic.ai Agent Framework - Sagentic.ai is a unified platform for building, running and scaling autonomous agents.", "url": "https://github.com/sagentic-ai/sagentic-af", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:libraryofcelsus--aetherius_ai_assistant", "kind": "repo", "label": "libraryofcelsus/Aetherius_AI_Assistant (315\u2605) \u2014 A completely private, locally-operated Ai Assistant/Chatbot/Sub-Agent Framework with realistic Long Term Memory and thought formation using Open Source LLMs. Qdrant is used for the Vector DB.", "url": "https://github.com/libraryofcelsus/Aetherius_AI_Assistant", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:alfredolopez80--multi-agent-ralph-loop", "kind": "repo", "label": "alfredolopez80/multi-agent-ralph-loop (140\u2605) \u2014 Autonomous orchestration framework for Claude Code with MemPalace-inspired memory (4-layer stack, 818-token wake-up), parallel-first Agent Teams (6 teammates), Aristotle First Principles methodology, ", "url": "https://github.com/alfredolopez80/multi-agent-ralph-loop", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:openlegion-ai--openlegion", "kind": "repo", "label": "openlegion-ai/openlegion (105\u2605) \u2014 Secure autonomous AI agent framework and platform. Build AI teams by describing what you want. Orchestrate agents that can do everything a human can do.", "url": "https://github.com/openlegion-ai/openlegion", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ashutosh0x--arc-cli", "kind": "repo", "label": "Ashutosh0x/arc-cli (19\u2605) \u2014 ARC: High-Performance Agentic CLI Framework built in Rust for autonomous multi-agent code generation.", "url": "https://github.com/Ashutosh0x/arc-cli", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:chaosync-org--awesome-ai-agent-testing", "kind": "repo", "label": "chaosync-org/awesome-ai-agent-testing (40\u2605) \u2014 \ud83e\udd16 A curated list of resources for testing AI agents - frameworks, methodologies, benchmarks, tools, and best practices for ensuring reliable, safe, and effective autonomous AI systems", "url": "https://github.com/chaosync-org/awesome-ai-agent-testing", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:xybruceliu--thoughtful-agents", "kind": "repo", "label": "xybruceliu/thoughtful-agents (39\u2605) \u2014 A Python framework for building proactive LLM agents that simulate human-like cognitive processes. Enables agents to continuously generate and evaluate thoughts in parallel with conversations, and aut", "url": "https://github.com/xybruceliu/thoughtful-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:gustavoeenriquez--makerai", "kind": "repo", "label": "gustavoeenriquez/MakerAi (189\u2605) \u2014 The AI Operating System for Delphi. 100% native framework with RAG 2.0, autonomous agents, MCP protocol, and universal LLM connector. Supports OpenAI, Claude, Gemini, Ollama, and more. Delphi 10.4+ (l", "url": "https://github.com/gustavoeenriquez/MakerAi", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:inquisimind--digital-life", "kind": "repo", "label": "InquisiMind/digital-life (21\u2605) \u2014 Digital Life \u00b7 Life Engineering \u2014 A runtime framework for persistent, autonomous LLM agents", "url": "https://github.com/InquisiMind/digital-life", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:opencsgs--coagent", "kind": "repo", "label": "OpenCSGs/coagent (29\u2605) \u2014 An open-source framework for building monolithic or distributed agentic systems, ranging from simple LLM calls to compositional workflows and autonomous agents.", "url": "https://github.com/OpenCSGs/coagent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ericwang915--pythonclaw", "kind": "repo", "label": "ericwang915/PythonClaw (37\u2605) \u2014 OpenClaw reimagined in pure Python \u2014 autonomous AI agent with memory, RAG, skills, web dashboard, voice input, daemon, and multi-channel support.", "url": "https://github.com/ericwang915/PythonClaw", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:beidald--liliumai", "kind": "repo", "label": "beidald/liliumai (94\u2605) \u2014 Lilium AI: The ultimate personal AI agent framework for autonomous computer control. Featuring browser automation, shell execution, and multi-channel integration (WeChat/Telegram/Discord).", "url": "https://github.com/beidald/liliumai", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:gwenlake--gwenflow", "kind": "repo", "label": "gwenlake/gwenflow (17\u2605) \u2014 A framework for orchestrating applications powered by autonomous AI agents and LLMs.", "url": "https://github.com/gwenlake/gwenflow", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:kalaspuff--ai-assisted-task-executor", "kind": "repo", "label": "kalaspuff/ai-assisted-task-executor (126\u2605) \u2014 \ud83e\udd16 A Task-Driven Autonomous Agent System as an AI-powered solution that leverages LLMs, vector search, and the LangChain framework to efficiently complete, generate, and prioritize tasks using a wide r", "url": "https://github.com/kalaspuff/ai-assisted-task-executor", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:h4ckologic--bughunter-ai", "kind": "repo", "label": "h4ckologic/bughunter-ai (50\u2605) \u2014 Autonomous Bug Bounty Hunting Framework powered by Claude Code. 20 AI agents, state-machine orchestration, Burp Suite MCP, credential vault, LLM security track. Type 'hunt target.com' and let AI find ", "url": "https://github.com/h4ckologic/bughunter-ai", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:francescostabile--omnigent", "kind": "repo", "label": "FrancescoStabile/omnigent (28\u2605) \u2014 Universal autonomous agent framework with ReAct loop, multi-provider LLM routing, reasoning graph, and MCP integration, domain-agnostic for building specialized AI agents.", "url": "https://github.com/FrancescoStabile/omnigent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:lixin97--agora-lab", "kind": "repo", "label": "LiXin97/agora-lab (47\u2605) \u2014 Multi-agent research automation framework for LLM agents, with adversarial lab meetings, paper-review rounds, auditable Markdown workflows, an autonomous runtime watchdog, and a pixel-art web dashboar", "url": "https://github.com/LiXin97/agora-lab", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nirholas--three.ws", "kind": "repo", "label": "nirholas/three.ws (77\u2605) \u2014 Open-source 3D AI agent framework \u2014 GLB/glTF avatars with LLM brains, memory, emotions, and autonomous payments. MCP server \u00b7 x402 \u00b7 Solana/EVM \u00b7 Three.js. Embed anywhere as a web component. Character", "url": "https://github.com/nirholas/three.ws", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ktol1--redteam-agent", "kind": "repo", "label": "ktol1/RedTeam-Agent (62\u2605) \u2014  RedTeam-Agent: AI-Powered Autonomous Red Team Framework via Model Context Protocol. AI\u7ea2\u961f\u4e0e\u5185\u7f51\u6e17\u900f\u81ea\u52a8\u5316\u6846\u67b6\uff0c\u652f\u6301 gogo, fscan, httpx, nuclei, impacket, playwright \u7b49 15+ \u6e17\u900f\u5de5\u5177\uff0c\u8ba9 LLM \u76f4\u63a5\u5316\u8eab\u5b89\u5168\u5ba1\u8ba1\u9ed1\u5ba2\u3002", "url": "https://github.com/ktol1/RedTeam-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sarthak1095--redefining-qa-multi-agent-ai-automation-using-mcp-protocol", "kind": "repo", "label": "sarthak1095/Redefining-QA-Multi-Agent-AI-Automation-Using-MCP-Protocol (16\u2605) \u2014 This project demonstrates how to build a multi-agent AI automation framework using the Model Context Protocol (MCP). The setup enables LLMs (Claude AI in this case) to autonomously execute UI flows, A", "url": "https://github.com/sarthak1095/Redefining-QA-Multi-Agent-AI-Automation-Using-MCP-Protocol", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:tenchineko--standalone-orchestrator", "kind": "repo", "label": "TenchiNeko/standalone-orchestrator (20\u2605) \u2014 Autonomous multi-agent coding system on local LLMs. No frameworks, no API costs. Plan \u2192 Build \u2192 Test \u2192 Fix with Qwen 80B + 7B on your own GPUs.", "url": "https://github.com/TenchiNeko/standalone-orchestrator", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:envisionmindca--os-agent", "kind": "repo", "label": "EnvisionMindCa/OS-Agent (5\u2605) \u2014 LLM agent framework that can use Linux terminal autonomously!", "url": "https://github.com/EnvisionMindCa/OS-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:simonstaton--agentmanager", "kind": "repo", "label": "simonstaton/AgentManager (23\u2605) \u2014 Conduct autonomous Claude Code agents at scale safely. Human-on-the-loop orchestration platform with kill switch, cost tracking, and inter-agent messaging.", "url": "https://github.com/simonstaton/AgentManager", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ai-agentswarm--agentswarm", "kind": "repo", "label": "ai-agentswarm/agentswarm (20\u2605) \u2014 A Recursive, Functional, and Type-Safe Framework for Autonomous AI Agents.", "url": "https://github.com/ai-agentswarm/agentswarm", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:micro-novelty--integratedpipeline-specialized-non-llm-ai-agent-framework", "kind": "repo", "label": "Micro-Novelty/IntegratedPipeline-Specialized-Non-LLM-AI-Agent-Framework (8\u2605) \u2014 [~]  IntegratedPipeline is a standalone AI Agent Library for Non-LLM memory Augmented Agentic Framework, Specifically designed to provide Agentic capability for any Autonomous Agentic Framework locall", "url": "https://github.com/Micro-Novelty/IntegratedPipeline-Specialized-Non-LLM-AI-Agent-Framework", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:fu351--doberman-core", "kind": "repo", "label": "fu351/Doberman-Core (111\u2605) \u2014 Doberman is an AI agent security framework for guardrails, prompt injection defense, runtime policy enforcement, tool-use permissions, agent monitoring, audit logs, LLM safety, autonomous workflow pro", "url": "https://github.com/fu351/Doberman-Core", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:kyegomez--awesome-multi-agent-papers", "kind": "repo", "label": "kyegomez/awesome-multi-agent-papers (1597\u2605) \u2014 A compilation of the best multi-agent papers", "url": "https://github.com/kyegomez/awesome-multi-agent-papers", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aianytime--multi-agents-system-from-scratch", "kind": "repo", "label": "AIAnytime/Multi-Agents-System-from-Scratch (70\u2605) \u2014 Multi AI Agents System from Scratch in pure python without any frameworks.", "url": "https://github.com/AIAnytime/Multi-Agents-System-from-Scratch", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:owshq-mec--ws-3-crew-ai-multi-agent", "kind": "repo", "label": "owshq-mec/ws-3-crew-ai-multi-agent (18\u2605) \u2014 CrewAI & Sentinel", "url": "https://github.com/owshq-mec/ws-3-crew-ai-multi-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:benitomartin--crewai-rag-langchain-qdrant", "kind": "repo", "label": "benitomartin/crewai-rag-langchain-qdrant (75\u2605) \u2014 Collaborative Multi-Agent RAG with CrewAI", "url": "https://github.com/benitomartin/crewai-rag-langchain-qdrant", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mesutdmn--autonomous-multi-agent-systems-with-crewai-essay-writer", "kind": "repo", "label": "mesutdmn/Autonomous-Multi-Agent-Systems-with-CrewAI-Essay-Writer (45\u2605) \u2014 This repository contains the source code for an autonomous multi-agent system built with CrewAI and LangChain. The project enables AI agents to collaborate on tasks such as researching, writing, and e", "url": "https://github.com/mesutdmn/Autonomous-Multi-Agent-Systems-with-CrewAI-Essay-Writer", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nisaaragharia--ai-agents", "kind": "repo", "label": "NisaarAgharia/AI-Agents (94\u2605) \u2014 Design Patterns for Multi Agents Frameworks Like Autogen, Langraph, Taskweaver,Crewai,etc", "url": "https://github.com/NisaarAgharia/AI-Agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jiaxuanliu-arsko--vaspilot", "kind": "repo", "label": "JiaxuanLiu-Arsko/VASPilot (107\u2605) \u2014 An automatic tool utilizing multi agent framework CrewAI and MCP for VASP calculation.", "url": "https://github.com/JiaxuanLiu-Arsko/VASPilot", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:gurpreetkaurjethra--ai-agents", "kind": "repo", "label": "GURPREETKAURJETHRA/AI-Agents (79\u2605) \u2014 Design Patterns for Multi Agents Frameworks Like Autogen, Langraph, Taskweaver, Crewai,etc", "url": "https://github.com/GURPREETKAURJETHRA/AI-Agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:abdulbasit110--blog-writer-multi-agent", "kind": "repo", "label": "Abdulbasit110/Blog-writer-multi-agent (62\u2605) \u2014 Blog Write multi agent AI is a custom multi-agent system designed to autonomously create high-quality, research-driven blogs. Using LangChain, Gemini 2.0-Flash-EXP, and Serper Web Search Tool, it auto", "url": "https://github.com/Abdulbasit110/Blog-writer-multi-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:oneduckyboy--awesome-ai-agents-hub-for-crewai", "kind": "repo", "label": "OneDuckyBoy/Awesome-AI-Agents-HUB-for-CrewAI (92\u2605) \u2014 In this repository I will showcase my cool multi agent system projects with Crew AI, and will reference other cool projects on the subject : )", "url": "https://github.com/OneDuckyBoy/Awesome-AI-Agents-HUB-for-CrewAI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:byrencheema--job-search-agent", "kind": "repo", "label": "byrencheema/job-search-agent (35\u2605) \u2014 Multi-agent job search system using CrewAI and Claude", "url": "https://github.com/byrencheema/job-search-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aws-samples--sample-multi-agent-builder-bedrock-crewai", "kind": "repo", "label": "aws-samples/sample-multi-agent-builder-bedrock-crewai (9\u2605)", "url": "https://github.com/aws-samples/sample-multi-agent-builder-bedrock-crewai", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:the-swarm-corporation--multi-agent-template-app", "kind": "repo", "label": "The-Swarm-Corporation/Multi-Agent-Template-App (45\u2605) \u2014 A radically simple, reliable, and high performance template to enable you to quickly get set up building multi-agent applications", "url": "https://github.com/The-Swarm-Corporation/Multi-Agent-Template-App", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:dataforscience--crewai", "kind": "repo", "label": "DataForScience/CrewAI (8\u2605) \u2014 Deploy autonomous multi-agent AI teams to research, code, and solve tasks", "url": "https://github.com/DataForScience/CrewAI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:kbhujbal--multi-agent-ai-travel-advisor", "kind": "repo", "label": "kbhujbal/Multi-Agent-AI-Travel-Advisor (53\u2605) \u2014 AI travel planner with 7 specialized agents, RAG, and tool-calling. Built with CrewAI & LangChain. Generates personalized itineraries with flights, hotels, activities, and cultural tips. Production-re", "url": "https://github.com/kbhujbal/Multi-Agent-AI-Travel-Advisor", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:botextractai--ai-crewai-multi-agent", "kind": "repo", "label": "botextractai/ai-crewai-multi-agent (38\u2605) \u2014 Multi AI agent system for financial analysis with CrewAI", "url": "https://github.com/botextractai/ai-crewai-multi-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:bhargobdeka--multi-agent-apps", "kind": "repo", "label": "bhargobdeka/multi-agent-apps (24\u2605) \u2014 This repository will contain projects on multi-agent applications using frameworks such as crewai, langchain, gradio, hugging face etc.", "url": "https://github.com/bhargobdeka/multi-agent-apps", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:numb94--crewai-astock", "kind": "repo", "label": "Numb94/crewai-astock (55\u2605) \u2014 \u57fa\u4e8e CrewAI \u591a\u667a\u80fd\u4f53\u534f\u4f5c\u7684 A \u80a1\u667a\u80fd\u5206\u6790\u4e0e\u63a8\u8350\u7cfb\u7edf | Multi-agent A-share stock   analyst built on CrewAI", "url": "https://github.com/Numb94/crewai-astock", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:adongwanai--agentguide", "kind": "repo", "label": "adongwanai/AgentGuide (6693\u2605) \u2014 https://adongwanai.github.io/AgentGuide | AI Agent\u5f00\u53d1\u6307\u5357 | LangGraph\u5b9e\u6218 | \u9ad8\u7ea7RAG | \u8f6c\u884c\u5927\u6a21\u578b | \u5927\u6a21\u578b\u9762\u8bd5 | \u7b97\u6cd5\u5de5\u7a0b\u5e08 | \u9762\u8bd5\u9898\u5e93 | \u5f3a\u5316\u5b66\u4e60\uff5c\u6570\u636e\u5408\u6210", "url": "https://github.com/adongwanai/AgentGuide", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:techindicium--multiagent-crewai", "kind": "repo", "label": "techindicium/MultiAgent-CrewAI (11\u2605)", "url": "https://github.com/techindicium/MultiAgent-CrewAI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:the-swarm-corporation--multi-agent-rag-template", "kind": "repo", "label": "The-Swarm-Corporation/Multi-Agent-RAG-Template (58\u2605) \u2014 This template demonstrates how to create a collaborative team of AI agents that work together to process, analyze, and generate insights from documents.", "url": "https://github.com/The-Swarm-Corporation/Multi-Agent-RAG-Template", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:luandev--comfyui-crewai", "kind": "repo", "label": "luandev/ComfyUI-CrewAI (63\u2605) \u2014 This project aims to integrate Crew AI's multi-agent collaboration framework into the ComfyUI environment. By combining the strengths of Crew AI's role-based, collaborative AI agent system with ComfyU", "url": "https://github.com/luandev/ComfyUI-CrewAI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aws-samples--sample-compliance-assistant-with-agents", "kind": "repo", "label": "aws-samples/sample-compliance-assistant-with-agents (29\u2605) \u2014 Sample solution to automate tedious regulatory compliance processes using multi-agent systems", "url": "https://github.com/aws-samples/sample-compliance-assistant-with-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:rn0311--crewaisecurityagent", "kind": "repo", "label": "RN0311/CrewAISecurityAgent (14\u2605) \u2014 This repository contains my implementation of building a Security Incident Management Multi-Agentic System.", "url": "https://github.com/RN0311/CrewAISecurityAgent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:hanantabak2--crewai_ai_business_consultant_on_streamlit", "kind": "repo", "label": "hanantabak2/crewai_ai_business_consultant_on_streamlit (18\u2605) \u2014 A multi-agent business consultant app on streamlit implemented using crewAI", "url": "https://github.com/hanantabak2/crewai_ai_business_consultant_on_streamlit", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aisquare-studio--aisquare-studio-qa", "kind": "repo", "label": "AISquare-Studio/AISquare-Studio-QA (164\u2605) \u2014 Setting up QA testing agents using playwright and crewAI", "url": "https://github.com/AISquare-Studio/AISquare-Studio-QA", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:felixggj--multi-agent-ai-newsletter", "kind": "repo", "label": "felixggj/multi-agent-ai-newsletter (29\u2605) \u2014 Multi-Agent AI system that automatically retrieves the latest Football news and creates a newsletter", "url": "https://github.com/felixggj/multi-agent-ai-newsletter", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nomannayeem--langchain_crewai_gemini-ai_agents", "kind": "repo", "label": "NoManNayeem/Langchain_CrewAI_Gemini-AI_Agents (14\u2605) \u2014 Langchain_CrewAI_Gemini - An Gemini AI powered AI Agent (Multi-Agent) Project.", "url": "https://github.com/NoManNayeem/Langchain_CrewAI_Gemini-AI_Agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nousresearch--hermes-agent-self-evolution", "kind": "repo", "label": "NousResearch/hermes-agent-self-evolution (4550\u2605) \u2014 \u2692 Evolutionary self-improvement for Hermes Agent \u2014 optimize skills, prompts, and code using DSPy + GEPA", "url": "https://github.com/NousResearch/hermes-agent-self-evolution", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:karthikscale3--dspyground", "kind": "repo", "label": "karthikscale3/dspyground (313\u2605) \u2014 A tool kit for generating high quality prompts using DSPy GEPA optimizer", "url": "https://github.com/karthikscale3/dspyground", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:davidberenstein1957--dspydantic", "kind": "repo", "label": "davidberenstein1957/dspydantic (318\u2605) \u2014 DSPydantic: Auto-Optimize Your Prompts and Pydantic Models with DSPy", "url": "https://github.com/davidberenstein1957/dspydantic", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:omidzamani--dspy-skills", "kind": "repo", "label": "OmidZamani/dspy-skills (112\u2605) \u2014 Collection of Claude Skills for DSPy framework - program language models, optimize prompts, and build RAG pipelines systematically", "url": "https://github.com/OmidZamani/dspy-skills", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:laxminarayen--dspy-prompt-optimizer", "kind": "repo", "label": "Laxminarayen/dspy-prompt-optimizer (1\u2605) \u2014 Streamlit app to optimize prompts using all DSPy optimizers \u2014 BootstrapFewShot, MIPROv2, COPRO, Optuna, LabeledFewShot, GEPA. Upload a dataset, define inputs/target, compare optimizer scores side-by-s", "url": "https://github.com/Laxminarayen/dspy-prompt-optimizer", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mahir-isikli--ai-tinkerers-dspy-talk", "kind": "repo", "label": "Mahir-Isikli/ai-tinkerers-dspy-talk (19\u2605) \u2014 DSPy prompt optimization demo from AI Tinkerers presentation", "url": "https://github.com/Mahir-Isikli/ai-tinkerers-dspy-talk", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mozilla-ai--visual-dspy", "kind": "repo", "label": "mozilla-ai/visual-dspy (15\u2605) \u2014 Visual demo of DSPy's prompt optimization on Gradio", "url": "https://github.com/mozilla-ai/visual-dspy", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:kazkozdev--dspy-optimization-patterns", "kind": "repo", "label": "KazKozDev/dspy-optimization-patterns (12\u2605) \u2014 A production framework for DSPy implementing the Teacher-Student pattern. Distill the reasoning of expensive models (Teacher) into optimized prompts for cheap, fast models (Student) to reduce inferenc", "url": "https://github.com/KazKozDev/dspy-optimization-patterns", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nielsgl--dspy-optimizer", "kind": "repo", "label": "nielsgl/dspy-optimizer (4\u2605) \u2014 DSPy Prompt Optimizer", "url": "https://github.com/nielsgl/dspy-optimizer", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:heathbrew--qdrant-dspy-colbertv2", "kind": "repo", "label": "heathbrew/Qdrant-Dspy-ColbertV2 (5\u2605) \u2014 building an efficient local semantic search application using ColBERT (Contextualized Late Interaction over BERT), DSPy (algorithmically optimizing LM prompts and weights), and Qdrant Vector Database.", "url": "https://github.com/heathbrew/Qdrant-Dspy-ColbertV2", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:immu4989--dspy-security-bench", "kind": "repo", "label": "immu4989/dspy-security-bench (4\u2605) \u2014 Measure how DSPy prompt optimization affects the prompt-injection robustness of agentic LLM programs, using AgentDojo's attack suite.", "url": "https://github.com/immu4989/dspy-security-bench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:emirhan-gazi--kaizen", "kind": "repo", "label": "emirhan-gazi/kaizen (7\u2605) \u2014 Continuous prompt optimization for AI applications. Collect feedback, auto-optimize with DSPy, deliver as reviewable PRs.", "url": "https://github.com/emirhan-gazi/kaizen", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:juyangbai--mas-promptbench", "kind": "repo", "label": "juyangbai/MAS-PromptBench (5\u2605) \u2014 A reproducible benchmark for studying when prompt optimization improves multi-agent LLM systems.", "url": "https://github.com/juyangbai/MAS-PromptBench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:yotambraun--flowprompt", "kind": "repo", "label": "yotambraun/flowprompt (6\u2605) \u2014 Type-safe prompt management with automatic optimization for LLMs. DSPy-style optimization, A/B testing, multimodal support, and more.", "url": "https://github.com/yotambraun/flowprompt", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aijnek--dspy_multimodal", "kind": "repo", "label": "aijnek/dspy_multimodal (2\u2605) \u2014 sample code for automatic multimodal prompt optimization using DSPy", "url": "https://github.com/aijnek/dspy_multimodal", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:asirwad--dspy-prompt-auto-optimizer", "kind": "repo", "label": "Asirwad/DSPy-Prompt-Auto-Optimizer (2\u2605) \u2014 A learning-focused exploration of programmatic prompt optimization using the DSPy framework.", "url": "https://github.com/Asirwad/DSPy-Prompt-Auto-Optimizer", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:saibhaskerraju--dspy-optimization", "kind": "repo", "label": "saibhaskerraju/dspy-optimization (2\u2605) \u2014 This Repository gives an Introduction to Dspy. The repo has all examples that explains the importance of using Dspy in regular projects when comparing it with prompt engineering.", "url": "https://github.com/saibhaskerraju/dspy-optimization", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jordan-barrett-jm--llm-page-extraction-gepa-dspy", "kind": "repo", "label": "jordan-barrett-jm/llm-page-extraction-gepa-dspy (4\u2605) \u2014 Demonstrates how to use the GEPA prompt optimizer in DSPy to improve a financial statement page extractor.", "url": "https://github.com/jordan-barrett-jm/llm-page-extraction-gepa-dspy", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:tosinamuda--llama-finetuning-dspy", "kind": "repo", "label": "tosinamuda/llama-finetuning-dspy (5\u2605) \u2014 DSPy GEPA synthetic data generation for instruction tuning Llama 3 on consulting one-pager and executive slide tasks. Outputs JSONL for AWS SageMaker. Uses uv. Works with watsonx, OpenAI, or OpenRoute", "url": "https://github.com/tosinamuda/llama-finetuning-dspy", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ai-maker-space--dspyevent", "kind": "repo", "label": "AI-Maker-Space/DSPyEvent (1\u2605) \u2014 DSPy Prompt Optimization Event", "url": "https://github.com/AI-Maker-Space/DSPyEvent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:salaivishnu123--adaptive-rag-secure-assistant", "kind": "repo", "label": "salaivishnu123/adaptive-rag-secure-assistant (0\u2605) \u2014 Dspy prompt optimization", "url": "https://github.com/salaivishnu123/adaptive-rag-secure-assistant", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:curiositech--prompt-learning-mcp", "kind": "repo", "label": "curiositech/prompt-learning-mcp (2\u2605) \u2014 Stateful prompt optimization MCP server with embedding-based learning. Uses APE, OPRO, DSPy patterns.", "url": "https://github.com/curiositech/prompt-learning-mcp", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nivlewd1--prompt-optimizer", "kind": "repo", "label": "nivlewd1/prompt-optimizer (2\u2605) \u2014 MCP Server that offers high-performance prompt optimization server with real-time streaming, pattern-based enhancement, and comprehensive session management capabilities.", "url": "https://github.com/nivlewd1/prompt-optimizer", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:armanhm--dspy-prompt-optimization-simulator", "kind": "repo", "label": "armanhm/DsPy-Prompt-Optimization-Simulator (0\u2605) \u2014 DsPy Prompt Optimization Simulator", "url": "https://github.com/armanhm/DsPy-Prompt-Optimization-Simulator", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:longntl-namitech--promptoptimization_mlflow-dspy", "kind": "repo", "label": "longntl-namitech/PromptOptimization_MLFlow-DSPy (1\u2605)", "url": "https://github.com/longntl-namitech/PromptOptimization_MLFlow-DSPy", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:hersh-gupta--safety-prompt-optimization", "kind": "repo", "label": "hersh-gupta/safety-prompt-optimization (0\u2605) \u2014 Using dspy for safety optimization", "url": "https://github.com/hersh-gupta/safety-prompt-optimization", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nafew-azim--dspy-frameworks-mipro-better-together-", "kind": "repo", "label": "nafew-azim/DSPy-FRAMEWORKS-MIPRO-BETTER-TOGETHER- (2\u2605) \u2014 A modular implementation of DSPy using MIPRO and BetterTogether optimizers to automate and enhance prompt engineering for LLMs. Includes joint instruction and example optimization, as well as hybrid p", "url": "https://github.com/nafew-azim/DSPy-FRAMEWORKS-MIPRO-BETTER-TOGETHER-", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ridhima-jain--dspy-prompt-optimization", "kind": "repo", "label": "Ridhima-Jain/dspy-prompt-optimization (0\u2605) \u2014 Automated prompt optimization using DSPy BootstrapFewShot for LLM workflows", "url": "https://github.com/Ridhima-Jain/dspy-prompt-optimization", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aymeric-roucher--gaia", "kind": "repo", "label": "aymeric-roucher/GAIA (152\u2605) \u2014 Beating the GAIA benchmark with Transformers Agents. \ud83d\ude80", "url": "https://github.com/aymeric-roucher/GAIA", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:gaia-agent--gaia-agent", "kind": "repo", "label": "gaia-agent/gaia-agent (16\u2605) \u2014 GAIA-benchmark-ready super agent built on AI SDK v6 ToolLoopAgent", "url": "https://github.com/gaia-agent/gaia-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:chiarapaglioni--gaia-agents", "kind": "repo", "label": "chiarapaglioni/GAIA-agents (4\u2605) \u2014 Final project for the Hugging Face AI Agents course testing smolagents on the GAIA benchmark", "url": "https://github.com/chiarapaglioni/GAIA-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:kvpratama--gaia-agent", "kind": "repo", "label": "kvpratama/gaia-agent (6\u2605) \u2014 LangGraph-based AI agents tackling complex tasks from the GAIA benchmark. Final project for the Hugging Face Agents course. Includes ReAct, Reflection, Plan-Execute, and Multi-Agent systems.", "url": "https://github.com/kvpratama/gaia-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sassarini-marco--gaia-agent", "kind": "repo", "label": "sassarini-marco/gaia-agent (5\u2605) \u2014 A modular benchmarking framework for evaluating the performance and collaboration of multi-agent AI systems against the GAIA (General AI Agent) benchmark suite", "url": "https://github.com/sassarini-marco/gaia-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:e-alizadeh--gaia-agent", "kind": "repo", "label": "e-alizadeh/GAIA-Agent (6\u2605) \u2014 \ud83e\udd16 AI Agent for answering GAIA Benchmark questions (Final Assignment of HuggingFace \ud83e\udd17 Agents Course)", "url": "https://github.com/e-alizadeh/GAIA-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:stanford-ppl--agentic_benchmarking_for_gaia", "kind": "repo", "label": "stanford-ppl/Agentic_Benchmarking_For_GAIA (4\u2605)", "url": "https://github.com/stanford-ppl/Agentic_Benchmarking_For_GAIA", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:fisherman611--gaia-agent", "kind": "repo", "label": "fisherman611/gaia-agent (5\u2605) \u2014 \"GAIA Agent: An AI system automating solutions for the GAIA benchmark with tools for reasoning, code execution, data interpretation, and multimodal tasks.\"", "url": "https://github.com/fisherman611/gaia-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jungwoonshin--agent-benchmark", "kind": "repo", "label": "jungwoonshin/agent-benchmark (0\u2605) \u2014 GAIA Dataset Challenge", "url": "https://github.com/jungwoonshin/agent-benchmark", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sunjilgahatraj1--autonomous-ai-agent", "kind": "repo", "label": "sunjilgahatraj1/Autonomous-AI-Agent (0\u2605) \u2014 GAIA Benchmark Autonomous AI Agent", "url": "https://github.com/sunjilgahatraj1/Autonomous-AI-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sagar-garg--ai-agent-huggingface-project", "kind": "repo", "label": "sagar-garg/ai-agent-huggingface-project (0\u2605) \u2014 Final Project Passing GAIA benchmark", "url": "https://github.com/sagar-garg/ai-agent-huggingface-project", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:brauliopf--agent-gaia-benchmark", "kind": "repo", "label": "brauliopf/Agent-GAIA-Benchmark (0\u2605)", "url": "https://github.com/brauliopf/Agent-GAIA-Benchmark", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jomonsugi--gaia-benchmark-agent", "kind": "repo", "label": "Jomonsugi/gaia-benchmark-agent (0\u2605) \u2014 An agentic framework that answers GAIA benchmark questions", "url": "https://github.com/Jomonsugi/gaia-benchmark-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:abdulmunimjemal--gaia-benchmark", "kind": "repo", "label": "abdulmunimjemal/gaia-benchmark (0\u2605) \u2014 Benchmark Claude Agent SDK against GAIA ", "url": "https://github.com/abdulmunimjemal/gaia-benchmark", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:daksh-chaudhary99--agent_gaia_benchmark", "kind": "repo", "label": "Daksh-Chaudhary99/Agent_GAIA_Benchmark (0\u2605) \u2014 AI Agent for optimal performance across the GAIA benchmark", "url": "https://github.com/Daksh-Chaudhary99/Agent_GAIA_Benchmark", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:andrea-acampora--gaia-benchmark-agent", "kind": "repo", "label": "andrea-acampora/gaia-benchmark-agent (0\u2605) \u2014 Repository with a LangGraph general purpose AI Agent for final assignment of HuggingFace Agents course.", "url": "https://github.com/andrea-acampora/gaia-benchmark-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:saidkaban--gaia-benchmark-agent", "kind": "repo", "label": "saidkaban/gaia-benchmark-agent (0\u2605)", "url": "https://github.com/saidkaban/gaia-benchmark-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jaimemontea--agent_gaia_benchmark", "kind": "repo", "label": "jaimeMontea/agent_gaia_benchmark (0\u2605) \u2014 This is an AI Agent capable of answering some questions in the GAIA benchmark.", "url": "https://github.com/jaimeMontea/agent_gaia_benchmark", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:rcarioni--gaia-benchmark-agent", "kind": "repo", "label": "rcarioni/GAIA-benchmark-agent (0\u2605)", "url": "https://github.com/rcarioni/GAIA-benchmark-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:iamvibhav--gaia-benchmark-agent", "kind": "repo", "label": "iamvibhav/Gaia-Benchmark-Agent (1\u2605) \u2014 An intelligent AI agent designed to tackle the GAIA benchmark with advanced reasoning capabilities and multi-modal tools.", "url": "https://github.com/iamvibhav/Gaia-Benchmark-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nicholasgoh--fastapi-mcp-langgraph-template", "kind": "repo", "label": "NicholasGoh/fastapi-mcp-langgraph-template (550\u2605) \u2014 A modern template for agentic orchestration \u2014 built for rapid iteration and scalable deployment using highly customizable, community-supported tools like MCP, LangGraph, and more.", "url": "https://github.com/NicholasGoh/fastapi-mcp-langgraph-template", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sonnysangha--ai-agent-langchain-langgraph-convex-clerk-ibm-wxtools-nextjs15", "kind": "repo", "label": "sonnysangha/ai-agent-langchain-langgraph-convex-clerk-ibm-wxtools-nextjs15 (151\u2605) \u2014 Modern Next.js 15 AI agent platform with Claude 3.5, prompt caching, and intelligent tool orchestration via IBM WxFlows (turns any data source into a tool)", "url": "https://github.com/sonnysangha/ai-agent-langchain-langgraph-convex-clerk-ibm-wxtools-nextjs15", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:foreveryh--mentis", "kind": "repo", "label": "foreveryh/mentis (298\u2605) \u2014 Mentis: A powerful multi-agent orchestration framework built on LangGraph.", "url": "https://github.com/foreveryh/mentis", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:fareedkhan-dev--scalable-rag-pipeline", "kind": "repo", "label": "FareedKhan-dev/scalable-rag-pipeline (148\u2605) \u2014 A scalable RAG platform combining LangGraph agents, hybrid retrieval (Vector+Graph), and Ray orchestration on Kubernetes.", "url": "https://github.com/FareedKhan-dev/scalable-rag-pipeline", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:fancy1108--clutch", "kind": "repo", "label": "fancy1108/Clutch (68\u2605) \u2014 Local AI multi-agent orchestration desktop app (Tauri \u00b7 LangGraph)", "url": "https://github.com/fancy1108/Clutch", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:laxmimerit--agentic-rag-with-langgraph-and-ollama", "kind": "repo", "label": "laxmimerit/Agentic-RAG-with-LangGraph-and-Ollama (36\u2605) \u2014 Building production-ready Retrieval-Augmented Generation (RAG) systems with LangGraph orchestration and local Ollama models for privacy-preserving AI applications.", "url": "https://github.com/laxmimerit/Agentic-RAG-with-LangGraph-and-Ollama", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:bernatsampera--event-deep-research", "kind": "repo", "label": "bernatsampera/event-deep-research (248\u2605) \u2014 AI Agent that researches the lives of historical figures and extracts events into structured JSON timelines using LangGraph multi-agent orchestration.", "url": "https://github.com/bernatsampera/event-deep-research", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:realyinchen--agenthub", "kind": "repo", "label": "realyinchen/AgentHub (98\u2605) \u2014 A modular AI agent framework built with FastAPI (backend) and TypeScript (frontend), integrating LangChain/LangGraph-based agents for conversational intelligence, reasoning, and tool orchestration.", "url": "https://github.com/realyinchen/AgentHub", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:aws-solutions-library-samples--guidance-for-multi-agent-orchestration-langgraph-on-aws", "kind": "repo", "label": "aws-solutions-library-samples/guidance-for-multi-agent-orchestration-langgraph-on-aws (35\u2605) \u2014 This Guidance demonstrates how to effectively orchestrate multiple specialized AI agents to solve complex customer support challenges through different coordination mechanisms on AWS.", "url": "https://github.com/aws-solutions-library-samples/guidance-for-multi-agent-orchestration-langgraph-on-aws", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sinanuozdemir--advanced-agentic-ai-in-three-weeks", "kind": "repo", "label": "sinanuozdemir/advanced-agentic-ai-in-three-weeks (32\u2605) \u2014 Build agents and workflows with RAG, MCP, harnesses, & multi-agent orchestration in a 3-week cohort", "url": "https://github.com/sinanuozdemir/advanced-agentic-ai-in-three-weeks", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:bobmatnyc--claude-multiagent-pm", "kind": "repo", "label": "bobmatnyc/claude-multiagent-pm (30\u2605) \u2014 Claude Multi-Agent Project Management Framework - AI-driven orchestration with LangGraph and OpenAI integration", "url": "https://github.com/bobmatnyc/claude-multiagent-pm", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:langtail--ai-orchestra", "kind": "repo", "label": "langtail/ai-orchestra (83\u2605) \u2014 Simple orchestration for AI Agents built around Vercel's streamText. Lightweight alternative to LangGraph for agent handoffs and state transitions.", "url": "https://github.com/langtail/ai-orchestra", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:samirpatil2000--agentic-template", "kind": "repo", "label": "samirpatil2000/agentic-template (33\u2605) \u2014 A FastAPI-powered workflow orchestration system that integrates LangGraph to design, run, and manage AI Agents workflows", "url": "https://github.com/samirpatil2000/agentic-template", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ani-in--multi-agent-customer-support", "kind": "repo", "label": "ANI-IN/Multi-Agent-Customer-Support (21\u2605) \u2014 Multi-agent AI customer support system for a digital music store. Built with LangGraph, Gradio, and the Chinook database. Features supervisor   routing, music catalog & invoice agents, human-in-the-lo", "url": "https://github.com/ANI-IN/Multi-Agent-Customer-Support", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:harimxchoi--langgraph-travel-agent", "kind": "repo", "label": "HarimxChoi/langgraph-travel-agent (17\u2605) \u2014 Production-ready LangGraph multi-agent system for travel planning. Async parallel orchestration across Amadeus, Hotelbeds, Twilio, HubSpot.", "url": "https://github.com/HarimxChoi/langgraph-travel-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jonathanscholtes--azure-ai-foundry-agentic-workshop", "kind": "repo", "label": "jonathanscholtes/azure-ai-foundry-agentic-workshop (26\u2605) \u2014 Workshop for building intelligent AI solutions using Azure AI Foundry, featuring Vector Search, RAG, Agentic AI, and multi-agent orchestration with LangChain and Azure AI Search.", "url": "https://github.com/jonathanscholtes/azure-ai-foundry-agentic-workshop", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:himanshumohanty-git24--rakshaquant", "kind": "repo", "label": "HimanshuMohanty-Git24/RakshaQuant (36\u2605) \u2014 \ud83d\udee1\ufe0f RakshaQuant - AI-powered paper trading for NSE using LangGraph multi-agent orchestration. Features 4 LLM agents, learning feedback loop, LangSmith observability & risk guardrails. Built with Groq, ", "url": "https://github.com/HimanshuMohanty-Git24/RakshaQuant", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:extrawest--fastapi-langgraph-chatbot-with-vector-store-memory-mcp-tools-and-voice-mode", "kind": "repo", "label": "extrawest/fastapi-langgraph-chatbot-with-vector-store-memory-mcp-tools-and-voice-mode (25\u2605) \u2014 A scalable AI chatbot platform built with FastAPI and LangGraph, featuring multi-agent orchestration, multi-tenant vector storage, cross-chat memory, and voice call capabilities through LiveKit integr", "url": "https://github.com/extrawest/fastapi-langgraph-chatbot-with-vector-store-memory-mcp-tools-and-voice-mode", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nvidia-ai-blueprints--retail-shopping-assistant", "kind": "repo", "label": "NVIDIA-AI-Blueprints/retail-shopping-assistant (75\u2605) \u2014 The Retail Shopping Assistant is an AI-powered blueprint that provides a comprehensive interface for an intelligent retail shopping advisor. Built with LangGraph for agent orchestration, it features m", "url": "https://github.com/NVIDIA-AI-Blueprints/retail-shopping-assistant", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:azurecosmosdb--multi-agent-langgraph", "kind": "repo", "label": "AzureCosmosDB/multi-agent-langgraph (6\u2605) \u2014 A sample for multi-agent orchestration in Python using Azure Cosmos DB with LangGraph", "url": "https://github.com/AzureCosmosDB/multi-agent-langgraph", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:yaalalabs--agent-kernel", "kind": "repo", "label": "yaalalabs/agent-kernel (58\u2605) \u2014 The Operating System for Scalable Enterprise AI Agents - Run, orchestrate, and deploy Compliant Enterprise AI Agents at scale across frameworks, without lock-in, rewrites or fragile glue code. Native ", "url": "https://github.com/yaalalabs/agent-kernel", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:prsaurabh--agentic-rag-orchestrated", "kind": "repo", "label": "prsaurabh/agentic-rag-orchestrated (9\u2605) \u2014 LangGraph orchestrated RAG pipeline with grading, rewriting, and hallucination check", "url": "https://github.com/prsaurabh/agentic-rag-orchestrated", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:youhonda30--agent-skill-bus", "kind": "repo", "label": "youhonda30/agent-skill-bus (2\u2605) \u2014 Self-improving task orchestration framework for AI agent systems. DAG-based task queue + automatic skill quality monitoring + external change detection. Framework-agnostic (OpenClaw, Claude Code, Code", "url": "https://github.com/youhonda30/agent-skill-bus", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:martymcenroe--assemblyzero", "kind": "repo", "label": "martymcenroe/AssemblyZero (105\u2605) \u2014 Parameterized multi-agent orchestration framework for Claude Code and Gemini", "url": "https://github.com/martymcenroe/AssemblyZero", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:bjornmelin--dev-pro-agents", "kind": "repo", "label": "BjornMelin/dev-pro-agents (12\u2605) \u2014 \ud83e\udd16 Advanced multi-agent orchestration framework built with LangGraph - Coordinate specialized AI agents for autonomous development, research, testing, and documentation workflows with intelligent task ", "url": "https://github.com/BjornMelin/dev-pro-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:tencentcloud--tencentdb-agent-memory", "kind": "repo", "label": "TencentCloud/TencentDB-Agent-Memory (7010\u2605) \u2014 TencentDB Agent Memory delivers fully local long-term memory for AI Agents via a 4-tier progressive pipeline, with zero external API dependencies.", "url": "https://github.com/TencentCloud/TencentDB-Agent-Memory", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:memvid--memvid", "kind": "repo", "label": "memvid/memvid (15730\u2605) \u2014 Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.", "url": "https://github.com/memvid/memvid", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:teleai-uagi--awesome-agent-memory", "kind": "repo", "label": "TeleAI-UAGI/Awesome-Agent-Memory (513\u2605) \u2014 Curated systems, benchmarks, and papers etc. on memory for LLMs/MLLMs --- long-term context, retrieval, and reasoning.", "url": "https://github.com/TeleAI-UAGI/Awesome-Agent-Memory", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:lycheemem--lycheemem", "kind": "repo", "label": "LycheeMem/LycheeMem (1114\u2605) \u2014 Lightweight Long-Term Memory for LLM Agents.", "url": "https://github.com/LycheeMem/LycheeMem", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:farzad-r--agentic-longterm-memory", "kind": "repo", "label": "Farzad-R/Agentic-LongTerm-Memory (54\u2605) \u2014 This project contains a step-by-step guide on how to design an advanced agentic memory for your LLM based applications.", "url": "https://github.com/Farzad-R/Agentic-LongTerm-Memory", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:matrixorigin--memoria", "kind": "repo", "label": "matrixorigin/Memoria (401\u2605) \u2014 Secure memory management for AI Agents \u2022 Ensures data integrity \u2022 Reduces hallucinations \u2022 Maintains consistent long-term context", "url": "https://github.com/matrixorigin/Memoria", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:dataojitori--nocturne_memory", "kind": "repo", "label": "Dataojitori/nocturne_memory (1258\u2605) \u2014 A lightweight, rollbackable, and visual Long-Term Memory Server for MCP Agents. Say goodbye to Vector RAG and amnesia. Empower your AI with persistent, graph-like structured memory across any model, s", "url": "https://github.com/Dataojitori/nocturne_memory", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:akirusprod--llm-agent", "kind": "repo", "label": "AkiRusProd/llm-agent (55\u2605) \u2014 LLM using long-term memory through vector database", "url": "https://github.com/AkiRusProd/llm-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:timan-group--plugmem", "kind": "repo", "label": "TIMAN-group/PlugMem (160\u2605) \u2014 ICML 2026 \u00b7 Plug-and-play long-term memory for LLM agents", "url": "https://github.com/TIMAN-group/PlugMem", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:edeai--openflux", "kind": "repo", "label": "EDEAI/OpenFlux (221\u2605) \u2014 \u26a1 Open-source AI Agent desktop client \u2014 multi-LLM, long-term memory, browser automation & tool orchestration | Tauri v2", "url": "https://github.com/EDEAI/OpenFlux", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:xortexai--xmem", "kind": "repo", "label": "XortexAI/XMem (232\u2605) \u2014 Xmem is a India's First open source multi-modal, multi-agentic long\u2011term memory layer for AI agents. ", "url": "https://github.com/XortexAI/XMem", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:uukuguy--speechless", "kind": "repo", "label": "uukuguy/speechless (110\u2605) \u2014 LLM based agents with proactive interactions, long-term memory, external tool integration, and local deployment capabilities.", "url": "https://github.com/uukuguy/speechless", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:morettt--my-neuro", "kind": "repo", "label": "morettt/my-neuro (1303\u2605) \u2014 This project lets you create your own AI desktop companion with customizable characters and voice conversations that respond in just 1 second. Features include long-term memory, visual recognition, vo", "url": "https://github.com/morettt/my-neuro", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mig-nju--personavlm", "kind": "repo", "label": "MiG-NJU/PersonaVLM (109\u2605) \u2014 [CVPR 2026 Highlight] PersonaVLM: Long-Term Personalized Multimodal LLMs", "url": "https://github.com/MiG-NJU/PersonaVLM", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:iaar-shanghai--awesome-ai-memory", "kind": "repo", "label": "IAAR-Shanghai/Awesome-AI-Memory (1058\u2605) \u2014 Awesome AI Memory | LLM Memory | A curated knowledge base on AI memory for LLMs and agents, covering long-term memory, reasoning, retrieval, and memory-native system design.  Awesome-AI-Memory \u662f\u4e00\u4e2a \u96c6\u4e2d\u5f0f", "url": "https://github.com/IAAR-Shanghai/Awesome-AI-Memory", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:teleai-uagi--telemem", "kind": "repo", "label": "TeleAI-UAGI/telemem (470\u2605) \u2014 TeleMem is a high-performance drop-in replacement for Mem0, featuring semantic deduplication, long-term dialogue memory, and multimodal video reasoning.", "url": "https://github.com/TeleAI-UAGI/telemem", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:wuwangzhang1216--opendb", "kind": "repo", "label": "wuwangzhang1216/openDB (19\u2605) \u2014 AI-native local database for files, search, and long-term agent memory.", "url": "https://github.com/wuwangzhang1216/openDB", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ob-labs--memory-powermem", "kind": "repo", "label": "ob-labs/memory-powermem (27\u2605) \u2014 openclaw(clawdbot) Plugin: give your bot long-term memory with PowerMem\u2014smart extraction, Ebbinghaus recall, multi-agent isolation.", "url": "https://github.com/ob-labs/memory-powermem", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sibyl-labs--sibyl-memory", "kind": "repo", "label": "Sibyl-Labs/Sibyl-Memory (91\u2605) \u2014 Durable, file-based long-term memory for AI agents. Five-package plugin family: SDK, CLI, MCP server, Hermes adapter, and a LangGraph BaseStore. No vector database, no embeddings.", "url": "https://github.com/Sibyl-Labs/Sibyl-Memory", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:memtomem--memtomem", "kind": "repo", "label": "memtomem/memtomem (10\u2605) \u2014 Markdown-first, long-term memory infrastructure for AI agents. Hybrid BM25 + semantic search across markdown/code files via MCP.", "url": "https://github.com/memtomem/memtomem", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jo-inc--pi-mem", "kind": "repo", "label": "jo-inc/pi-mem (66\u2605) \u2014 Plain-Markdown persistent memory for AI coding agents. Long-term facts, daily logs, scratchpad, and semantic search \u2014 works with pi, Claude Code, and any LLM agent.", "url": "https://github.com/jo-inc/pi-mem", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:gizclaw--flowcraft", "kind": "repo", "label": "GizClaw/flowcraft (491\u2605) \u2014 Production-grade Go SDK for building AI agents with long-term memory, knowledge retrieval, and voice \u2014 runnable as a library, a daemon, or a real-time pipeline.", "url": "https://github.com/GizClaw/flowcraft", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:goodai--goodai-ltm-benchmark", "kind": "repo", "label": "GoodAI/goodai-ltm-benchmark (87\u2605) \u2014 A library for benchmarking the Long Term Memory and Continual learning capabilities of  LLM based agents. With all the tests and code you need to evaluate your own agents. See more in the blogpost:", "url": "https://github.com/GoodAI/goodai-ltm-benchmark", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:k-kolomeitsev--data-structure-protocol", "kind": "repo", "label": "k-kolomeitsev/data-structure-protocol (57\u2605) \u2014 Graph-based long-term memory skill for AI (LLM) coding agents \u2014 faster context, fewer tokens, safer refactors", "url": "https://github.com/k-kolomeitsev/data-structure-protocol", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:markmbain--aius", "kind": "repo", "label": "markmbain/aius (62\u2605) \u2014 The long-term memory for your Superagents \ud83e\udd77and LLMs \ud83e\udd16. Built with GraphRAG, Knowledge graphs and autonomous ai agents", "url": "https://github.com/markmbain/aius", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:russellcanfield--wingman-ai", "kind": "repo", "label": "RussellCanfield/wingman-ai (32\u2605) \u2014 A distributed platform for AI Agents. Supports multiple LLMs, orchestration/subagents, long term memory, dynamic UI and more.", "url": "https://github.com/RussellCanfield/wingman-ai", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:pinkpixel-dev--mem0-mcp", "kind": "repo", "label": "pinkpixel-dev/mem0-mcp (98\u2605) \u2014 \u2728 mem0 MCP Server: A memory system using mem0 for AI applications with model context protocl (MCP) integration. Enables long-term memory for AI agents as a drop-in MCP server.", "url": "https://github.com/pinkpixel-dev/mem0-mcp", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:letta-ai--learning-sdk", "kind": "repo", "label": "letta-ai/learning-sdk (44\u2605) \u2014 Drop-in SDK for adding continual learning and long-term memory to any LLM agent.", "url": "https://github.com/letta-ai/learning-sdk", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:tostechbr--memoryclaw", "kind": "repo", "label": "tostechbr/memoryClaw (8\u2605) \u2014 Universal Memory & Context Engine (MCP Server) to give Long-Term Memory to AI Agents.", "url": "https://github.com/tostechbr/memoryClaw", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sqliteai--adam", "kind": "repo", "label": "sqliteai/adam (97\u2605) \u2014 An embeddable cross-platform AI agent library written in C. Cloud and local LLMs, tool calling, long-term memory, voice, sessions, research mode, self-evolving loops. The SQLite of agent frameworks: s", "url": "https://github.com/sqliteai/adam", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:achetronic--magec", "kind": "repo", "label": "achetronic/magec (99\u2605) \u2014 Multi-agent AI platform with voice and text control. Visual workflows, web interface, and chat integrations (Telegram, Discord, Slack). Long-term memory, any LLM backend, extensible via MCP tools.", "url": "https://github.com/achetronic/magec", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:visendi-labs--uffe", "kind": "repo", "label": "visendi-labs/uffe (11\u2605) \u2014 A sub-100 lines, self-aware, independent, somewhat capabable LLM Agent with long term memory", "url": "https://github.com/visendi-labs/uffe", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mine-ustc--atommem", "kind": "repo", "label": "MINE-USTC/AtomMem (23\u2605) \u2014 AtomMem: a long-term memory system for personalized LLM agents.", "url": "https://github.com/MINE-USTC/AtomMem", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:0verl1nk--papersage", "kind": "repo", "label": "0verL1nk/PaperSage (36\u2605) \u2014 \ud83d\udcda AI-powered research reading workbench. Project-based paper Q&A with Hybrid RAG, multi-agent workflows (ReAct/Plan-Act/RePlan), long-term memory, and traceable evidence. Built with LangChain + LangGr", "url": "https://github.com/0verL1nk/PaperSage", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mmx920--ebbingflow", "kind": "repo", "label": "MMX920/ebbingflow (108\u2605) \u2014 \u771f\u6b63\u8bb0\u5f97\u4f4f\u4f60\u3001\u8ba4\u8bc6\u4f60\u3001\u968f\u4f60\u6210\u957f\u7684 AI \u957f\u6548\u8ba4\u77e5\u8bb0\u5fc6\u5f15\u64ce  Long-term Cognitive Memory Engine for LLM Agents", "url": "https://github.com/MMX920/ebbingflow", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sompote--tiger_bot", "kind": "repo", "label": "Sompote/Tiger_bot (21\u2605) \u2014 Agentic Swarm AI Agent with persistent long-term memory, multi-provider LLM support, token management, self-learning, and Telegram bot integration \u2014 designed for 24/7 autonomous operation on Linux.", "url": "https://github.com/Sompote/Tiger_bot", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:yunghuihsu--long-term-agentic-memory-with-langgraph", "kind": "repo", "label": "YunghuiHsu/Long-Term-Agentic-Memory-With-LangGraph (8\u2605) \u2014 Code examples and implementations from the course [Long-Term Agentic Memory with LangGraph](https://www.deeplearning.ai/short-courses/long-term-agentic-memory-with-langgraph/) by DeepLearning.AI.  Cou", "url": "https://github.com/YunghuiHsu/Long-Term-Agentic-Memory-With-LangGraph", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mhndayesh--easy-agentic-memory-system-easy-memory-", "kind": "repo", "label": "mhndayesh/Easy-agentic-memory-system-easy-memory- (16\u2605) \u2014 The Standalone Agentic Memory Tool is a lightweight drop-in proxy for standard LLMs. It provides two superpowers: On-Demand RAG to selectively search a massive semantic vector database, and Infinite A", "url": "https://github.com/mhndayesh/Easy-agentic-memory-system-easy-memory-", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ksm26--llms-as-operating-systems-agent-memory", "kind": "repo", "label": "ksm26/LLMs-as-Operating-Systems-Agent-Memory (8\u2605) \u2014 This repository introduces the Letta framework, empowering developers to build LLM-based agents with long-term, persistent memory and advanced reasoning capabilities. It leverages concepts from MemGPT", "url": "https://github.com/ksm26/LLMs-as-Operating-Systems-Agent-Memory", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:foundationagents--metagpt", "kind": "repo", "label": "FoundationAgents/MetaGPT (69241\u2605) \u2014 \ud83c\udf1f The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming", "url": "https://github.com/FoundationAgents/MetaGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:lynnooo--multi-agents", "kind": "repo", "label": "Lynnooo/Multi-Agents (0\u2605) \u2014 based in MetaGPT", "url": "https://github.com/Lynnooo/Multi-Agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:cerqwq--multi-agent", "kind": "repo", "label": "cerqwq/multi-agent (0\u2605) \u2014 Multi-Agent - \u591aAgent\u534f\u4f5c\u6846\u67b6 (inspired by MetaGPT)", "url": "https://github.com/cerqwq/multi-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:htoyll8--metagpt", "kind": "repo", "label": "htoyll8/MetaGPT (0\u2605) \u2014 Multi-agent System!", "url": "https://github.com/htoyll8/MetaGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mishuni--metagpt_bkd", "kind": "repo", "label": "Mishuni/MetaGPT_BKD (0\u2605) \u2014 multi-agent LLM security", "url": "https://github.com/Mishuni/MetaGPT_BKD", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ravindrakush11--metagpt_multi-agent-framework", "kind": "repo", "label": "ravindrakush11/MetaGPT_Multi-Agent-Framework (0\u2605)", "url": "https://github.com/ravindrakush11/MetaGPT_Multi-Agent-Framework", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:edgemoorlf--metagptagents", "kind": "repo", "label": "edgemoorlf/metagptagents (0\u2605) \u2014 A football commentator multi-agent framework based on metagpt", "url": "https://github.com/edgemoorlf/metagptagents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:rizusaki--ai-multi-agent-metagpt-guide", "kind": "repo", "label": "RizuSaki/ai-multi-agent-metagpt-guide (0\u2605) \u2014 Panduan Komprehensif AI Multi-Agent MetaGPT - Implementation Guide, Best Practices, dan Development Workflow", "url": "https://github.com/RizuSaki/ai-multi-agent-metagpt-guide", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:0325kai-huang--metagpt_write_story_multi-agents", "kind": "repo", "label": "0325Kai-Huang/MetaGPT_write_story_multi-agents (0\u2605)", "url": "https://github.com/0325Kai-Huang/MetaGPT_write_story_multi-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mormerneed--multi-agent-policy-discussion", "kind": "repo", "label": "mormerneed/multi-agent-policy-discussion (0\u2605) \u2014 \u57fa\u4e8eMetaGPT\u7684\u591a\u667a\u80fd\u4f53\u653f\u7b56\u8ba8\u8bba\u53ef\u89c6\u5316\u7cfb\u7edf", "url": "https://github.com/mormerneed/multi-agent-policy-discussion", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:lynx-1221--centadmetagpt", "kind": "repo", "label": "Lynx-1221/CentadMetagpt (1\u2605) \u2014 Multi-agent AI Framework to help simplify quantum computing algorithm development", "url": "https://github.com/Lynx-1221/CentadMetagpt", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:k-rks--metagpt", "kind": "repo", "label": "k-rks/MetaGPT (0\u2605) \u2014 \ud83c\udf1f The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming", "url": "https://github.com/k-rks/MetaGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sai-prannav--metagpt", "kind": "repo", "label": "Sai-Prannav/MetaGPT (0\u2605) \u2014 \ud83c\udf1f The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming", "url": "https://github.com/Sai-Prannav/MetaGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:smiroofingcompany--metagpt", "kind": "repo", "label": "Smiroofingcompany/MetaGPT (0\u2605) \u2014 \ud83c\udf1f The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming", "url": "https://github.com/Smiroofingcompany/MetaGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:khoabd--metagpt", "kind": "repo", "label": "khoabd/MetaGPT (0\u2605) \u2014 \ud83c\udf1f The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming", "url": "https://github.com/khoabd/MetaGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:void-kusho--metagpt", "kind": "repo", "label": "void-kusho/MetaGPT (0\u2605) \u2014 \ud83c\udf1f The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo", "url": "https://github.com/void-kusho/MetaGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:gridgentoo--metagpt", "kind": "repo", "label": "gridgentoo/MetaGPT (0\u2605) \u2014 The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo", "url": "https://github.com/gridgentoo/MetaGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:serkac1000--metagpt-1", "kind": "repo", "label": "serkac1000/MetaGPT-1 (0\u2605) \u2014 \ud83c\udf1f The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming", "url": "https://github.com/serkac1000/MetaGPT-1", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:violettance--metagpt", "kind": "repo", "label": "violettance/metagpt (0\u2605) \u2014 This project is a web application generated by metagpt, a multi-agent framework, to explore the capabilities of autonomous AI in software development", "url": "https://github.com/violettance/metagpt", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:daniel-flynn-github--multi-agent-collaboration-for-ffe-in-the-metagpt-framework", "kind": "repo", "label": "daniel-flynn-github/Multi-Agent-Collaboration-for-FFE-in-the-MetaGPT-Framework (0\u2605)", "url": "https://github.com/daniel-flynn-github/Multi-Agent-Collaboration-for-FFE-in-the-MetaGPT-Framework", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jjj54788--multi-agent-debate", "kind": "repo", "label": "jjj54788/multi-agent-debate (0\u2605) \u2014 \u57fa\u4e8e MetaGPT \u67b6\u6784\u7684\u591a\u667a\u80fd\u4f53\u8ba8\u8bba\u7cfb\u7edf\uff0c\u652f\u63018\u79cdAI\u667a\u80fd\u4f53\u534f\u540c\u8fa9\u8bba\uff0c\u5b9e\u65f6\u8bc4\u5206\u548c\u667a\u80fd\u603b\u7ed3", "url": "https://github.com/jjj54788/multi-agent-debate", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:vincentwei1021--awesome-ai-agent-frameworks", "kind": "repo", "label": "Vincentwei1021/awesome-ai-agent-frameworks (4\u2605) \u2014 \ud83e\udd16 AI Agent Framework Guide (\u4e2d\u6587) | Scion \u00b7 AutoGen \u00b7 CrewAI \u00b7 LangGraph \u00b7 MetaGPT \u00b7 Dify \u00b7 Coze \u2014 \u6df1\u5ea6\u5bf9\u6bd4 + \u9009\u578b\u51b3\u7b56\u6811 | Chinese developer guide for choosing the right multi-agent framework", "url": "https://github.com/Vincentwei1021/awesome-ai-agent-frameworks", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:arvind-sundararajan--metagpt-sd-optimizer", "kind": "repo", "label": "arvind-sundararajan/metagpt-sd-optimizer (0\u2605) \u2014 A sophisticated multi-agent implementation by Arvind Sundararajan solving the complex problem of optimizing software development workflows using Bayesian inference and latency-sensitive orchestration", "url": "https://github.com/arvind-sundararajan/metagpt-sd-optimizer", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:neverpanick--lv_metagpt", "kind": "repo", "label": "neverpanick/LV_METAGPT (0\u2605) \u2014 **LV_METAGPT** is an autonomous multi-agent software framework transforming text prompts into complete apps. Like ChatDev, it orchestrates LLM agents (PM, Architect, Engineer, QA) to manage the full S", "url": "https://github.com/neverpanick/LV_METAGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:open-sourcery-umd--impact-of-agent-personality-on-multi-agent-system-performance", "kind": "repo", "label": "Open-Sourcery-UMD/Impact-of-Agent-Personality-on-Multi-Agent-System-Performance (0\u2605) \u2014 Explores how agent personalities (detailed, succinct, critical) affect performance in MetaGPT\u2019s fixed-role multi-agent system. Evaluates correctness, speed, and collaboration on coding benchmarks. Inc", "url": "https://github.com/Open-Sourcery-UMD/Impact-of-Agent-Personality-on-Multi-Agent-System-Performance", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:joyozhang333-lgtm--awesome-ai-organization", "kind": "repo", "label": "joyozhang333-lgtm/awesome-ai-organization (3\u2605) \u2014 Build your AI-powered team. Frameworks, role templates, workflows, and playbooks for running an organization with AI employees.", "url": "https://github.com/joyozhang333-lgtm/awesome-ai-organization", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:xinxin2021110--inkrealm", "kind": "repo", "label": "xinxin2021110/InkRealm (4\u2605) \u2014 InkRealm is a multi-agent storytelling system for character recreation and co-writing. Inspired by MetaGPT, it uses structured roles, memory, and retrieval to keep characters consistent. It also suppo", "url": "https://github.com/xinxin2021110/InkRealm", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:octadecimal-ai--hydra-agent-orchestration-showcase", "kind": "repo", "label": "octadecimal-ai/hydra-agent-orchestration-showcase (0\u2605) \u2014 Sanitized portfolio mirror: multi-agent orchestration, adapters, MCP patterns, AdminJS and observability", "url": "https://github.com/octadecimal-ai/hydra-agent-orchestration-showcase", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:tauricresearch--tradingagents", "kind": "repo", "label": "TauricResearch/TradingAgents (91540\u2605) \u2014 TradingAgents: Multi-Agents LLM Financial Trading Framework", "url": "https://github.com/TauricResearch/TradingAgents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:openai--openai-agents-python", "kind": "repo", "label": "openai/openai-agents-python (27705\u2605) \u2014 A lightweight, powerful framework for multi-agent workflows", "url": "https://github.com/openai/openai-agents-python", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:open-multi-agent--open-multi-agent", "kind": "repo", "label": "open-multi-agent/open-multi-agent (6527\u2605) \u2014 TypeScript multi-agent orchestration framework. Describe a goal, a coordinator decomposes it into a task DAG that runs on any LLM: Claude, ChatGPT, Gemini, DeepSeek, or local models. ", "url": "https://github.com/open-multi-agent/open-multi-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:lazyagi--lazyllm", "kind": "repo", "label": "LazyAGI/LazyLLM (3855\u2605) \u2014 Easiest and laziest way for  building multi-agent LLMs applications.", "url": "https://github.com/LazyAGI/LazyLLM", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:trypromptly--llmstack", "kind": "repo", "label": "trypromptly/LLMStack (2304\u2605) \u2014 No-code multi-agent framework to build LLM Agents, workflows and applications with your data", "url": "https://github.com/trypromptly/LLMStack", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:internlm--mindsearch", "kind": "repo", "label": "InternLM/MindSearch (6884\u2605) \u2014 \ud83d\udd0d An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT)", "url": "https://github.com/InternLM/MindSearch", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:zhangzhengeric--sage", "kind": "repo", "label": "ZHangZHengEric/Sage (1208\u2605) \u2014 Multi-Agent System Framework For Complex Tasks", "url": "https://github.com/ZHangZHengEric/Sage", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:wjayesh--mahilo", "kind": "repo", "label": "wjayesh/mahilo (479\u2605) \u2014 mahilo: Multi-Agent Human-in-the-Loop Framework is a flexible framework for creating multi-agent systems that can each interact with humans while sharing relevant context internally.", "url": "https://github.com/wjayesh/mahilo", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:tsinghuac3i--marti", "kind": "repo", "label": "TsinghuaC3I/MARTI (535\u2605) \u2014 A Framework for LLM-based Multi-Agent Reinforced Training and Inference", "url": "https://github.com/TsinghuaC3I/MARTI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:huygiatrng--alpacatradingagent", "kind": "repo", "label": "huygiatrng/AlpacaTradingAgent (238\u2605) \u2014 AlpacaTradingAgent: Multi-Agents LLM Financial Trading Framework and perform trades on alpaca", "url": "https://github.com/huygiatrng/AlpacaTradingAgent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:bupt-gamma--masfactory", "kind": "repo", "label": "BUPT-GAMMA/MASFactory (486\u2605) \u2014 A Graph-Centric Framework for Orchestrating Multi-Agent Systems with Vibe Graphing.", "url": "https://github.com/BUPT-GAMMA/MASFactory", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:raga-ai-hub--ragaai-catalyst", "kind": "repo", "label": "raga-ai-hub/RagaAI-Catalyst (16145\u2605) \u2014 Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced anal", "url": "https://github.com/raga-ai-hub/RagaAI-Catalyst", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:framerslab--agentos", "kind": "repo", "label": "framerslab/agentos (589\u2605) \u2014 TypeScript AI agent framework: cognitive memory, runtime tool forging, multi-agent orchestration, 11 LLM providers.", "url": "https://github.com/framerslab/agentos", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:langroid--langroid-examples", "kind": "repo", "label": "langroid/langroid-examples (153\u2605) \u2014 Using Langroid's Multi-Agent Framework to Build LLM Apps", "url": "https://github.com/langroid/langroid-examples", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:a-agmon--rs-graph-llm", "kind": "repo", "label": "a-agmon/rs-graph-llm (349\u2605) \u2014 High-performance framework for building interactive workflow systems in Rust. Designed for complex workflows and multi-agent systems", "url": "https://github.com/a-agmon/rs-graph-llm", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:terry-cyx--metaopenfoam", "kind": "repo", "label": "Terry-cyx/MetaOpenFOAM (200\u2605) \u2014 MetaOpenFOAM: an LLM-based multi-agent framework for CFD", "url": "https://github.com/Terry-cyx/MetaOpenFOAM", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:zju-llms--agent-kernel", "kind": "repo", "label": "ZJU-LLMs/Agent-Kernel (428\u2605) \u2014 A MicroKernel Multi-Agents System Framework for Adaptive Social Simulation Powered by LLMs", "url": "https://github.com/ZJU-LLMs/Agent-Kernel", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:yongchao98--multi-agent-framework", "kind": "repo", "label": "yongchao98/multi-agent-framework (50\u2605) \u2014 LLM multi-agent discussion framework for multi-agent/robot situations.", "url": "https://github.com/yongchao98/multi-agent-framework", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:liquidos-ai--autoagents", "kind": "repo", "label": "liquidos-ai/AutoAgents (705\u2605) \u2014 A  multi-agent framework written in Rust that enables you to build, deploy, and coordinate multiple intelligent agents", "url": "https://github.com/liquidos-ai/AutoAgents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nlpodyssey--openai-agents-go", "kind": "repo", "label": "nlpodyssey/openai-agents-go (262\u2605) \u2014 A lightweight, powerful framework for multi-agent workflows in Go", "url": "https://github.com/nlpodyssey/openai-agents-go", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:cnsdqd-dyb--villageragent-minecraft-multiagent-framework", "kind": "repo", "label": "cnsdqd-dyb/VillagerAgent-Minecraft-multiagent-framework (93\u2605) \u2014 (VillagerAgent ACL 2024) A Graph based Minecraft multi agents framework", "url": "https://github.com/cnsdqd-dyb/VillagerAgent-Minecraft-multiagent-framework", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sii-research--siirl", "kind": "repo", "label": "sii-research/siiRL (364\u2605) \u2014 siiRL: Shanghai Innovation Institute RL Framework for Advanced LLMs and Multi-Agent Systems", "url": "https://github.com/sii-research/siiRL", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:wanxingai--lightagent", "kind": "repo", "label": "wanxingai/LightAgent (1175\u2605) \u2014 LightAgent: Lightweight Python framework for OpenAI-compatible agents with tools, memory, guardrails, tracing, lifecycle hooks, multi-agent collaboration, and workflows.", "url": "https://github.com/wanxingai/LightAgent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:geteff1--multi-agent-conversation-for-disease-diagnosis", "kind": "repo", "label": "geteff1/Multi-agent-conversation-for-disease-diagnosis (85\u2605) \u2014 This depository introduces a multi-agent conversation framework which facilitates in depth conversation among LLMs for complex disease diagnosis.", "url": "https://github.com/geteff1/Multi-agent-conversation-for-disease-diagnosis", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:pettingllms-ai--pettingllms", "kind": "repo", "label": "pettingllms-ai/PettingLLMs (198\u2605) \u2014 [ICLR'26] Stronger-MAS: A RL Framework for multi LLM agent system; [arxiv] MetaAgent-X:  End-to-End Reinforcement Learning Automatic Multi-Agent Systems", "url": "https://github.com/pettingllms-ai/PettingLLMs", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:deepauto-ai--automl-agent", "kind": "repo", "label": "DeepAuto-AI/automl-agent (145\u2605) \u2014 [ICML-25] AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML", "url": "https://github.com/DeepAuto-AI/automl-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:minimalfuture--agentmesh", "kind": "repo", "label": "MinimalFuture/AgentMesh (305\u2605) \u2014 A Multi-Agent framework that enables AI agents to collaborate effectively, helping you build powerful agent teams for solving complex tasks.", "url": "https://github.com/MinimalFuture/AgentMesh", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:samholt--l2mac", "kind": "repo", "label": "samholt/L2MAC (156\u2605) \u2014 \ud83d\ude80 The LLM Automatic Computer Framework: L2MAC", "url": "https://github.com/samholt/L2MAC", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:codefuse-ai--codefuse-muagent", "kind": "repo", "label": "codefuse-ai/CodeFuse-muAgent (774\u2605) \u2014 An Innovative Agent Framework Driven by KG Engine", "url": "https://github.com/codefuse-ai/CodeFuse-muAgent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:tradinggoose--tradinggoose.github.io", "kind": "repo", "label": "TradingGoose/TradingGoose.github.io (71\u2605) \u2014 A Multi-Agents LLM Financial Trading Framework for both individual stock analysis & portfolio management", "url": "https://github.com/TradingGoose/TradingGoose.github.io", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:0pusai--opus-agent-swarm-llm-framework", "kind": "repo", "label": "0pusAI/Opus-Agent-Swarm-LLM-Framework (4\u2605) \u2014 OPUS \u2014 bio-inspired multi-agent swarm architecture for collective LLM reasoning. Open-source. Ars Magna.", "url": "https://github.com/0pusAI/Opus-Agent-Swarm-LLM-Framework", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:llmp-io--legion", "kind": "repo", "label": "LLMP-io/Legion (117\u2605) \u2014 A Python-based framework for building multi-agent systems with LLMs. Currently in pre-launch alpha.", "url": "https://github.com/LLMP-io/Legion", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:freedomintelligence--twinmarket", "kind": "repo", "label": "FreedomIntelligence/TwinMarket (200\u2605) \u2014 [NeurIPS 2025 & ICLR 2025 Financial AI Best Paper Award] A multi-agent framework that leverages LLMs to simulate socio-economic systems", "url": "https://github.com/FreedomIntelligence/TwinMarket", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:servicenow--tapeagents", "kind": "repo", "label": "ServiceNow/TapeAgents (318\u2605) \u2014 TapeAgents is a framework that facilitates all stages of the LLM Agent development lifecycle", "url": "https://github.com/ServiceNow/TapeAgents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:adris-misra--multi-agentic-framework", "kind": "repo", "label": "adris-misra/multi-agentic-framework (11\u2605) \u2014 UNS-native, cybersecurity-aware multi-agent reference architecture for U.S. small-to-mid manufacturers. Industrial agentic intelligence aligned with ISA-95, NIST AI RMF, and CMMC L2.", "url": "https://github.com/adris-misra/multi-agentic-framework", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:openai--openai-cs-agents-demo", "kind": "repo", "label": "openai/openai-cs-agents-demo (6525\u2605) \u2014 Demo of a customer service use case implemented with the OpenAI Agents SDK", "url": "https://github.com/openai/openai-cs-agents-demo", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:strands-agents--harness-sdk", "kind": "repo", "label": "strands-agents/harness-sdk (6456\u2605) \u2014 Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.", "url": "https://github.com/strands-agents/harness-sdk", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:qx-labs--agents-deep-research", "kind": "repo", "label": "qx-labs/agents-deep-research (779\u2605) \u2014 An implementation of iterative deep research using the OpenAI Agents SDK", "url": "https://github.com/qx-labs/agents-deep-research", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:openai--openai-voice-agent-sdk-sample", "kind": "repo", "label": "openai/openai-voice-agent-sdk-sample (255\u2605) \u2014 Sample application to add voice capabilities to the Agents SDK", "url": "https://github.com/openai/openai-voice-agent-sdk-sample", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:shahidali54--openai-agents-sdk", "kind": "repo", "label": "shahidali54/OpenAI-Agents-SDK (60\u2605) \u2014 Learning OpenAI Agents SDK", "url": "https://github.com/shahidali54/OpenAI-Agents-SDK", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:agentops-ai--agentops", "kind": "repo", "label": "AgentOps-AI/agentops (5684\u2605) \u2014 Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and Ca", "url": "https://github.com/AgentOps-AI/agentops", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:strands-agents--samples", "kind": "repo", "label": "strands-agents/samples (805\u2605) \u2014 Agent samples built using the Strands Agents SDK.", "url": "https://github.com/strands-agents/samples", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:panaversity--learn-agentic-ai", "kind": "repo", "label": "panaversity/learn-agentic-ai (4270\u2605) \u2014 Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes", "url": "https://github.com/panaversity/learn-agentic-ai", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:chatwoot--ai-agents", "kind": "repo", "label": "chatwoot/ai-agents (149\u2605) \u2014 Ruby AI Agents SDK - Inspired by OpenAI Agents SDK", "url": "https://github.com/chatwoot/ai-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:dannymac180--meta-agent", "kind": "repo", "label": "DannyMac180/meta-agent (416\u2605) \u2014 An agent that uses OpenAI's Agents SDK to generate new agents", "url": "https://github.com/DannyMac180/meta-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:vercel--ai", "kind": "repo", "label": "vercel/ai (25393\u2605) \u2014 The AI Toolkit for TypeScript. From the creators of Next.js, the AI SDK is a free open-source library for building AI-powered applications and agents ", "url": "https://github.com/vercel/ai", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:packtpublishing--building-agents-with-openai-agents-sdk", "kind": "repo", "label": "PacktPublishing/Building-Agents-with-OpenAI-Agents-SDK (27\u2605) \u2014 Building Agents with OpenAI SDK, Published by Packt", "url": "https://github.com/PacktPublishing/Building-Agents-with-OpenAI-Agents-SDK", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:strands-agents--sdk-typescript", "kind": "repo", "label": "strands-agents/sdk-typescript (696\u2605) \u2014 A model-driven approach to building AI agents in just a few lines of code. ", "url": "https://github.com/strands-agents/sdk-typescript", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jgravelle--openai-agentssdk-gui", "kind": "repo", "label": "jgravelle/OpenAI-AgentsSDK-GUI (51\u2605)", "url": "https://github.com/jgravelle/OpenAI-AgentsSDK-GUI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:davidpc007--solana-agent-kit", "kind": "repo", "label": "davidpc007/solana-agent-kit (54\u2605) \u2014 solana ai agent toolkit for modular monorepo with plugin architecture, first-class support for langchain, vercel ai sdk, openai agents and claude", "url": "https://github.com/davidpc007/solana-agent-kit", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:enkrateialucca--oreilly-openai-agents-sdk", "kind": "repo", "label": "EnkrateiaLucca/oreilly-openai-agents-sdk (22\u2605) \u2014 Repo for oreilly course: OpenAI Agents SDK", "url": "https://github.com/EnkrateiaLucca/oreilly-openai-agents-sdk", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:deepstation--openai-academy-openai-agents-sdk", "kind": "repo", "label": "deepstation/openai-academy-openai-agents-sdk (46\u2605)", "url": "https://github.com/deepstation/openai-academy-openai-agents-sdk", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:subhankaladi--openai_agents_sdk", "kind": "repo", "label": "subhankaladi/OpenAI_Agents_SDK (24\u2605) \u2014 Learning OpenAI Agents SDK", "url": "https://github.com/subhankaladi/OpenAI_Agents_SDK", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:tanstack--ai", "kind": "repo", "label": "TanStack/ai (2870\u2605) \u2014 \ud83e\udd16 Type-safe, provider-agnostic TypeScript AI SDK for streaming chat, tool calling, agents, and multimodal apps across OpenAI, Anthropic, Gemini, React, Vue, Svelte, and Solid.", "url": "https://github.com/TanStack/ai", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:apssouza22--ai-agent-react-llm", "kind": "repo", "label": "apssouza22/ai-agent-react-llm (17\u2605) \u2014 A vanilla implementation of ReAct: Synergizing Reasoning and Acting in Language Models", "url": "https://github.com/apssouza22/ai-agent-react-llm", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jeomon--meta-agent-with-more-agents", "kind": "repo", "label": "Jeomon/Meta-Agent-with-More-Agents (47\u2605) \u2014 The purpose of the \"Meta Agent with More Agents\" project is to dynamically solve complex queries by breaking them down into smaller tasks and assigning each to specialized AI agents. The Meta Agent co", "url": "https://github.com/Jeomon/Meta-Agent-with-More-Agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:anionex--llm-react-agent", "kind": "repo", "label": "Anionex/LLM-ReACT-Agent (7\u2605) \u2014 \u624b\u6413\u4e00\u4e2a\u57fa\u4e8eReact\u63a8\u7406\u6846\u67b6\u7684agent\uff0c\u652f\u6301\u6dfb\u52a0\u5de5\u5177 | Build a LLM agent using ReAct reasoning framework from scratch, supporting adding custom tools", "url": "https://github.com/Anionex/LLM-ReACT-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:cerno-ai--cerno-agentic-local-deep-research", "kind": "repo", "label": "Cerno-AI/Cerno-Agentic-Local-Deep-Research (68\u2605) \u2014 Cerno is a local-first research platform that leverages agentic AI to break down complex queries into verifiable, multi-step workflows. Switch smoothly between cloud LLMs and self-hosted models, tra", "url": "https://github.com/Cerno-AI/Cerno-Agentic-Local-Deep-Research", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:thepradip--nexussql", "kind": "repo", "label": "thepradip/NexusSQL (8\u2605) \u2014 The SQL agent that thinks before it queries ReAct reasoning, semantic caching, multi-LLM, 100+ tables, zero config", "url": "https://github.com/thepradip/NexusSQL", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:om-ai-lab--open-agent-leaderboard", "kind": "repo", "label": "om-ai-lab/open-agent-leaderboard (36\u2605) \u2014 Reproducible Language Agent Research", "url": "https://github.com/om-ai-lab/open-agent-leaderboard", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:balaji-r-05--visa-hackathon", "kind": "repo", "label": "Balaji-R-05/visa-hackathon (11\u2605) \u2014 An Agentic AI framework that combines deterministic rules with LLM reasoning for automated data quality auditing and compliance mapping.", "url": "https://github.com/Balaji-R-05/visa-hackathon", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:wz289494--anyclaw", "kind": "repo", "label": "wz289494/anyclaw (13\u2605) \u2014 \u57fa\u4e8e LangChain \u7684 CLI Agent \u6846\u67b6\uff0c\u91c7\u7528 ReAct\uff08Reasoning + Acting\uff09\u6a21\u5f0f\u3002\u652f\u6301 OpenAI\u3001Gemini\u3001Qwen\u3001DeepSeek\u3001Kimi \u7b49\u591a\u79cd LLM \u63d0\u4f9b\u5546\uff0c\u63d0\u4f9b\u6d41\u5f0f\u54cd\u5e94\u3001\u4f1a\u8bdd\u6301\u4e45\u5316\u3001\u5de5\u5177\u6269\u5c55\u3001Token \u8ffd\u8e2a\u3001\u6d88\u606f\u538b\u7f29\u7b49\u7279\u6027\u3002\u901a\u8fc7vibe coding\u8fdb\u884c\u7b80\u5355\u7684\u914d\u7f6e\u548c\u5de5\u5177\u6dfb\u52a0\uff0c\u5373\u53ef\u5feb\u901f\u642d\u5efa\u901a\u7528\u6216\u5782\u7c7b Agent\uff0c\u65e0\u9700\u6df1\u5165\u6846\u67b6\u5e95\u5c42", "url": "https://github.com/wz289494/anyclaw", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:banghuazhao--swift-ai-agent-demo", "kind": "repo", "label": "banghuazhao/swift-ai-agent-demo (15\u2605) \u2014 \ud83e\udd16 Native iOS implementation of the ReAct (Reasoning + Acting) AI agent pattern with SwiftUI. Watch AI think, act, and solve problems step-by-step using OpenAI's GPT models.", "url": "https://github.com/banghuazhao/swift-ai-agent-demo", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:vanillasky00--reagent", "kind": "repo", "label": "vanillaSky00/reAgent (4\u2605) \u2014 Minimal, hackable AI agent built on the ReAct reasoning loop. No frameworks \u2014 just a transparent Thought \u2192 Action \u2192 Observation cycle you can read and extend in an afternoon.", "url": "https://github.com/vanillaSky00/reAgent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jasonclark--agentic-search-react", "kind": "repo", "label": "jasonclark/agentic-search-react (4\u2605) \u2014 Agent uses an LLM (via Ollama) and ReAct (Reasoning + Acting) cycle to apply tools for searching and context-building. Flask app includes an interface that shows thinking patterns and reasons for a fi", "url": "https://github.com/jasonclark/agentic-search-react", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nishchal-29--reasoning-llm-agent", "kind": "repo", "label": "Nishchal-29/reasoning-llm-agent (0\u2605) \u2014 A Tool-Augmented Reasoning Agent powered by Qwen2.5-3B-Instruct, featuring execution-aligned SFT and GRPO training, live tool integration, multi-step ReAct reasoning, verification and self-correction ", "url": "https://github.com/Nishchal-29/reasoning-llm-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:lamemind--react-agent-ts", "kind": "repo", "label": "lamemind/react-agent-ts (2\u2605) \u2014 A lightweight, streaming-first ReAct (Reasoning + Acting) agent that works with any LangChain-compatible model. Focus on agent logic while LangChain handles the provider complexity.", "url": "https://github.com/lamemind/react-agent-ts", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:johnmachado11--react-agent-from-scratch", "kind": "repo", "label": "JohnMachado11/ReAct-Agent-from-Scratch (2\u2605) \u2014 ReAct (Reasoning and Acting) agent built from scratch in Python. No libraries, no abstractions, simple and straight to the point.", "url": "https://github.com/JohnMachado11/ReAct-Agent-from-Scratch", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:zj-rrissh--react-agent", "kind": "repo", "label": "zj-rrissh/ReAct-Agent (2\u2605) \u2014 \u57fa\u4e8e ReAct (Reasoning + Acting) \u6a21\u5f0f\u7684\u667a\u80fd\u52a9\u7406\uff0c\u652f\u6301\u5de5\u5177\u8c03\u7528\u3001\u81ea\u6211\u53cd\u601d\u548c\u591a\u540e\u7aef LLM\u3002", "url": "https://github.com/zj-rrissh/ReAct-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:xinzhel--lits-llm", "kind": "repo", "label": "xinzhel/lits-llm (3\u2605) \u2014 A modular Python framework for building LLM agents with tree search (e.g., MCTS, BFS) and chain reasoning (e.g., ReAct) --- CiT [ACL2026 Findings], LiTS [ACL 2026 Demo], LiTS-Mem [Under Review]", "url": "https://github.com/xinzhel/lits-llm", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:adilshamim8--ask-the-web-103", "kind": "repo", "label": "AdilShamim8/Ask-the-Web-103 (8\u2605) \u2014 Production-grade Perplexity-like AI agent with real-time web search, ReACT/ReWOO/Reflexion/Tree-Search reasoning, MCP & A2A protocols, multi-agent orchestration, streaming SSE API, and full evaluation", "url": "https://github.com/AdilShamim8/Ask-the-Web-103", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:eriri9876--thought-collapse-llm-agents", "kind": "repo", "label": "Eriri9876/thought-collapse-llm-agents (0\u2605) \u2014 Cross-task diagnosis of Capacity Domination in ReAct agents \u2014 paper artefacts and reproduction code.", "url": "https://github.com/Eriri9876/thought-collapse-llm-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:josephg3001--reactagent", "kind": "repo", "label": "JosephG3001/ReActAgent (0\u2605) \u2014 Small demo of the LLM ReAct (Reasoning and Acting) agent pattern in ASP.Net", "url": "https://github.com/JosephG3001/ReActAgent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:rtj1--reflexive-llm-agent", "kind": "repo", "label": "rtj1/reflexive-llm-agent (1\u2605) \u2014 A self-reflective LLM agent with tools, memory, and reasoning built using LangChain + ReAct + Reflexion. Modular FastAPI backend + Streamlit UI.", "url": "https://github.com/rtj1/reflexive-llm-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:tushar2704--react-agents", "kind": "repo", "label": "tushar2704/ReAct-Agents (0\u2605) \u2014 This repository aims to guide you through the process of creating a ReAct (Reasoning and Acting) AI agent from the ground up.", "url": "https://github.com/tushar2704/ReAct-Agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:fireflyframework--fireflyframework-agentic", "kind": "repo", "label": "fireflyframework/fireflyframework-agentic (4\u2605) \u2014 In-process Python metaframework on Pydantic AI for production GenAI \u2014 composable, protocol-driven layers for agents & middleware, tools, reasoning (ReAct/CoT/ToT/Reflexion), memory, validation/QoS, DA", "url": "https://github.com/fireflyframework/fireflyframework-agentic", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nmhelmy--conversational-ai-reasoning-agents", "kind": "repo", "label": "NMHelmy/conversational-ai-reasoning-agents (0\u2605) \u2014 A Python-based AI agent using OpenAI API to answer weather queries and perform calculations via three reasoning approaches (Basic, Chain-of-Thought, ReAct). Integrates weather API and simulated tools ", "url": "https://github.com/NMHelmy/conversational-ai-reasoning-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:devxjitin--autourgos-react-agent", "kind": "repo", "label": "devxjitin/autourgos-react-agent (0\u2605) \u2014 Self-contained ReAct (Reasoning + Acting) agent for the Autourgos framework \u2014 works with any OpenAI-compatible LLM", "url": "https://github.com/devxjitin/autourgos-react-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:alexanzilex--llm-agents-playground", "kind": "repo", "label": "AlexAnzilex/llm-agents-playground (0\u2605) \u2014 This repository contains experiments and notes developed while learning LLM agent architectures such as ReAct, tool-augmented reasoning, and LangGraph-style workflows.", "url": "https://github.com/AlexAnzilex/llm-agents-playground", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:fvilmos--ai_react_agent", "kind": "repo", "label": "fvilmos/AI_ReAct_agent (1\u2605) \u2014 Implements a Reasoning and Acting AI agent with local LLM and tools usage in Python.", "url": "https://github.com/fvilmos/AI_ReAct_agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mayankmishra15--math_reasoning_agent", "kind": "repo", "label": "Mayankmishra15/Math_reasoning_agent (0\u2605) \u2014 Built a Math Reasoning Agent using the ReAct (Reason + Act) framework that solves math problems step-by-step by combining LLM-based reasoning with Python-based tool execution. The system supports inte", "url": "https://github.com/Mayankmishra15/Math_reasoning_agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:gambletan--agent-engine", "kind": "repo", "label": "gambletan/agent-engine (0\u2605) \u2014 Agent reasoning engine with ReAct loop \u2014 LLM-agnostic, pluggable planning and tool execution", "url": "https://github.com/gambletan/agent-engine", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:farhad-davaripour--react_agent_from_scratch", "kind": "repo", "label": "Farhad-Davaripour/ReAct_Agent_from_Scratch (0\u2605) \u2014 This repository provides an introductory implementation of the ReAct (Reasoning and Acting) Agentic workflow.", "url": "https://github.com/Farhad-Davaripour/ReAct_Agent_from_Scratch", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:alucek--smolagents-guide", "kind": "repo", "label": "ALucek/smolagents-guide (50\u2605) \u2014 A walk through HuggingFace smolagents", "url": "https://github.com/ALucek/smolagents-guide", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mstryoda--llm-agents-example", "kind": "repo", "label": "mstrYoda/llm-agents-example (41\u2605) \u2014 An example repository to use HuggingFace smolagents, Phidata and CrewAI frameworks with local LLMs", "url": "https://github.com/mstrYoda/llm-agents-example", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:snowflake-labs--sfguide-build-agentic-workflows-with-huggingface-smolagents-in-snowflake", "kind": "repo", "label": "Snowflake-Labs/sfguide-build-agentic-workflows-with-huggingface-smolagents-in-snowflake (7\u2605)", "url": "https://github.com/Snowflake-Labs/sfguide-build-agentic-workflows-with-huggingface-smolagents-in-snowflake", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:vladkha--drone-agent", "kind": "repo", "label": "VladKha/drone-agent (3\u2605) \u2014 Drone autonomy powered by Generative AI (HuggingFace smolagents + Google Gemini)", "url": "https://github.com/VladKha/drone-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:kazemihabib--huggingface-agents-course-marimo-edition", "kind": "repo", "label": "kazemihabib/Huggingface-Agents-Course-Marimo-Edition (6\u2605) \u2014 Marimo versions of HuggingFace's Agents course notebooks.", "url": "https://github.com/kazemihabib/Huggingface-Agents-Course-Marimo-Edition", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:thecolonycc--smolagents-colony", "kind": "repo", "label": "TheColonyCC/smolagents-colony (0\u2605) \u2014 smolagents tools for The Colony (thecolony.cc) \u2014 give any HuggingFace agent the ability to search, read, write, and interact on the AI agent internet", "url": "https://github.com/TheColonyCC/smolagents-colony", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:murataslan1--ai-agent-benchmark", "kind": "repo", "label": "murataslan1/ai-agent-benchmark (26\u2605) \u2014 AI coding agents comparison - 80+ agents, SWE-Bench leaderboard, pricing. Devin, Cursor, Claude Code, Copilot, and more. December 2025.", "url": "https://github.com/murataslan1/ai-agent-benchmark", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:raymyers--swe-bench-util", "kind": "repo", "label": "raymyers/swe-bench-util (8\u2605) \u2014 Scripts for working with SWE-Bench, the AI coding agent benchmark ", "url": "https://github.com/raymyers/swe-bench-util", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:vexp-ai--vexp-swe-bench", "kind": "repo", "label": "Vexp-ai/vexp-swe-bench (11\u2605) \u2014 Open benchmark for AI coding agents on SWE-bench Verified. Compare resolution rates, cost, and unique wins.", "url": "https://github.com/Vexp-ai/vexp-swe-bench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:humphreysun98--repoagentbench", "kind": "repo", "label": "HumphreySun98/repoagentbench (31\u2605) \u2014 SWE-bench for your codebase \u2014 mine your merged PRs into local, contamination-free coding-agent benchmarks. Adapters: claude-code, aider (Opus 4.7 / GPT-5.5 / Sonnet 4.6 / Gemini 3.1 Pro).", "url": "https://github.com/HumphreySun98/repoagentbench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:linny006--agent-eval-harness", "kind": "repo", "label": "linny006/agent-eval-harness (5\u2605) \u2014 Live, open-source benchmark for comparing AI coding agents on real GitHub issues", "url": "https://github.com/linny006/agent-eval-harness", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:benchflow-ai--agents", "kind": "repo", "label": "benchflow-ai/agents (9\u2605) \u2014 Minimal coding agents, easy to play with (opencode TUI) and easy to benchmark (ACP on BenchFlow) \u2014 built around mini-swe-agent", "url": "https://github.com/benchflow-ai/agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:robertkodes--repo-eval", "kind": "repo", "label": "RobertKodes/repo-eval (0\u2605) \u2014 SWE-bench compliant benchmarking for coding agents", "url": "https://github.com/RobertKodes/repo-eval", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jlab-nlp--dialogue_swe_bench", "kind": "repo", "label": "jlab-nlp/dialogue_swe_bench (1\u2605) \u2014 A benchmark dataset for dialogue-driven coding agents", "url": "https://github.com/jlab-nlp/dialogue_swe_bench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:rounakbende10--rh-swe-bench", "kind": "repo", "label": "rounakbende10/rh-swe-bench (1\u2605) \u2014 Red Hat Specific Benchmarks for Coding Agents - 357 verified tasks in Harbor format", "url": "https://github.com/rounakbende10/rh-swe-bench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nripankadas07--patchgym", "kind": "repo", "label": "nripankadas07/patchgym (0\u2605) \u2014 Turn any Git repository into a local SWE-bench-style coding-agent benchmark.", "url": "https://github.com/nripankadas07/patchgym", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ttxs69--coding-agent-eval", "kind": "repo", "label": "ttxs69/coding-agent-eval (1\u2605) \u2014 Public, reproducible benchmark of CLI coding agents (Claude Code, Codex, Aider) on SWE-bench Verified. Live leaderboard: https://ttxs69.github.io/coding-agent-eval/", "url": "https://github.com/ttxs69/coding-agent-eval", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:he-yufeng--issuebenchkit", "kind": "repo", "label": "he-yufeng/IssueBenchKit (3\u2605) \u2014 Turn a real GitHub issue into a repeatable coding-agent benchmark task", "url": "https://github.com/he-yufeng/IssueBenchKit", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:xavierxmorris--ai-coding-benchmarks-reference", "kind": "repo", "label": "xavierxmorris/ai-coding-benchmarks-reference (0\u2605) \u2014 Curated map of AI agent evaluation benchmarks (SWE-bench, Spider 2.0, BIRD, DS-1000, FinQA, ConvFinQA, TAT-QA, BFCL) with a guide on using them per task.", "url": "https://github.com/xavierxmorris/ai-coding-benchmarks-reference", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nvandessel--floop-bench", "kind": "repo", "label": "nvandessel/floop-bench (1\u2605) \u2014 Open benchmark evaluating floop's impact on coding agent performance using SWE-bench Verified", "url": "https://github.com/nvandessel/floop-bench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ryanstoffel--context-layer-bench", "kind": "repo", "label": "RyanStoffel/context-layer-bench (0\u2605) \u2014 Benchmark: GraphRAG MCP layer vs. baseline context-management for AI coding agents (Claude Code + SWE Bench Verified)", "url": "https://github.com/RyanStoffel/context-layer-bench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sergeyklay--agentprobe", "kind": "repo", "label": "sergeyklay/agentprobe (0\u2605) \u2014 Reproducible benchmark framework for testing hypotheses about AI coding agents", "url": "https://github.com/sergeyklay/agentprobe", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:daseinlabs--code-compression-bench", "kind": "repo", "label": "daseinlabs/code-compression-bench (0\u2605) \u2014 Dasein Code-Compression Bench \u2014 a comprehensive, reproducible benchmark of context-compression layers for coding agents on SWE-bench Verified.", "url": "https://github.com/daseinlabs/code-compression-bench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sabofxx--agent-smith-42", "kind": "repo", "label": "Sabofxx/agent-smith-42 (0\u2605) \u2014 LLM code-agent framework \u2014 Thought\u2192Code\u2192Observation loop, process-isolated sandbox, MBPP + SWE-bench tracks, MCP tools, multi-model OpenRouter benchmarks. 42 School project.", "url": "https://github.com/Sabofxx/agent-smith-42", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ttxs69--awesome-coding-agent-eval", "kind": "repo", "label": "ttxs69/awesome-coding-agent-eval (0\u2605) \u2014 A curated list of benchmarks, harnesses, leaderboards, and tools for evaluating AI coding agents.", "url": "https://github.com/ttxs69/awesome-coding-agent-eval", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:fl4p--kimi-tools", "kind": "repo", "label": "fl4p/kimi-tools (0\u2605) \u2014 Kimi K2 (Moonshot) system prompts for coding agents + an A/B benchmark harness (cline/opencode/pi) and SWE-bench Verified eval", "url": "https://github.com/fl4p/kimi-tools", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:architehc--30b-moe-benchmarks", "kind": "repo", "label": "architehc/30b-moe-benchmarks (0\u2605) \u2014 Comprehensive benchmarks for 30B MoE models on RTX 4090. Key finding: HumanEval \u2260 SWE-bench - the 98% HumanEval model scores 0% on agentic tasks. Includes Nemotron, GLM-4.7-Flash, Qwen3-Coder comparis", "url": "https://github.com/architehc/30b-moe-benchmarks", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:t-timms--godspeed-coding-agent", "kind": "repo", "label": "t-timms/godspeed-coding-agent (0\u2605) \u2014 Alpha \u2014 Security-first open-source coding agent. 4-tier permissions, hash-chained audit trails, 200+ LLM providers. Seeking testers.", "url": "https://github.com/t-timms/godspeed-coding-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:huzaifa-57--self-sycophancy-on-swe-bench", "kind": "repo", "label": "huzaifa-57/Self-Sycophancy-on-SWE-bench (0\u2605) \u2014 This repository implements the experiment described in \u201cExperiment: Self-Sycophancy in SWE-bench PR Evaluation.\u201d The goal is to measure whether LLM inflates the quality of its own pull requests relati", "url": "https://github.com/huzaifa-57/Self-Sycophancy-on-SWE-bench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:anandesh-sharma--awesome-agent-harnesses", "kind": "repo", "label": "Anandesh-Sharma/awesome-agent-harnesses (0\u2605) \u2014 \ud83e\udd16 The definitive curated map of agent harnesses \u2014 concepts, design patterns, architectures, frameworks, coding agents, papers & benchmarks.", "url": "https://github.com/Anandesh-Sharma/awesome-agent-harnesses", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:euraika-labs--swe-postcutoff-bench", "kind": "repo", "label": "Euraika-Labs/swe-postcutoff-bench (0\u2605) \u2014 Contamination-controlled multi-language agentic-coding benchmark \u2014 bug-fix tasks from real GitHub issues filed after Oct 2024 across Python, TS, Java, Go, Rust, Ruby, C/C++. Compatible with SWE-bench ", "url": "https://github.com/Euraika-Labs/swe-postcutoff-bench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:brandeispatrick--openbench", "kind": "repo", "label": "BrandeisPatrick/openbench (4\u2605) \u2014 Reverse-engineer the RL reward an LLM was trained on \u2014 from black-box agentic coding behavior alone. Tested on Opus 4.8, Fable 5, GPT-5.5.", "url": "https://github.com/BrandeisPatrick/openbench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:tajaddin--swe-mini-bench", "kind": "repo", "label": "Tajaddin/swe-mini-bench (0\u2605) \u2014 Lightweight code-patch eval: 10 curated Python bugs \u00d7 3 agent strategies (zero-shot/scratchpad/scratchpad+critique). Real Haiku 4.5 numbers with named failure modes.", "url": "https://github.com/Tajaddin/swe-mini-bench", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:uran-company--awesome-ai-models-for-software-developers", "kind": "repo", "label": "Uran-Company/awesome-ai-models-for-software-developers (0\u2605) \u2014 Explore Awesome AI models revolutionizing dev in 2025: Claude Sonnet 4.5, Gemini 2.5 Pro, GPT-5 Codex, Grok Code Fast 1, Composer (Cursor 2.0), DeepSeek V3.2, Claude Haiku 4.5. Dive into benchmarks li", "url": "https://github.com/Uran-Company/awesome-ai-models-for-software-developers", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:zuwasi--quickswe", "kind": "repo", "label": "zuwasi/QuickSWE (0\u2605) \u2014 QuickSWE: A fast, rigorous benchmark for AI coding agents. Not a stripped-down SWE-Bench \u2014 a practical alternative that runs on your laptop in hours with statistical multi-run analysis, regression det", "url": "https://github.com/zuwasi/QuickSWE", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:flo7up--swe-rl-forge-lite", "kind": "repo", "label": "flo7up/swe-rl-forge-lite (0\u2605) \u2014 A lightweight, open-source framework that turns historical GitHub pull requests into reproducible, verifiable software-engineering tasks for training and evaluating coding agents.", "url": "https://github.com/flo7up/swe-rl-forge-lite", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ryota-kawamura--functions-tools-and-agents-with-langchain", "kind": "repo", "label": "Ryota-Kawamura/Functions-Tools-and-Agents-with-LangChain (16\u2605) \u2014 You\u2019ll explore new advancements like ChatGPT\u2019s function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extr", "url": "https://github.com/Ryota-Kawamura/Functions-Tools-and-Agents-with-LangChain", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:oct4pie--toolbridge", "kind": "repo", "label": "Oct4Pie/toolbridge (77\u2605) \u2014 Enable tool/function calling for any LLM, in OpenAI and Ollama API formats, adding universal function calling to models without native support. Use local or cloud models with full agent capabilities.", "url": "https://github.com/Oct4Pie/toolbridge", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:arslankas--functions-tools-and-agents-with-langchain", "kind": "repo", "label": "ArslanKAS/Functions-Tools-and-Agents-with-LangChain (15\u2605) \u2014 Explore new advancements like ChatGPT\u2019s function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extraction,", "url": "https://github.com/ArslanKAS/Functions-Tools-and-Agents-with-LangChain", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sjakati98--awesome-tools-for-agents", "kind": "repo", "label": "sjakati98/awesome-tools-for-agents (9\u2605) \u2014 Awesome List of tools that can be used by conversational agents and LLMs. Geared towards APIs and tools that can be used in function calling.", "url": "https://github.com/sjakati98/awesome-tools-for-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:haxxorcialtion--simpletool", "kind": "repo", "label": "HaxxorCialtion/SimpleTool (55\u2605) \u2014 A method to use LLM function calling with real-time level speed, empowering latency-sensitive applications like robotics, game AI, and autonomous agents.", "url": "https://github.com/HaxxorCialtion/SimpleTool", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:violet-sword--ai-agent-toolcall-function", "kind": "repo", "label": "Violet-sword/AI-Agent-ToolCall-Function (3\u2605) \u2014 A demonstration of dynamic tool calling with AI Agent using Ollama. Showcases how LLMs can invoke external Python functions in real time to augment their reasoning with live, actionable data.", "url": "https://github.com/Violet-sword/AI-Agent-ToolCall-Function", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:pd2871--end-to-end-llm-projects", "kind": "repo", "label": "pd2871/End-to-End-LLM-Projects (11\u2605) \u2014 This repo contains code related to development of LLM based projects with Langchain and LLamaIndex. It uses RAG, Function calling, agents and tools as of now for interaction with data.", "url": "https://github.com/pd2871/End-to-End-LLM-Projects", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:fullstacksam23--gofer", "kind": "repo", "label": "fullstacksam23/gofer (11\u2605) \u2014 A Go-based CLI LLM agent that can read, write, and modify files and execute shell commands using tool-based function calling.", "url": "https://github.com/fullstacksam23/gofer", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nghiavt2906--multi-agent-code-assistant-with-rag-and-tool-use", "kind": "repo", "label": "nghiavt2906/Multi-Agent-Code-Assistant-with-RAG-and-Tool-Use (4\u2605) \u2014 \ud83e\udd16 Production-ready multi-agent AI system orchestrating specialized agents (Planner, Coder, Reviewer, Debugger, Optimizer) with RAG, function calling, and multi-LLM support. Built with FastAPI, React, ", "url": "https://github.com/nghiavt2906/Multi-Agent-Code-Assistant-with-RAG-and-Tool-Use", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:faruk-ops--ai-agent-function-calling", "kind": "repo", "label": "Faruk-ops/ai-agent-function-calling (0\u2605) \u2014 Simulations and JSON schemas for LLM tool use and agentic workflows.", "url": "https://github.com/Faruk-ops/ai-agent-function-calling", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:kristofferv98--agent_nexus", "kind": "repo", "label": "kristofferv98/Agent_Nexus (5\u2605) \u2014 Agentic framework for dynamic function calling across latest LLMs (gpt-4o, gemini-2.0-flash, groq modes, and anthropic models). Converts Python functions into provider-specific schemas for autonomous ", "url": "https://github.com/kristofferv98/Agent_Nexus", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:paul-kingston--llm-tool-calling-agent", "kind": "repo", "label": "paul-kingston/llm-tool-calling-agent (0\u2605) \u2014 A tool-augmented AI agent built with LangChain and Groq, implementing the ReAct framework for dynamic reasoning and function calling. Supports streaming responses and modular tool integration using uv", "url": "https://github.com/paul-kingston/llm-tool-calling-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jra-codinglab--tool-use-agent", "kind": "repo", "label": "JRA-CodingLab/tool-use-agent (0\u2605) \u2014 A clean tool-use / function-calling agent (Anthropic tool use) that plans, calls tools, and completes multi-step tasks.", "url": "https://github.com/JRA-CodingLab/tool-use-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:wmmthu--awesome-llm-agent-skills-papers", "kind": "repo", "label": "wmmthu/awesome-llm-agent-skills-papers (3\u2605) \u2014 A curated list of papers, blog posts, and systems on skills for LLM agents \u2014 reusable, named capability units that an agent can store, retrieve, compose, and improve over time \u2014 together with closely ", "url": "https://github.com/wmmthu/awesome-llm-agent-skills-papers", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:cerenaaa--ai-agents", "kind": "repo", "label": "cerenaaa/ai-agents (0\u2605) \u2014 Tool-using LLM agents with function calling, planning, and memory", "url": "https://github.com/cerenaaa/ai-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:emrekaanb--ai-agent-tool-use", "kind": "repo", "label": "emrekaanb/ai-agent-tool-use (0\u2605) \u2014  Agentic backend service in C#/.NET that orchestrates LLM function calling for multi-step tasks: SQL queries, REST API calls, and structured reports.", "url": "https://github.com/emrekaanb/ai-agent-tool-use", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:yousefbadr0--agent-with-function-calling", "kind": "repo", "label": "Yousefbadr0/Agent-with-Function-Calling (0\u2605) \u2014 A simple AI Agent built with Qwen2.5-7B-Instruct that uses an LLM router and tool calling to perform tasks like weather lookup, search, news summarization, currency conversion, and calculations.", "url": "https://github.com/Yousefbadr0/Agent-with-Function-Calling", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:prathameshlohar--functions-tools-and-agents-with-langchain", "kind": "repo", "label": "PrathameshLohar/Functions-Tools-and-Agents-with-LangChain (0\u2605) \u2014 Repository for building structured, tool-aware LLM agents using function calling and LangChain Expression Language (LCEL).", "url": "https://github.com/PrathameshLohar/Functions-Tools-and-Agents-with-LangChain", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sanskar1724--ai_agents", "kind": "repo", "label": "Sanskar1724/AI_Agents (2\u2605) \u2014 \ud83d\ude80 Learn how to build AI Agents from scratch using Python. Covers LLM APIs, Tool Calling, ReAct, Agent Tracing, Code Agents, Native Function Calling, and real-world implementations without relying on f", "url": "https://github.com/Sanskar1724/AI_Agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:chenkuanchung--llm-function-calling-lab", "kind": "repo", "label": "chenkuanchung/llm-function-calling-lab (0\u2605) \u2014 Production-grade AI Agent pipeline for an Order CS Assistant. Optimized with Qwen2.5-3B and LoRA fine-tuning for precise tool use. Features a FastAPI/Docker backend with hand-rolled ReAct logic, auto-", "url": "https://github.com/chenkuanchung/llm-function-calling-lab", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:puru763--rag-powered-ai-travel-assistant-with-real-time-tool-calling-workflow-automation", "kind": "repo", "label": "puru763/RAG-Powered-AI-Travel-Assistant-with-Real-Time-Tool-Calling-Workflow-Automation (2\u2605) \u2014 Built a modular Spring Boot AI integration layer using Spring AI to connect enterprise microservices with multiple LLMs (OpenAI). Implemented a RAG pipeline with Qdrant for context-aware responses and", "url": "https://github.com/puru763/RAG-Powered-AI-Travel-Assistant-with-Real-Time-Tool-Calling-Workflow-Automation", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:johnnysgithubaccount--smart-home-virtual-assistant", "kind": "repo", "label": "JohnnysGithubAccount/Smart-Home-Virtual-Assistant (0\u2605) \u2014 A virtual assistant using function calling tool of LLM Agent System", "url": "https://github.com/JohnnysGithubAccount/Smart-Home-Virtual-Assistant", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:iammoafiaanawaz---agentic-ai-study-helper", "kind": "repo", "label": "iamMoafiaaNawaz/-Agentic-AI-Study-Helper (0\u2605) \u2014 \"Advanced AI agent using structured tool calling and  LLM function capabilities for educational assistance.  Built with LiteLLM and native function calling.\"", "url": "https://github.com/iamMoafiaaNawaz/-Agentic-AI-Study-Helper", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:dlcastan--agentes", "kind": "repo", "label": "dlcastan/agentes (0\u2605) \u2014 Agente conversacional en Python que usa Groq como LLM con soporte de tool use (function calling). ", "url": "https://github.com/dlcastan/agentes", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:shashankg-dev404--react-native-gemma-agent", "kind": "repo", "label": "shashankg-dev404/react-native-gemma-agent (5\u2605) \u2014 React Native SDK for on-device AI agents powered by Google Gemma 4. Run LLM inference locally with function calling, tool use, and a pluggable JS skill system \u2014 no server, no API key, 100% private. Bu", "url": "https://github.com/shashankg-dev404/react-native-gemma-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:danidevadoss--agentic-ai-poc-local-llm", "kind": "repo", "label": "danidevadoss/agentic-ai-poc-local-llm (0\u2605) \u2014 This project demonstrates an agentic AI system using LangGraph with a local LLM (Ollama) that can perform multiplication operations using function calling/tool usage.", "url": "https://github.com/danidevadoss/agentic-ai-poc-local-llm", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:balamurali0532--llm-agent", "kind": "repo", "label": "balamurali0532/LLM-Agent (0\u2605) \u2014 A tool-using LLM agent that calls a calculator, clock, and live weather API via native function calling. Demonstrates the agent decide-act-observe loop. Python, provider-agnostic.", "url": "https://github.com/balamurali0532/LLM-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:abhinav744--functions-tools-and-agents-with-langchain", "kind": "repo", "label": "abhinav744/functions-tools-and-agents-with-langchain (0\u2605) \u2014 This project demonstrates how to use LangChain's agents framework in combination with tools and function-calling capabilities of LLMs (like OpenAI GPT) to perform dynamic, multi-step tasks with extern", "url": "https://github.com/abhinav744/functions-tools-and-agents-with-langchain", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:jbamigbade--llm-customer-support-agent", "kind": "repo", "label": "jbamigbade/llm-customer-support-agent (0\u2605) \u2014 An AI-powered customer support workflow built using OpenAI, Pydantic, structured JSON outputs, validation retry loops, and tool calling.  The system validates customer queries, converts natural langua", "url": "https://github.com/jbamigbade/llm-customer-support-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:karrrmma--codeguide-agent", "kind": "repo", "label": "Karrrmma/CodeGuide-Agent (0\u2605) \u2014 A tool-calling AI agent that answers questions about any codebase using OpenAI function calling, with project-boundary validation and ignore-list filtering.", "url": "https://github.com/Karrrmma/CodeGuide-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:hrishi0102--ai_agent_dbintegration", "kind": "repo", "label": "hrishi0102/AI_Agent_DBintegration (0\u2605) \u2014 Low level code of function/tool calling with llm and performing crud database operations using natural language prompts", "url": "https://github.com/hrishi0102/AI_Agent_DBintegration", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sina158--llm-agent", "kind": "repo", "label": "sina158/llm-agent (0\u2605) \u2014 A minimal but real tool-using AI agent: an agentic loop with function calling (calculator, datetime, text-stats, sandboxed file read). Runs offline via a deterministic MockLLM; plugs into OpenAI/Anthr", "url": "https://github.com/sina158/llm-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:rjmcginley--ai-agents", "kind": "repo", "label": "RJMcGinley/ai-agents (0\u2605) \u2014 A basic implementation of an AI agent loop using LLM function calling for structured tool execution and state management.", "url": "https://github.com/RJMcGinley/ai-agents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:nftushar--from-llm-to-agent", "kind": "repo", "label": "nftushar/from-llm-to-agent (0\u2605) \u2014 A lightweight agentic AI system that uses LLM function calling to interact with the local filesystem, execute Python code, and iteratively solve coding tasks through tool-based reasoning loops.", "url": "https://github.com/nftushar/from-llm-to-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:rdowning07--agent-sandbox", "kind": "repo", "label": "rdowning07/agent-sandbox (0\u2605) \u2014 Toy tool-using LLM agent built as part of Boot.dev; experiments with function calling, iteration, and autonomous bug fixing.", "url": "https://github.com/rdowning07/agent-sandbox", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:sumitroy154--the-knowledge-navigator-agent", "kind": "repo", "label": "SumitRoy154/The-Knowledge-Navigator-Agent (0\u2605) \u2014 An LLM concierge using Function Calling & RAG. Retrieves/compares real-time course data, maintaining State Management with custom tools.", "url": "https://github.com/SumitRoy154/The-Knowledge-Navigator-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:samuelmartinezduran--agenteval", "kind": "repo", "label": "Samuelmartinezduran/agenteval (0\u2605) \u2014 Framework open source para evaluar agentes LLM con function calling / tool use. Scoring por dimensi\u00f3n (tool accuracy, response quality, safety) + CLI, API y dashboard.", "url": "https://github.com/Samuelmartinezduran/agenteval", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:deejayy14--career-conversation-agent", "kind": "repo", "label": "deejayy14/Career-Conversation-Agent (0\u2605) \u2014 An agentic workflow using LLMs with function-calling, structured tool execution and contextual grounding to deliver human-like career interactions.", "url": "https://github.com/deejayy14/Career-Conversation-Agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:ngozikam--ai-agent-plant-advisor", "kind": "repo", "label": "Ngozikam/ai-agent-plant-advisor (0\u2605) \u2014 AI Agent demonstrating LLM tool calling, agent loops, structured function execution, and retrieval of plant care data using the Groq API.", "url": "https://github.com/Ngozikam/ai-agent-plant-advisor", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:poojitha29cj--llm", "kind": "repo", "label": "POOJITHA29CJ/LLM (0\u2605) \u2014 This project is a Math Orchestrator Agent powered by Google Gemini, SymPy, and NumPy. It solves quadratic equations, multiplies matrices, and computes eigenvalues/eigenvectors. Using agent-based routi", "url": "https://github.com/POOJITHA29CJ/LLM", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:flashinfer-ai--flashinfer", "kind": "repo", "label": "flashinfer-ai/flashinfer (5917\u2605) \u2014 FlashInfer: Kernel Library for LLM Serving", "url": "https://github.com/flashinfer-ai/flashinfer", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:hkustdial--flash-sparse-attention", "kind": "repo", "label": "HKUSTDial/flash-sparse-attention (723\u2605) \u2014 Trainable fast and memory-efficient sparse attention", "url": "https://github.com/HKUSTDial/flash-sparse-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:moonshotai--flashkda", "kind": "repo", "label": "MoonshotAI/FlashKDA (450\u2605) \u2014 FlashKDA: high-performance Kimi Delta Attention kernels", "url": "https://github.com/MoonshotAI/FlashKDA", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:amorehead--jvp_flash_attention", "kind": "repo", "label": "amorehead/jvp_flash_attention (180\u2605) \u2014 Flash Attention Triton kernel with support for second-order derivatives", "url": "https://github.com/amorehead/jvp_flash_attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:tlc-pack--libflash_attn", "kind": "repo", "label": "tlc-pack/libflash_attn (113\u2605) \u2014 Standalone Flash Attention v2 kernel without libtorch dependency ", "url": "https://github.com/tlc-pack/libflash_attn", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:kyegomez--flashattention20", "kind": "repo", "label": "kyegomez/FlashAttention20 (115\u2605) \u2014 Get down and dirty with FlashAttention2.0 in pytorch, plug in and play no complex CUDA kernels ", "url": "https://github.com/kyegomez/FlashAttention20", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:catswe--flash-attention-residuals", "kind": "repo", "label": "catswe/flash-attention-residuals (84\u2605) \u2014 Triton kernels and PyTorch ops for Block Attention Residuals (AttnRes)", "url": "https://github.com/catswe/flash-attention-residuals", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:nx-ai--mlstm_kernels", "kind": "repo", "label": "NX-AI/mlstm_kernels (89\u2605) \u2014 Tiled Flash Linear Attention library for fast and efficient mLSTM Kernels.", "url": "https://github.com/NX-AI/mlstm_kernels", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:dwvs2004--a.u.r.a.---flashattention-asic-accelerator", "kind": "repo", "label": "dwvs2004/A.U.R.A.---FlashAttention-ASIC-Accelerator (8\u2605) \u2014 SystemVerilog based ASIC accelerator for the FlashAttention kernel used in modern transformers", "url": "https://github.com/dwvs2004/A.U.R.A.---FlashAttention-ASIC-Accelerator", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:zjy0516--fa-fwd", "kind": "repo", "label": "ZJY0516/fa-fwd (2\u2605) \u2014 Flash-Attention-3 forward kernel", "url": "https://github.com/ZJY0516/fa-fwd", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:lavawolfiee--mini-flash-attention", "kind": "repo", "label": "lavawolfiee/mini-flash-attention (24\u2605) \u2014 Minimal FlashAttention in CUDA C++/CuTe: readable WMMA/CuTe kernels, no NxN workspace, up to 4.5x faster than naive PyTorch", "url": "https://github.com/lavawolfiee/mini-flash-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:mog9--flashattention-cupy", "kind": "repo", "label": "Mog9/FlashAttention-CuPy (18\u2605) \u2014 Flash Attention from scratch, tiled CUDA forward kernel, online softmax with running max and correction factor, recomputation trick in backward, O(N) memory, full forward and backward verified against", "url": "https://github.com/Mog9/FlashAttention-CuPy", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:lyj20071013--triton-flashattention", "kind": "repo", "label": "lyj20071013/Triton-FlashAttention (11\u2605) \u2014 This repository contains multiple implementations of Flash Attention optimized with Triton kernels, showcasing progressive performance improvements through hardware-aware optimizations. The implementa", "url": "https://github.com/lyj20071013/Triton-FlashAttention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:fms-zth--blackflash", "kind": "repo", "label": "fms-zth/BlackFlash (23\u2605) \u2014 Handwritten Flash Attention 2 CUDA kernel for Blackwell (SM120) with TMA, swizzle, double buffering & warp specialization", "url": "https://github.com/fms-zth/BlackFlash", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:tugbars--flash-attention-ptx-cuda", "kind": "repo", "label": "Tugbars/Flash-Attention-PTX-CUDA (7\u2605) \u2014 Hand-written PTX flash attention kernel hitting 202 TFLOPS FP16 (86% of theoretical peak) on RTX 5080: beats or matches vLLM's FlashAttention-2 on most shapes without WGMMA, TMA, or datacenter hardwar", "url": "https://github.com/Tugbars/Flash-Attention-PTX-CUDA", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:aicl-lab--diy-flash-attention", "kind": "repo", "label": "AICL-Lab/diy-flash-attention (4\u2605) \u2014 Learn Triton by building FlashAttention from scratch \u2014 V2 kernels, persistent threads, mask DSL, profiling toolkit, bilingual docs", "url": "https://github.com/AICL-Lab/diy-flash-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:alexdremov--chill-attention", "kind": "repo", "label": "alexdremov/chill-attention (3\u2605) \u2014 Fast, flexible, and chill sparse flash attention kernel", "url": "https://github.com/alexdremov/chill-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:alex4210987--qwen-tilelang-infer", "kind": "repo", "label": "Alex4210987/qwen-tilelang-infer (4\u2605) \u2014 High-performance TileLang fused kernels for Qwen3 inference (RMSNorm, RoPE, GQA Flash Attention, SwiGLU, W4A16 GEMV) with auto-tuning on A100", "url": "https://github.com/Alex4210987/qwen-tilelang-infer", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:priyammaz--tritonkernels", "kind": "repo", "label": "priyammaz/TritonKernels (3\u2605) \u2014 A quick and annotated Demo going from Numpy to Flash Attention", "url": "https://github.com/priyammaz/TritonKernels", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:tonbistudio--gqa-flash-attn-rtx3060", "kind": "repo", "label": "tonbistudio/gqa-flash-attn-rtx3060 (11\u2605) \u2014 Triton GQA flash attention kernel for NVIDIA RTX 3060 (sm_86). Matches or beats flash-attn2 on 9/10 workloads; up to 2.95x faster on long-context decode.", "url": "https://github.com/tonbistudio/gqa-flash-attn-rtx3060", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:mvideet--adaptive-splash-attention", "kind": "repo", "label": "mvideet/Adaptive-Splash-Attention (2\u2605) \u2014 Developing CUDA Kernel for Adaptive Sparse Flash Attention (Goncalves et. al)", "url": "https://github.com/mvideet/Adaptive-Splash-Attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:ankitbelbase17--flash-attention-forward-backward-pass-in-trition-kernel-", "kind": "repo", "label": "ankitbelbase17/Flash-Attention-forward-Backward-pass-in-Trition-Kernel- (2\u2605) \u2014 This project implements an efficient version of the Flash Attention mechanism , including both the forward and backward passes , using Triton , a programming language for writing highly optimized GPU ", "url": "https://github.com/ankitbelbase17/Flash-Attention-forward-Backward-pass-in-Trition-Kernel-", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:sumantrad--flash", "kind": "repo", "label": "sumantrad/flash (0\u2605) \u2014 flash type attention kernel tuning", "url": "https://github.com/sumantrad/flash", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:danieleschmidt--dp-flash-attention", "kind": "repo", "label": "danieleschmidt/dp-flash-attention (2\u2605) \u2014 Re-implements Flash-Attention 3 kernels with integrated R\u00e9nyi differential-privacy noise injection\u2014zero overhead versus post-hoc clipping. First hardware-optimized DP implementation for attention mech", "url": "https://github.com/danieleschmidt/dp-flash-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:mpsops--mps-linear-attention", "kind": "repo", "label": "mpsops/mps-linear-attention (2\u2605) \u2014 Metal kernels for Flash Linear Attention (DeltaNet/Qwen3.5) on Apple Silicon MPS", "url": "https://github.com/mpsops/mps-linear-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:reyansh00--flashattention-kernels", "kind": "repo", "label": "Reyansh00/FlashAttention-Kernels (0\u2605)", "url": "https://github.com/Reyansh00/FlashAttention-Kernels", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:v1kstrand--triton_fused_rope_flash_attn", "kind": "repo", "label": "v1kstrand/triton_fused_rope_flash_attn (3\u2605) \u2014 Triton FlashAttention kernel with fused 2D RoPE for fast ViT attention on modern NVIDIA GPUs.", "url": "https://github.com/v1kstrand/triton_fused_rope_flash_attn", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:bruce-lee-ly--decoding_attention", "kind": "repo", "label": "Bruce-Lee-LY/decoding_attention (47\u2605) \u2014 Decoding Attention is specially optimized for MHA, MQA, GQA and MLA using CUDA core for the decoding stage of LLM inference.", "url": "https://github.com/Bruce-Lee-LY/decoding_attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:mininglamp-ai--cider", "kind": "repo", "label": "Mininglamp-AI/cider (333\u2605) \u2014 W8A8/W4A8 inference + optimized SDPA on Apple Silicon \u2014 unlocking unused INT8 TensorOps in M5 for 1.2\u20131.9\u00d7 faster LLM prefill, plus FlashInfer-inspired GQA decode attention for up to 1.6\u00d7 SDPA speedup", "url": "https://github.com/Mininglamp-AI/cider", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:syhya--mlsys26-flashinfer-solution-sparse-attention", "kind": "repo", "label": "syhya/mlsys26-flashinfer-solution-sparse-attention (2\u2605) \u2014 Track B - Sparse attention mechanisms for long-context inference", "url": "https://github.com/syhya/mlsys26-flashinfer-solution-sparse-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:gloria72--flashinfer-kernel-bench", "kind": "repo", "label": "Gloria72/flashinfer-kernel-bench (0\u2605) \u2014 Correctness-first microbenchmarks for LLM attention and sampling kernels.", "url": "https://github.com/Gloria72/flashinfer-kernel-bench", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:colin6618--flashinfer-performance-benchmarks", "kind": "repo", "label": "Colin6618/flashinfer-performance-benchmarks (0\u2605) \u2014 A comprehensive benchmark for Flashinfer( a high-performance GPU kernel library for LLM inference). This project analyzes key performance characteristics of FlashInfer's single-decode attention kernel", "url": "https://github.com/Colin6618/flashinfer-performance-benchmarks", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:ammar-alnagar--yaie", "kind": "repo", "label": "Ammar-Alnagar/YAIE (1\u2605) \u2014 YAIE (Yet Another Inference Engine) is an educational project designed to help students and developers understand how modern LLM inference engines work. This implementation is inspired by state-of-the", "url": "https://github.com/Ammar-Alnagar/YAIE", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:kamalrss88--flashmla", "kind": "repo", "label": "kamalrss88/FlashMLA (1\u2605) \u2014 \ud83d\ude80 Accelerate attention mechanisms with FlashMLA, featuring optimized kernels for DeepSeek models, enhancing performance through sparse and dense attention.", "url": "https://github.com/kamalrss88/FlashMLA", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:aymanelrody--flashmla", "kind": "repo", "label": "aymanelrody/FlashMLA (1\u2605) \u2014 \u26a1 Optimize attention mechanisms with FlashMLA, a library of advanced sparse and dense kernels for DeepSeek models, improving performance and efficiency.", "url": "https://github.com/aymanelrody/FlashMLA", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:kyegomez--jamba", "kind": "repo", "label": "kyegomez/Jamba (219\u2605) \u2014 PyTorch Implementation of Jamba: \"Jamba: A Hybrid Transformer-Mamba Language Model\"", "url": "https://github.com/kyegomez/Jamba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:nick7nlp--jamba_paper_reading", "kind": "repo", "label": "nick7nlp/Jamba_Paper_Reading (15\u2605) \u2014 Paper reading: Jamba \u2014 Hybrid Transformer-Mamba LM (SSM \u2192 S4 \u2192 S6 \u2192 Jamba)", "url": "https://github.com/nick7nlp/Jamba_Paper_Reading", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:suzuki-2001--genomic-jamba", "kind": "repo", "label": "suzuki-2001/genomic-jamba (4\u2605) \u2014 An implementation of a hybrid architecture combining Mamba2 and FlashAttention2.", "url": "https://github.com/suzuki-2001/genomic-jamba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:farzanehjafari1987--jambatalk", "kind": "repo", "label": "FarzanehJafari1987/JambaTalk (5\u2605) \u2014 [ACM TOMM] The official repository for the JambaTalk: Speech-Driven 3D Talking Head Generation Based on Hybrid Transformer-Mamba Model.", "url": "https://github.com/FarzanehJafari1987/JambaTalk", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:amlplugins--ai21-chat", "kind": "repo", "label": "amlplugins/ai21-chat (0\u2605) \u2014 Native ai21 SDK re-exported under @amlplugins \u2014 AI21 Chat Completions \u2014 Jamba 1.7 Large/Mini Mamba-Transformer hybrid models with streaming and tool calls.", "url": "https://github.com/amlplugins/ai21-chat", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:sapmitra--ssm-scope", "kind": "repo", "label": "sapmitra/SSM-Scope (9\u2605) \u2014 State Space Model and SSM-Transformer Hybrid model characterization on consumer GPU and edge devices for very large context", "url": "https://github.com/sapmitra/SSM-Scope", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:gpantaz--retrievit", "kind": "repo", "label": "gpantaz/retrievit (0\u2605) \u2014 Retrievit: In-context Retrieval Capabilities of Transformers, State Space Models, and Hybrid Architectures", "url": "https://github.com/gpantaz/retrievit", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:shivpratap10--hybridsegnet", "kind": "repo", "label": "shivpratap10/HybridSegNet (0\u2605) \u2014 HybridSegNet: A hybrid breast ultrasound image segmentation framework that integrates a Hierarchical Vision Transformer, Vision State-Space Model, and gated attention for accurate and robust lesion de", "url": "https://github.com/shivpratap10/HybridSegNet", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:wallscreet--tinymamba", "kind": "repo", "label": "wallscreet/tinymamba (0\u2605) \u2014 a minimal, educational implementation of a hybrid language model architecture combining state-space modeling (SSM) and transformer attention.", "url": "https://github.com/wallscreet/tinymamba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:scraper-sky--cs224n_final_project", "kind": "repo", "label": "scraper-sky/cs224n_final_project (0\u2605) \u2014 Investigating trade-offs between (Mamba) State Space Model, Transformers, and custom-implemented Hybrid Model in specialized reasoning tasks", "url": "https://github.com/scraper-sky/cs224n_final_project", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:chokevin8--mvhybrid", "kind": "repo", "label": "chokevin8/MVHybrid (1\u2605) \u2014 MVHybrid: Improving Spatial Transcriptomics Prediction with Hybrid State Space-Vision Transformer Backbone in Pathology Vision Foundation Models (MICCAI 2025 COMPAYL Oral)", "url": "https://github.com/chokevin8/MVHybrid", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:gracee-dion--mambavision-multispectral-soil-analysis", "kind": "repo", "label": "GraceE-Dion/MambaVision-MultiSpectral-Soil-Analysis (0\u2605) \u2014 MambaVision Hybrid Mamba-Transformer backbone applied to multi-spectral laser soil moisture classification - extending the ViT baseline with state-space sequence modeling", "url": "https://github.com/GraceE-Dion/MambaVision-MultiSpectral-Soil-Analysis", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:gokulprasanth-m--vimbaformer-a-hybrid-vision-mamba-unet-architecture-for-uav-semantic-segmentation", "kind": "repo", "label": "GOKULPRASANTH-M/ViMbaFormer-A-Hybrid-Vision-Mamba-Unet-Architecture-for-UAV-Semantic-Segmentation (0\u2605) \u2014 ViMbaFormer is a hybrid semantic segmentation framework designed for high-resolution UAV imagery. It integrates Vision Transformers, Mamba State Space Models, and a U-Net\u2013style encoder\u2013decoder to", "url": "https://github.com/GOKULPRASANTH-M/ViMbaFormer-A-Hybrid-Vision-Mamba-Unet-Architecture-for-UAV-Semantic-Segmentation", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:harsh543--nemotron-vllm-l4-infra", "kind": "repo", "label": "harsh543/nemotron-vllm-l4-infra (0\u2605) \u2014  Nemotron-Hybrid vLLM Orchestrator This infrastructure is designed to serve the NVIDIA Nemotron-Nano-9B-v2, a hybrid model combining Transformer and Mamba-2 architectures. Running this on a single-nod", "url": "https://github.com/harsh543/nemotron-vllm-l4-infra", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:anany25--advanced-colorization-gan", "kind": "repo", "label": "Anany25/Advanced-Colorization-GAN (0\u2605) \u2014 A high-performing image colorization model in PyTorch, featuring a hybrid Vision Transformer (ViT) and U-Net generator. This GAN operates in the LAB color space and is stabilized with modern techniqu", "url": "https://github.com/Anany25/Advanced-Colorization-GAN", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:arks0001--hymba-1.5b", "kind": "repo", "label": "ArkS0001/Hymba-1.5B (0\u2605) \u2014 The model has hybrid architecture with Mamba and Attention heads running in parallel", "url": "https://github.com/ArkS0001/Hymba-1.5B", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:fabian-bautista--mlx-hymba", "kind": "repo", "label": "fabian-bautista/mlx-hymba (0\u2605) \u2014 Run NVIDIA Hymba on Apple Silicon via MLX. Hybrid attention + Mamba SSM heads, native to M1/M2/M3/M4, no CUDA required.", "url": "https://github.com/fabian-bautista/mlx-hymba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:dogacel--auto-gpu-kernel", "kind": "repo", "label": "Dogacel/auto-gpu-kernel (147\u2605) \u2014 Winner \ud83c\udfc6 (Agent-only) MLSys 2026 - FlashInfer AI Kernel Generation Contest for the DeepSeek Sparse Attention (DSA) track with an average speedup of 34.93x", "url": "https://github.com/Dogacel/auto-gpu-kernel", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:msdllcpapers--triton-sigmoid", "kind": "repo", "label": "MSDLLCpapers/triton-sigmoid (7\u2605) \u2014 Fused sigmoid attention kernels for NVIDIA GPUs built with Triton.", "url": "https://github.com/MSDLLCpapers/triton-sigmoid", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:prachi-kushwaha--triton-guide", "kind": "repo", "label": "Prachi-kushwaha/Triton-guide (3\u2605) \u2014 A hands-on guide to writing fast custom GPU kernels in Triton :-- from your first vector addition to fused attention mechanisms.", "url": "https://github.com/Prachi-kushwaha/Triton-guide", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:jerry2423--triton-attention-kernels", "kind": "repo", "label": "Jerry2423/Triton-Attention-Kernels (0\u2605) \u2014 GPU attention kernels for LLM inference, implemented from scratch in Triton.", "url": "https://github.com/Jerry2423/Triton-Attention-Kernels", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:mohamedabbouda--flash-attention-gpu-kernel", "kind": "repo", "label": "mohamedabbouda/Flash-Attention-GPU-Kernel (0\u2605) \u2014 Triton FlashAttention kernel with PyTorch autograd, correctness tests, and GPU benchmarks.", "url": "https://github.com/mohamedabbouda/Flash-Attention-GPU-Kernel", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:caroline430--kernel-learning", "kind": "repo", "label": "caroline430/kernel-learning (4\u2605) \u2014 Everything-in-one-place GPU kernel programming for ML engineers. Covers CUDA, Triton, Flash Attention 2/3, paged attention, Mamba, speculative decoding, FP8/AWQ/GPTQ quantization, cuBLAS/cuDNN/CUTLASS", "url": "https://github.com/caroline430/kernel-learning", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:kaustubhas--triton-based-tiled-flashattention-gpu-kernel", "kind": "repo", "label": "KaustubhAs/Triton-Based-Tiled-FlashAttention-GPU-Kernel (0\u2605)", "url": "https://github.com/KaustubhAs/Triton-Based-Tiled-FlashAttention-GPU-Kernel", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:chinmaydk99--gpu_optimized_attention_mechanisms", "kind": "repo", "label": "chinmaydk99/GPU_Optimized_Attention_Mechanisms (0\u2605) \u2014 Starting with MultiHead Attention, kernels to optimize existing methods using triton or CUDA", "url": "https://github.com/chinmaydk99/GPU_Optimized_Attention_Mechanisms", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:anggipratama17--triton-accelerated-attention", "kind": "repo", "label": "Anggipratama17/triton-accelerated-attention (1\u2605) \u2014 \ud83d\ude80 Implement Triton GPU kernels for multi-head self-attention, enabling efficient understanding and benchmarking of core attention computations.", "url": "https://github.com/Anggipratama17/triton-accelerated-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:harrisonvshen--triton-accelerated-attention", "kind": "repo", "label": "harrisonvshen/triton-accelerated-attention (1\u2605) \u2014 Custom Triton GPU kernels for multi-head attention, including QK^T, softmax, and value aggregation with end-to-end benchmarking.", "url": "https://github.com/harrisonvshen/triton-accelerated-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:jrajath94--triton-inference-kernels", "kind": "repo", "label": "jrajath94/triton-inference-kernels (0\u2605) \u2014 Fused softmax + Flash Attention in OpenAI Triton \u2014 50x VRAM reduction at seq_len=2048", "url": "https://github.com/jrajath94/triton-inference-kernels", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:visharadr--mini-transformer---gpu-optimized", "kind": "repo", "label": "VisharadR/Mini-Transformer---GPU-optimized (2\u2605) \u2014 a mini-Transformer inference engine with custom CUDA/Triton kernels (layernorm, QKV projection, attention, MLP) that beats a na\u00efve PyTorch baseline on latency and throughput.", "url": "https://github.com/VisharadR/Mini-Transformer---GPU-optimized", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:bhavikupadhyay--triton-kernels", "kind": "repo", "label": "Bhavikupadhyay/triton-kernels (1\u2605) \u2014 22 progressive Triton GPU kernels, from elementwise ops to Flash Attention v2, featuring correctness tests and PyTorch throughput/TFLOPS benchmarks.  ", "url": "https://github.com/Bhavikupadhyay/triton-kernels", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:yifu-ding--mp-sparse-attn", "kind": "repo", "label": "yifu-ding/MP-Sparse-Attn (2\u2605) \u2014 MP-Sparse-Attn provides Triton kernels for Diagonal-Tiled Mixed-Precision Attention, targeting efficient low-bit MXFP inference for Transformer models. It combines tile-level mixed-precision computati", "url": "https://github.com/yifu-ding/MP-Sparse-Attn", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:tobiaszn8972--turboquant-gpu", "kind": "repo", "label": "Tobiaszn8972/turboquant-gpu (2\u2605) \u2014 Compress KV cache for LLM inference with 5.02x efficiency on NVIDIA GPUs using cuTile kernels.", "url": "https://github.com/Tobiaszn8972/turboquant-gpu", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:selau642--quantizedattention", "kind": "repo", "label": "selau642/QuantizedAttention (0\u2605) \u2014 GPU Triton Kernels written in Helion to speed up Attention inference, fine tuning and training speeds.", "url": "https://github.com/selau642/QuantizedAttention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:susmitsingh01--triton-llm-kernels-lab", "kind": "repo", "label": "susmitsingh01/triton-llm-kernels-lab (0\u2605) \u2014 A hands-on lab implementing LLM inference kernels from scratch using Triton. Covers fused attention, Flash Attention, GQA, RoPE, INT8 quantization, KV cache optimization, and speculative decoding \u2014 wi", "url": "https://github.com/susmitsingh01/triton-llm-kernels-lab", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:winnie1221--flash-attention-triton", "kind": "repo", "label": "Winnie1221/flash-attention-triton (0\u2605) \u2014 # FlashAttention Implementation in PyTorch & Triton  Implemented FlashAttention forward/backward pass from scratch using PyTorch and Triton kernels, optimized for GPU memory efficiency. Trained and be", "url": "https://github.com/Winnie1221/flash-attention-triton", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:indrarg8899--triton-rocm-samples", "kind": "repo", "label": "indrarg8899/triton-rocm-samples (0\u2605) \u2014 Triton kernel samples and tutorials for AMD GPUs \u2014 matmul, flash attention, softmax, reduce with ROCm backend", "url": "https://github.com/indrarg8899/triton-rocm-samples", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:argonaut790--fused-turboquant", "kind": "repo", "label": "Argonaut790/fused-turboquant (8\u2605) \u2014 Fused Triton kernels for TurboQuant KV cache compression \u2014 2-4 bit quantization with RHT rotation. Drop-in HuggingFace & vLLM integration. Up to 4.9x KV cache compression for Llama, Qwen, Mistral, and", "url": "https://github.com/Argonaut790/fused-turboquant", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:brianyu43--triton-training", "kind": "repo", "label": "brianyu43/triton-training (0\u2605) \u2014 CUDA & Triton kernel training \u2014 progressively built vector add \u2192 reduction \u2192 softmax \u2192 matmul \u2192 flash attention (MHA, causal). Lesson-by-lesson handoff docs + L4 GPU benchmarks.", "url": "https://github.com/brianyu43/triton-training", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:chelokot--flash-attention-rdna3", "kind": "repo", "label": "chelokot/flash-attention-rdna3 (0\u2605) \u2014 FlashAttention-2 Triton kernel for AMD RDNA3 (gfx1100 / Radeon RX 7900 XT/XTX/GRE): forward, backward, and split-K decode", "url": "https://github.com/chelokot/flash-attention-rdna3", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:gaurav711cgu--tritonforge", "kind": "repo", "label": "Gaurav711cgu/Tritonforge (1\u2605) \u2014 An automated GPU kernel optimization and profiling workstation compiling fused OpenAI Triton kernels (RMSNorm, SwiGLU, Tiled Attention) to maximize SRAM reuse. Exposes custom backward autograd functio", "url": "https://github.com/Gaurav711cgu/Tritonforge", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:haregali--pageskip", "kind": "repo", "label": "haregali/pageskip (0\u2605) \u2014 Page-sparse flash-decode attention kernels in Triton: 94% of memory bandwidth dense, 16x past it sparse", "url": "https://github.com/haregali/pageskip", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:j-arndt--orthocache-gpu", "kind": "repo", "label": "j-arndt/orthocache-gpu (0\u2605) \u2014 Spectral KV-cache eviction for NVIDIA GPUs \u2014 1.28\u00d7 faster attention at 32K+ context with 50% KV memory savings. Fused Walsh-Hadamard Split-K Triton kernel. Lean 4 verified.", "url": "https://github.com/j-arndt/orthocache-gpu", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:iamrahulreddy--flashtile", "kind": "repo", "label": "iamrahulreddy/FlashTile (1\u2605) \u2014 Reference Flash Attention implementation in PyTorch with V1/V2, GQA/MQA, Triton kernels, benchmark and docs.", "url": "https://github.com/iamrahulreddy/FlashTile", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:jaehbk--triton-programming-course", "kind": "repo", "label": "jaeHbk/triton-programming-course (0\u2605) \u2014 An agent-guided skeleton course for learning the Triton GPU programming language, from first kernel to fused attention and frontier hardware. Read it with your AI partner. Structure modeled on the Age", "url": "https://github.com/jaeHbk/triton-programming-course", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:joey0122--mini-gpu-inference-engine", "kind": "repo", "label": "Joey0122/Mini-GPU-Inference-Engine (0\u2605) \u2014 CUDA-based GPT-2 124M inference from scratch. Self-implemented kernels: reduction, scan, transpose, GEMM (FP32/FP16 Tensor Core), layer norm, softmax, GELU, attention. Validated against PyTorch. Bench", "url": "https://github.com/Joey0122/Mini-GPU-Inference-Engine", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:skyhehe123--scatterformer", "kind": "repo", "label": "skyhehe123/ScatterFormer (80\u2605) \u2014 ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention (ECCV 2024)", "url": "https://github.com/skyhehe123/ScatterFormer", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:xinghaochen--slab", "kind": "repo", "label": "xinghaochen/SLAB (110\u2605) \u2014 [ICML 2024] Official PyTorch implementation of \"SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization\"", "url": "https://github.com/xinghaochen/SLAB", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:milmor--ladagan", "kind": "repo", "label": "milmor/LadaGAN (9\u2605) \u2014 Efficient generative adversarial networks using linear additive-attention Transformers", "url": "https://github.com/milmor/LadaGAN", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:acosharma--elita-transformer", "kind": "repo", "label": "acosharma/elita-transformer (18\u2605) \u2014 Official Repository for Efficient Linear-Time Attention Transformers.", "url": "https://github.com/acosharma/elita-transformer", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:aliothren--efficient-transformer-accelerator", "kind": "repo", "label": "aliothren/efficient-transformer-accelerator (2\u2605) \u2014 This is for ECE562 project Energy-Efficient Accelerator Architecture for Transformers Using Linear Attention", "url": "https://github.com/aliothren/efficient-transformer-accelerator", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:zeeza18--efficient_transformer", "kind": "repo", "label": "zeeza18/EFFICIENT_TRANSFORMER (3\u2605) \u2014 Research implementation of Hierarchical Tree Attention (HTA) - an efficient transformer achieving O(N log N) complexity through recursive binary aggregation and chunkwise linear attention. 91.39% accu", "url": "https://github.com/zeeza18/EFFICIENT_TRANSFORMER", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:arturbeg--efficient_transformer", "kind": "repo", "label": "arturbeg/efficient_transformer (2\u2605) \u2014 Scaling Transformer architectures has been critical for pushing the frontiers of Language Modelling (LM), a problem central to Natural Language Processing (NLP) and Language Understanding. Although th", "url": "https://github.com/arturbeg/efficient_transformer", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:szu-advtech-2024-test--363-gated-linear-attention-transformers-with-hardware-efficient-training", "kind": "repo", "label": "SZU-AdvTech-2024-Test/363-Gated-Linear-Attention-Transformers-with-Hardware-Efficient-Training (0\u2605)", "url": "https://github.com/SZU-AdvTech-2024-Test/363-Gated-Linear-Attention-Transformers-with-Hardware-Efficient-Training", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:szu-advtech-2024--363-gated-linear-attention-transformers-with-hardware-efficient-training", "kind": "repo", "label": "SZU-AdvTech-2024/363-Gated-Linear-Attention-Transformers-with-Hardware-Efficient-Training (1\u2605)", "url": "https://github.com/SZU-AdvTech-2024/363-Gated-Linear-Attention-Transformers-with-Hardware-Efficient-Training", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:johndpope--ladagan-pytorch", "kind": "repo", "label": "johndpope/LadaGAN-pytorch (1\u2605) \u2014 Efficient generative adversarial networks using linear additive-attention Transformers", "url": "https://github.com/johndpope/LadaGAN-pytorch", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:duongngockhanh--ladagan", "kind": "repo", "label": "duongngockhanh/ladagan (0\u2605) \u2014 An implementation of LadaGAN: Efficient Generative Adversarial Networks using Linear ADditive-Attention Transformers", "url": "https://github.com/duongngockhanh/ladagan", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:mohammedqaraad--msh-trans", "kind": "repo", "label": "MohammedQaraad/MSH-Trans (0\u2605) \u2014 MSH-Trans: A Multi-Scale Hybrid Transformer with Linear Attention for Parameter-Efficient Brain Tumor Segmentation", "url": "https://github.com/MohammedQaraad/MSH-Trans", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:shahazzat--fanformergpt", "kind": "repo", "label": "shahazzat/FANformerGPT (0\u2605) \u2014 A lightweight Causal Transformer with Causal Linear Attention, designed for efficient autoregressive text generation and question answering.", "url": "https://github.com/shahazzat/FANformerGPT", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:imfatal--implementation-and-analysis-of-transformer-variants", "kind": "repo", "label": "Imfatal/Implementation-and-Analysis-of-Transformer-Variants (0\u2605) \u2014 PyTorch implementations and comparative evaluation of Transformer and Conformer variants, including efficient attention mechanisms (Sliding Window, Linear, and Multi-Query Attention), positional encod", "url": "https://github.com/Imfatal/Implementation-and-Analysis-of-Transformer-Variants", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:ghsjk--esst", "kind": "repo", "label": "ghsjk/ESST (0\u2605) \u2014 An efficient semantic  segmentation Transformer (ESST) of RSIs that combines zero-padding position encoding with linear space reduction attention.", "url": "https://github.com/ghsjk/ESST", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:likith-sg--hmct", "kind": "repo", "label": "likith-sg/HMCT (0\u2605) \u2014 A hierarchical memory-augmented Transformer architecture for efficient long-context sequence modeling using gated multi-tier memory and linear attention.", "url": "https://github.com/likith-sg/HMCT", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:amrutiyakirtan--factorized-vit-probsparsing", "kind": "repo", "label": "AmrutiyaKirtan/Factorized-vit-Probsparsing (0\u2605) \u2014 This repository presents Factorized Vision Transformers (FaViT) with ProbSparse self-attention for efficient image classification. The architecture factorizes ViT blocks and uses probabilistic sparse ", "url": "https://github.com/AmrutiyaKirtan/Factorized-vit-Probsparsing", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:sohamkudva--gcltmodel", "kind": "repo", "label": "SohamKudva/GCLTModel (0\u2605) \u2014 PyTorch implementation of the Gated Chunkwise Linear Transformer (GCLT). This architecture combines chunkwise exact attention with global linear recurrence to achieve O(N) memory scaling. It efficient", "url": "https://github.com/SohamKudva/GCLTModel", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:nvlabs--mambavision", "kind": "repo", "label": "NVlabs/MambaVision (2198\u2605) \u2014 [CVPR 2025] Official PyTorch Implementation of MambaVision: A Hybrid Mamba-Transformer Vision Backbone", "url": "https://github.com/NVlabs/MambaVision", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:xiongxiaoxu--sst", "kind": "repo", "label": "XiongxiaoXu/SST (229\u2605) \u2014 The code of CIKM'25 paper: \"SST: Multi-Scale Hybrid Mamba-Transformer Experts for Time Series Forecasting\"", "url": "https://github.com/XiongxiaoXu/SST", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:tiger-ai-lab--vamba", "kind": "repo", "label": "TIGER-AI-Lab/Vamba (104\u2605) \u2014 Code for the paper \"Vamba: Understanding Hour-Long Videos with Hybrid Mamba-Transformers\" [ICCV 2025]", "url": "https://github.com/TIGER-AI-Lab/Vamba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:xiaoyao3302--pointramba", "kind": "repo", "label": "xiaoyao3302/PoinTramba (72\u2605) \u2014 PoinTramba: A Hybrid Transformer-Mamba Framework for Point Cloud Analysis", "url": "https://github.com/xiaoyao3302/PoinTramba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:wenjuan7275--matir", "kind": "repo", "label": "wenjuan7275/MatIR (20\u2605) \u2014 MatIR: A Hybrid Mamba-Transformer Image Restoration Model", "url": "https://github.com/wenjuan7275/MatIR", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:hu-po--karpamambathy", "kind": "repo", "label": "hu-po/karpamambathy (7\u2605) \u2014 hybrid mamba transformer on arc challenge", "url": "https://github.com/hu-po/karpamambathy", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:vukrosic--hybrid-llm-mamba-transformer-research", "kind": "repo", "label": "vukrosic/hybrid-llm-mamba-transformer-research (8\u2605) \u2014 hybrid-llm-mamba-transformer-research", "url": "https://github.com/vukrosic/hybrid-llm-mamba-transformer-research", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:deepinact--hybridtm", "kind": "repo", "label": "deepinact/HybridTM (26\u2605) \u2014 [IROS 2025] Official code of \u201dHybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation\u201c", "url": "https://github.com/deepinact/HybridTM", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:enesdoruk--da-mamba", "kind": "repo", "label": "enesdoruk/DA-Mamba (17\u2605) \u2014 [ECAI] DA-Mamba: Domain Adaptive Hybrid Mamba-Transformer Based One-Stage Object Detection", "url": "https://github.com/enesdoruk/DA-Mamba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:nubot-nudt--inscmpr", "kind": "repo", "label": "nubot-nudt/InsCMPR (26\u2605) \u2014 [ICRA 25] InsCMPR: Efficient Cross-Modal Place Recognition via Instance-Aware Hybrid Mamba-Transformer", "url": "https://github.com/nubot-nudt/InsCMPR", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:xiaomi-research--timeviper", "kind": "repo", "label": "xiaomi-research/timeviper (25\u2605) \u2014 [CVPR'26] TimeViper: A Hybrid Mamba-Transformer Vision-Language Model for Efficient Long Video Understanding", "url": "https://github.com/xiaomi-research/timeviper", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:vukrosic--hybrid-llm-mamba-transformer-research-2", "kind": "repo", "label": "vukrosic/hybrid-llm-mamba-transformer-research-2 (4\u2605) \u2014 hybrid-llm-mamba-transformer-research-2", "url": "https://github.com/vukrosic/hybrid-llm-mamba-transformer-research-2", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:nhanth301--mambastegaformer", "kind": "repo", "label": "nhanth301/MambaStegaFormer (4\u2605) \u2014 MambaStegaFormer: Serial Style Transfer with Content Steganography and Hybrid Mamba-Transformer", "url": "https://github.com/nhanth301/MambaStegaFormer", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:elonlit--melchior", "kind": "repo", "label": "elonlit/melchior (4\u2605) \u2014 Melchior: A Hybrid Mamba-Transformer RNA Basecaller", "url": "https://github.com/elonlit/melchior", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:yixing-li--transmamba", "kind": "repo", "label": "Yixing-Li/TransMamba (6\u2605) \u2014 Official code for paper: TransMamba: A Sequence-Level Hybrid Transformer-Mamba Language Model (AAAI 2026 Poster)", "url": "https://github.com/Yixing-Li/TransMamba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:lihongzhao99--rrgmambaformer", "kind": "repo", "label": "lihongzhao99/RRGMambaFormer (4\u2605) \u2014 RRGMambaFormer: A Hybrid Transformer-Mamba Architecture for Radiology Report Generation", "url": "https://github.com/lihongzhao99/RRGMambaFormer", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:vukrosic--hybrid-llm-mamba-transformer-research-3", "kind": "repo", "label": "vukrosic/hybrid-llm-mamba-transformer-research-3 (2\u2605) \u2014 hybrid-llm-mamba-transformer-research-3", "url": "https://github.com/vukrosic/hybrid-llm-mamba-transformer-research-3", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:varun3ware--paged-attention", "kind": "repo", "label": "VARUN3WARE/Paged-Attention (8\u2605) \u2014 Implementation of PagedAttention from vLLM paper - a notable attention algorithm that treats KV cache like virtual memory. Eliminates memory fragmentation, increases batch sizes, and dramatically", "url": "https://github.com/VARUN3WARE/Paged-Attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:icecreammilkytea--pagedkvcomm", "kind": "repo", "label": "IceCreamMilkyTea/PagedKVCOMM (0\u2605) \u2014 Accelerating multi-agent system with paged attention and kv cache reuse .", "url": "https://github.com/IceCreamMilkyTea/PagedKVCOMM", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:mukhal--micro-vllm", "kind": "repo", "label": "mukhal/micro-vllm (2\u2605) \u2014 A single-file implementation of KV cache paged attention ", "url": "https://github.com/mukhal/micro-vllm", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:jnros--cuda-attn-ref", "kind": "repo", "label": "jnros/cuda-attn-ref (2\u2605) \u2014 Paged Attention: virtual memory for KV Cache in CUDA", "url": "https://github.com/jnros/cuda-attn-ref", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:manankapoor23--kv-paged-attention", "kind": "repo", "label": "manankapoor23/KV-Paged-Attention (0\u2605) \u2014 This project implements a simplified KV-cache paging system for autoregressive Transformer inference, inspired by production inference engines such as vLLM.  The goal is to demonstrate how paged memor", "url": "https://github.com/manankapoor23/KV-Paged-Attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:bojjachetan--flash-decode-paged-attention", "kind": "repo", "label": "bojjachetan/flash-decode-paged-attention (0\u2605) \u2014 CUDA paged KV-cache decode attention kernel for LLM inference", "url": "https://github.com/bojjachetan/flash-decode-paged-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:truongson421--triton_kernel_paged_kv_cache_attention", "kind": "repo", "label": "TruongSon421/Triton_Kernel_Paged_KV_Cache_Attention (0\u2605)", "url": "https://github.com/TruongSon421/Triton_Kernel_Paged_KV_Cache_Attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:gaurav-redhat--paged-attention", "kind": "repo", "label": "gaurav-redhat/Paged-Attention (0\u2605) \u2014 Efficient memory management for Large Language Model (LLM) inference using block-based KV cache.", "url": "https://github.com/gaurav-redhat/Paged-Attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:capybara-brain346--pagedattention-simulation", "kind": "repo", "label": "capybara-brain346/PagedAttention-Simulation (1\u2605) \u2014 This project implements a PagedAttention mechanism for managing key-value (KV) cache in large language models. It simulates memory allocation, block management, and cache hit/miss tracking for prompt/", "url": "https://github.com/capybara-brain346/PagedAttention-Simulation", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:lisihao--thunderllama", "kind": "repo", "label": "lisihao/ThunderLLAMA (3\u2605) \u2014 Apple Silicon Paged Attention for llama.cpp - Efficient KV cache management on M1/M2/M3/M4 GPUs", "url": "https://github.com/lisihao/ThunderLLAMA", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:zhihengy--int8-quantized-kv-cache-for-efficient-paged-attention", "kind": "repo", "label": "zhihengy/Int8-Quantized-KV-Cache-for-Efficient-Paged-Attention (0\u2605)", "url": "https://github.com/zhihengy/Int8-Quantized-KV-Cache-for-Efficient-Paged-Attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:p4ralyn--aapt_pagedattention", "kind": "repo", "label": "p4ralyn/AAPT_PagedAttention (0\u2605) \u2014 A natively integrated, hardware-aware memory management subsystem for the xv6 RISC-V kernel. Implements OS-level Copy-on-Write (CoW) and PagedAttention primitives to mitigate KV-cache redundancy in co", "url": "https://github.com/p4ralyn/AAPT_PagedAttention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:abderahmane-ai--pagedattentionmetal", "kind": "repo", "label": "abderahmane-ai/PagedAttentionMetal (0\u2605) \u2014   PagedAttentionMetal is a production-ready, hardware-accelerated implementation of the PagedAttention algorithm (from   vLLM) built natively for Apple Silicon using Metal 3. It provides efficient mem", "url": "https://github.com/abderahmane-ai/PagedAttentionMetal", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:hemanthiitj--kvstream", "kind": "repo", "label": "HemanthIITJ/KVstream (0\u2605) \u2014 KVStream sits in front of your existing LLM runtime and fixes the biggest bottleneck in local inference: wasted KV cache memory and poor batching. By streaming KV allocation instead of reserving it up", "url": "https://github.com/HemanthIITJ/KVstream", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:sanjanashah--llm-paged-batching", "kind": "repo", "label": "SanjanaShah/llm-paged-batching (0\u2605) \u2014 A lightweight LLM inference serving simulator implementing paged attention, KV-cache management, and continuous batching.", "url": "https://github.com/SanjanaShah/llm-paged-batching", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:akshitha024--kv-cache-optimizer", "kind": "repo", "label": "Akshitha024/kv-cache-optimizer (0\u2605) \u2014 Discrete-step KV-cache simulator + attention-variant and eviction-policy ablation (Flash, Paged, Chunked-prefill x LRU, LFU, Time)", "url": "https://github.com/Akshitha024/kv-cache-optimizer", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:gandholisarat--kv-cache-visualizer", "kind": "repo", "label": "GandholiSarat/kv-cache-visualizer (1\u2605) \u2014 A conceptual, client\u2011side KV Cache and Paged Attention visualizer for LLM inference. It demonstrates prefill vs decode, paged KV blocks, and continuous batching without running a real model.", "url": "https://github.com/GandholiSarat/kv-cache-visualizer", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:zlatanwic--fused-kernel-for-paged-attention", "kind": "repo", "label": "Zlatanwic/Fused-Kernel-for-Paged-attention (0\u2605) \u2014 \u9762\u5411\u5927\u6a21\u578b\u957f\u4e0a\u4e0b\u6587\u89e3\u7801\u573a\u666f\uff0c\u5b9e\u73b0\u5e76\u5206\u6790 paged KV cache \u7684 block-gather CUDA kernel\uff0c\u9a8c\u8bc1 fused attention \u5bf9\u51cf\u5c11\u4e2d\u95f4\u663e\u5b58\u6d41\u91cf\u548c\u63d0\u5347 decode \u541e\u5410\u7684\u6548\u679c\u3002", "url": "https://github.com/Zlatanwic/Fused-Kernel-for-Paged-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:kennethjefferson--ccg_app_cuda_vllmpagedinference", "kind": "repo", "label": "KennethJefferson/ccg_app_cuda_VllmPagedInference (0\u2605) \u2014 vLLM-style paged-attention inference engine for TinyLlama 1.1B int4 on NVIDIA T1200 Turing sm_75: Triton prefill + paged-decode kernels, KV-cache block manager, FastAPI streaming server", "url": "https://github.com/KennethJefferson/ccg_app_cuda_VllmPagedInference", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:sahil139--predictive-kv-prefetch", "kind": "repo", "label": "sahil139/predictive-kv-prefetch (0\u2605) \u2014 Predictive KV-cache prefetching framework for transformer inference. It compares baseline, reactive paging, and attention-driven predictive caching to reduce GPU memory stalls.", "url": "https://github.com/sahil139/predictive-kv-prefetch", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:google-deepmind--recurrentgemma", "kind": "repo", "label": "google-deepmind/recurrentgemma (682\u2605) \u2014 Open weights language model from Google DeepMind, based on Griffin.", "url": "https://github.com/google-deepmind/recurrentgemma", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:google-gemma--cookbook", "kind": "repo", "label": "google-gemma/cookbook (3874\u2605) \u2014 A collection of guides and examples for the Gemma open models from Google.", "url": "https://github.com/google-gemma/cookbook", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:surakku--cadence-gemma", "kind": "repo", "label": "surakku/cadence-gemma (0\u2605) \u2014 Giving RecurrentGemma sight.", "url": "https://github.com/surakku/cadence-gemma", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:tushaargvs--sae", "kind": "repo", "label": "TushaarGVS/sae (0\u2605) \u2014 Sparse autoencoder for recurrentgemma", "url": "https://github.com/TushaarGVS/sae", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:sw10-cryptanalysis--recurrentgemma", "kind": "repo", "label": "SW10-Cryptanalysis/RecurrentGemma (0\u2605) \u2014 trained to decipher long homophonic substitution ciphers without spaces and punctutation.", "url": "https://github.com/SW10-Cryptanalysis/RecurrentGemma", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:firmanadi2002--recurrentgemma_summarizer", "kind": "repo", "label": "firmanadi2002/RecurrentGemma_Summarizer (0\u2605) \u2014 Repository ini berisi Model Recurrent Gemma yang telah dilatih untuk tugas peringkas teks berita berbahasa Indonesia", "url": "https://github.com/firmanadi2002/RecurrentGemma_Summarizer", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:vyom1611--recurrentgemma-cuda", "kind": "repo", "label": "vyom1611/RecurrentGemma-CUDA (0\u2605) \u2014 Optimized version of the RecurrentGemma model written in Torch + CUDA. Implements advance kernels and inference techniques", "url": "https://github.com/vyom1611/RecurrentGemma-CUDA", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:tushaargvs--simple-linear-rnn", "kind": "repo", "label": "TushaarGVS/simple-linear-rnn (1\u2605) \u2014 Triton kernels for linear RNN (currently recurrentgemma)", "url": "https://github.com/TushaarGVS/simple-linear-rnn", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:rajivraghu--google-recurrentgemma_2b", "kind": "repo", "label": "rajivraghu/google-recurrentgemma_2b (0\u2605) \u2014 Opensource Google Recurren Gemma_2b", "url": "https://github.com/rajivraghu/google-recurrentgemma_2b", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:harshks911--molgemma-using-recurrentgemma-architecture", "kind": "repo", "label": "harshKS911/MOLgemma-using-recurrentgemma-architecture (1\u2605)", "url": "https://github.com/harshKS911/MOLgemma-using-recurrentgemma-architecture", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:brendanjameslynskey--arch_03_long_context", "kind": "repo", "label": "BrendanJamesLynskey/Arch_03_Long_Context (0\u2605) \u2014 Long-context LLMs: RoPE, position interpolation, NTK-aware scaling, YaRN, ALiBi, sliding window attention, StreamingLLM sink tokens, ring attention, context parallelism", "url": "https://github.com/BrendanJamesLynskey/Arch_03_Long_Context", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:semanticarchitectures--interceptordronesim", "kind": "repo", "label": "semanticarchitectures/interceptorDroneSim (5\u2605) \u2014 Counter-UAS interceptor drone engagement simulation \u2014 full kill chain from detection through intercept", "url": "https://github.com/semanticarchitectures/interceptorDroneSim", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:paragontechnologies--cuas-drone-detection", "kind": "repo", "label": "ParagonTechnologies/cuas-drone-detection (2\u2605) \u2014 Multi-sensor fusion system for counter-UAS drone detection", "url": "https://github.com/ParagonTechnologies/cuas-drone-detection", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:soussi-aymen--drone-detection-frontend", "kind": "repo", "label": "Soussi-Aymen/drone-detection-frontend (0\u2605) \u2014 This repository contains the single-page application (SPA) frontend for the Counter-UAS (C-UAS) system. It serves as the users primary interface for real-time situational awareness.", "url": "https://github.com/Soussi-Aymen/drone-detection-frontend", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:mohamesb--ai-powered-drone-detection-system", "kind": "repo", "label": "mohamesb/AI-Powered-Drone-Detection-System (0\u2605) \u2014 A full-stack project demonstrating AI-powered drone detection inspired by counter-UAS defense systems.", "url": "https://github.com/mohamesb/AI-Powered-Drone-Detection-System", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:gerardgz--autonomous-drone-landing-risk-detection", "kind": "repo", "label": "GerardGz/autonomous-drone-landing-risk-detection (0\u2605) \u2014 Computer Vision based counter-uas threat detection system, which utilizes a custom cnn and public datasets.", "url": "https://github.com/GerardGz/autonomous-drone-landing-risk-detection", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:soussi-aymen--drone-detection-backend", "kind": "repo", "label": "Soussi-Aymen/drone-detection-backend (1\u2605) \u2014 This repository contains the backend orchestration layer for the Counter-UAS (C-UAS) Human-Machine Interface (HMI) system, focused on providing real-time threat detection awareness to individual users", "url": "https://github.com/Soussi-Aymen/drone-detection-backend", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:suliman8--skyshield", "kind": "repo", "label": "Suliman8/SkyShield (0\u2605) \u2014 RF-Based Drone Detection, Payload Analysis & Threat Classification System - Affordable open-source Counter-UAS research", "url": "https://github.com/Suliman8/SkyShield", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:jiyounroth--drone_rf_detection_fpga", "kind": "repo", "label": "JiyounRoth/Drone_RF_Detection_FPGA (0\u2605) \u2014 This project implements a high-performance RF Signal Detection pipeline on an FPGA specifically designed for Portabel/Handheld Counter-UAS (Unmanned Aircraft Systems) Hardware. The design focuses on r", "url": "https://github.com/JiyounRoth/Drone_RF_Detection_FPGA", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:sayeh-1337--meshkah", "kind": "repo", "label": "Sayeh-1337/meshkah (0\u2605) \u2014 meshkah is an academic Counter-UAS (CUAS) prototype that fuses RGB, thermal, RF, and acoustic detections to estimate and track drone position in 3D. It integrates ROS 2 Jazzy, Gazebo Harmonic, and Ard", "url": "https://github.com/Sayeh-1337/meshkah", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:a-for-aarushi--ps-09---ai-tools-for-maritime-domain-awareness-", "kind": "repo", "label": "a-for-aarushi/PS-09---AI-tools-for-Maritime-Domain-Awareness- (1\u2605) \u2014 End-to-end AI solution for Maritime Domain Awareness featuring vessel detection from EO/SAR imagery, length-width-heading estimation, AIS correlation, vessel classification, and path interpolation/pre", "url": "https://github.com/a-for-aarushi/PS-09---AI-tools-for-Maritime-Domain-Awareness-", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:razerardi--dark-vessel-sar-detection", "kind": "repo", "label": "RazerArdi/dark-vessel-sar-detection (0\u2605) \u2014 Neuro-symbolic Maritime Domain Awareness System (MDAS) for real-time SAR imagery decoding, geospatial extrapolation, and automated SITREP generation.", "url": "https://github.com/RazerArdi/dark-vessel-sar-detection", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:iberasa3--carcosa", "kind": "repo", "label": "Iberasa3/Carcosa (0\u2605) \u2014 Detecting illegal maritime activity by cross-referencing real-time satellite detections with AIS broadcasts. Built to combat IUU (Illegal, Unreported, and Unregulated) fishing and enhance maritime dom", "url": "https://github.com/Iberasa3/Carcosa", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:andrewkritikos--ais_anomaly_detection", "kind": "repo", "label": "AndrewKritikos/ais_anomaly_detection (1\u2605) \u2014 This real-time anomaly detection system exposes deceptive shipping practices utilized by the 'shadow fleet' for illicit operations. By processing live AIS telemetry from the Strait of Malacca, it math", "url": "https://github.com/AndrewKritikos/ais_anomaly_detection", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:moulirichards--a-machine-learning-based-approach-for-detection-of-ships-and-uavs-in-military-forces", "kind": "repo", "label": "Moulirichards/A-machine-learning-based-approach-for-detection-of-ships-and-UAVs-in-military-forces (0\u2605) \u2014 This system detects ships in satellite images using Faster R-CNN and identifies drones in real-time video with YOLOv5. Featuring a military-themed, user-friendly interface, it enhances situation", "url": "https://github.com/Moulirichards/A-machine-learning-based-approach-for-detection-of-ships-and-UAVs-in-military-forces", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:madeit07--radarmotr", "kind": "repo", "label": "madeit07/RadarMOTR (20\u2605) \u2014 Multi-Object Tracking with Transformer Neural Networks on Range-Doppler Maps", "url": "https://github.com/madeit07/RadarMOTR", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:radar-lab--radar_camera_mot", "kind": "repo", "label": "radar-lab/Radar_Camera_MOT (28\u2605) \u2014 Code for our paper: Radar-Camera Fused Multi-Object Tracking: Online Calibration and Common Feature", "url": "https://github.com/radar-lab/Radar_Camera_MOT", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:ramchendooran--unscented-kalman-filter-multiple-object-tracking", "kind": "repo", "label": "ramchendooran/Unscented-Kalman-Filter-Multiple-Object-Tracking (5\u2605) \u2014 Tracking of cars on a highway by using an unscented kalman filter to fuse LIDAR and RADAR data", "url": "https://github.com/ramchendooran/Unscented-Kalman-Filter-Multiple-Object-Tracking", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:santimontiel--lira-mot", "kind": "repo", "label": "santimontiel/lira-mot (6\u2605) \u2014 \ud83d\ude98 Code of my Bachelor's Thesis \"Multi Object-Tracking system based on LiDAR and RADAR for Intelligent Vehicles applications\".", "url": "https://github.com/santimontiel/lira-mot", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:dinggh0817--4d_radar_mot", "kind": "repo", "label": "dinggh0817/4D_Radar_MOT (21\u2605) \u2014 The code for reproducing experiment results in the conference paper \"Which Framework is Suitable for Online 3D Multi-Object Tracking for Autonomous Driving with Automotive 4D Imaging Radar?\" in 35th I", "url": "https://github.com/dinggh0817/4D_Radar_MOT", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:madeit07--radtrack", "kind": "repo", "label": "madeit07/RADTrack (8\u2605) \u2014 Dataset for Range-Azimuth-Doppler Based Radar Multi-Object Tracking", "url": "https://github.com/madeit07/RADTrack", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:andreimoraru123--needforscenes", "kind": "repo", "label": "AndreiMoraru123/NeedForScenes (5\u2605) \u2014 Multi Object Tracking Sensor Fusion 3D Interactive Simulation/Game in PCL", "url": "https://github.com/AndreiMoraru123/NeedForScenes", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:nsenel--sensordatafusion", "kind": "repo", "label": "nsenel/SensorDataFusion (3\u2605) \u2014 Multi object tracker sensors(Camera, LiDAR, Radar)", "url": "https://github.com/nsenel/SensorDataFusion", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:jie311--lidar-radar-mot", "kind": "repo", "label": "jie311/LiDAR-Radar-MOT (2\u2605) \u2014 \ud83d\ude98 Code of my Bachelor's Degree Thesis \"Multi Object-Tracking system based on LiDAR and RADAR for Intelligent Vehicles applications\" developed at RobeSafe Research Group (University of Alcal\u00e1) under th", "url": "https://github.com/jie311/LiDAR-Radar-MOT", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:steve-p99--radar-console-display-simulator", "kind": "repo", "label": "Steve-p99/Radar-Console-Display-Simulator (2\u2605) \u2014 Radar Console Display Simulator for Multi Object Tracking Using Qt - IDE", "url": "https://github.com/Steve-p99/Radar-Console-Display-Simulator", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:vaiy108--multi-object-radar-tracking", "kind": "repo", "label": "Vaiy108/multi-object-radar-tracking (0\u2605) \u2014 Industry-style radar tracking project", "url": "https://github.com/Vaiy108/multi-object-radar-tracking", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:bingxue-xu--radarmot", "kind": "repo", "label": "bingxue-xu/RadarMOT (0\u2605) \u2014 [ICRA'26 workshop] RadarMOT: Radar-Informed 3D Multi-Object Tracking under Adverse Conditions", "url": "https://github.com/bingxue-xu/RadarMOT", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:vaiy108--radar-camera-fusion", "kind": "repo", "label": "Vaiy108/radar-camera-fusion (1\u2605) \u2014 A real-time C++ system for multi-object tracking and sensor fusion using camera-based motion detections", "url": "https://github.com/Vaiy108/radar-camera-fusion", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:smanohar201--automotive_object_tracking", "kind": "repo", "label": "sManohar201/automotive_object_tracking (0\u2605) \u2014 Production-grade multi-object tracking for autonomous driving \u2014 LiDAR, radar, and camera fusion in C++17 on ROS2", "url": "https://github.com/sManohar201/automotive_object_tracking", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:airou-lab--velacar3dmot", "kind": "repo", "label": "airou-lab/VelACAR3DMOT (1\u2605) \u2014 Camera-Radar 3D Multi-Object Tracking pipeline inspired by AB3DMOT, made for the nuScenes dataset. Using radar velocity to improve on existing method, using CRN and Radiant as Detection backbones.", "url": "https://github.com/airou-lab/VelACAR3DMOT", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:akajiaku11--carbon-footprint-analysis-and-emission-forecasting", "kind": "repo", "label": "Akajiaku11/Carbon-Footprint-Analysis-and-Emission-Forecasting (61\u2605) \u2014 This project is a Python-based tool for analyzing carbon emissions and forecasting future trends. It uses synthetic data to simulate historical emissions and applies ARIMA (a time series model) and Li", "url": "https://github.com/Akajiaku11/Carbon-Footprint-Analysis-and-Emission-Forecasting", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:beckybams--carbon-footprint-estimation-tool", "kind": "repo", "label": "Beckybams/Carbon-Footprint-Estimation-Tool (25\u2605) \u2014 The **Carbon-Footprint-Estimation-Tool** uses synthetic data and machine learning to estimate carbon emissions from activities such as transportation, electricity use, fuel consumption, and waste gene", "url": "https://github.com/Beckybams/Carbon-Footprint-Estimation-Tool", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:nefagi-01--cumulator", "kind": "repo", "label": "nefagi-01/cumulator (0\u2605) \u2014 A tool to quantify and report the carbon footprint of machine learning computations and communication", "url": "https://github.com/nefagi-01/cumulator", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:gauravswarnakar--carbon-footprint-predictor", "kind": "repo", "label": "gauravswarnakar/carbon-footprint-predictor (1\u2605) \u2014 AI-based carbon footprint calculator using Machine Learning", "url": "https://github.com/gauravswarnakar/carbon-footprint-predictor", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:harshitadd--dp-carbon-footprint", "kind": "repo", "label": "harshitadd/DP-Carbon-Footprint (8\u2605) \u2014 Analysing the carbon footprint of Differential privacy guarantees on Vanilla BERT ( modelled for news classification ), MNIST and the Cartpole Problem using Opacus. [ Accepted to appear at  ICML 2021 ", "url": "https://github.com/harshitadd/DP-Carbon-Footprint", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:curiosit--phd-predictingcarbonfootprintofbuildings", "kind": "repo", "label": "Curiosit/PhD-PredictingCarbonFootprintOfBuildings (7\u2605) \u2014 Machine Learning (CNN) for carbon footprint prediction in early stages of architectural design", "url": "https://github.com/Curiosit/PhD-PredictingCarbonFootprintOfBuildings", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:nelvinebi--carbon-footprint-estimator-for-urban-households", "kind": "repo", "label": "Nelvinebi/Carbon-Footprint-Estimator-for-Urban-Households (11\u2605) \u2014 This project builds a machine learning model to estimate urban household carbon footprints using synthetic data. It analyzes energy use, transport, diet, and lifestyle factors to predict annual CO\u2082 em", "url": "https://github.com/Nelvinebi/Carbon-Footprint-Estimator-for-Urban-Households", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:airi-institute--eco4cast", "kind": "repo", "label": "AIRI-Institute/eco4cast (16\u2605) \u2014 eco4cast library aims to reduce carbon footprint of machine learning models with predictive cloud computing scheduling", "url": "https://github.com/AIRI-Institute/eco4cast", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:avelero--avelero_hydrocarbon", "kind": "repo", "label": "Avelero/Avelero_HydroCarbon (4\u2605) \u2014 Lightweight model for automated carbon and water footprint estimation using machine learning", "url": "https://github.com/Avelero/Avelero_HydroCarbon", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:zero010010--usin-ml-to-predict-carbon-footprint-", "kind": "repo", "label": "zero010010/Usin-ML-to-predict-Carbon-FootPrint- (2\u2605) \u2014 Using Machine Learning to Predict Carbon Foot Print ", "url": "https://github.com/zero010010/Usin-ML-to-predict-Carbon-FootPrint-", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:lokenderpratap8-sketch--carbon-footprint-ml", "kind": "repo", "label": "lokenderpratap8-sketch/Carbon-Footprint-ML (2\u2605) \u2014 AI-powered Carbon Footprint Prediction and Recommendation System using Machine Learning, Flask, and Scikit-Learn.", "url": "https://github.com/lokenderpratap8-sketch/Carbon-Footprint-ML", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:atharvchaudhari2907-code--carbonquest", "kind": "repo", "label": "atharvchaudhari2907-code/CarbonQuest (0\u2605) \u2014 AI Sustainability Assistant is a smart web platform that analyzes lifestyle data to calculate carbon footprint and suggests personalized eco-friendly actions. The system combines web development, data", "url": "https://github.com/atharvchaudhari2907-code/CarbonQuest", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:ksm26--carbon-aware-computing-for-genai-developers", "kind": "repo", "label": "ksm26/Carbon-Aware-Computing-for-GenAI-Developers (9\u2605) \u2014 Learn to optimize machine learning tasks for environmental sustainability. Discover how to use real-time electricity data and low-carbon energy sources for model training and inference, reducing the c", "url": "https://github.com/ksm26/Carbon-Aware-Computing-for-GenAI-Developers", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:gurpreet0022--carbonfootprint", "kind": "repo", "label": "Gurpreet0022/CarbonFootprint (0\u2605) \u2014 Machine learning based carbon footprint predictor webapp", "url": "https://github.com/Gurpreet0022/CarbonFootprint", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:mayowa1012--carbon-footprint-prediction", "kind": "repo", "label": "Mayowa1012/Carbon-Footprint-Prediction (2\u2605) \u2014 This Project analyses the carbon footprint of the U.S. commercial sector using three machine learning models. A combination of energy consumption data and carbon dioxide emission data was used to achi", "url": "https://github.com/Mayowa1012/Carbon-Footprint-Prediction", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:tanayshandilya--carbon-footprint-monitoring-system", "kind": "repo", "label": "tanayshandilya/Carbon-Footprint-Monitoring-System (2\u2605) \u2014 The project aims to provide a statistical data of carbon emission from vehicles, and using the data science tools and machine learning to provide future usage limitations of vehicles to reduce carbon ", "url": "https://github.com/tanayshandilya/Carbon-Footprint-Monitoring-System", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:jellybeansxo--carbonfootprintemission", "kind": "repo", "label": "JellyBeansXO/CarbonFootprintEmission (0\u2605) \u2014 Machine Learning model for tracking carbon footprint emission", "url": "https://github.com/JellyBeansXO/CarbonFootprintEmission", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:mounicauddagiri--carbon_footprints", "kind": "repo", "label": "mounicauddagiri/Carbon_footprints (0\u2605) \u2014 machine learning model for Carbon footprints", "url": "https://github.com/mounicauddagiri/Carbon_footprints", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:mazid2003--carbon-footprint-estimator-using-machine-learning", "kind": "repo", "label": "Mazid2003/Carbon-Footprint-Estimator-using-Machine-Learning (1\u2605) \u2014 This project aims to predict the carbon footprint of various activities and evaluate the prediction accuracy using the R\u00b2 score. The project involves a data processing pipeline where actual carbon foo", "url": "https://github.com/Mazid2003/Carbon-Footprint-Estimator-using-Machine-Learning", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:kwabena-a--carbon-footprint", "kind": "repo", "label": "Kwabena-A/Carbon-Footprint (0\u2605) \u2014 Predicting carbon footprint based on the best preforming machine learning model", "url": "https://github.com/Kwabena-A/Carbon-Footprint", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:yugh88--carbon-footprint-calculator_app", "kind": "repo", "label": "yugh88/Carbon-Footprint-Calculator_App (0\u2605) \u2014 Blockchain and Machine Learning Based Carbon Footprint Calculator", "url": "https://github.com/yugh88/Carbon-Footprint-Calculator_App", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:dakshesh-1293--carbon-footprint-predictor", "kind": "repo", "label": "dakshesh-1293/carbon-footprint-predictor (1\u2605) \u2014 ML-based personal carbon footprint predictor using Streamlit and machine learning.", "url": "https://github.com/dakshesh-1293/carbon-footprint-predictor", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:vamshiiyer--ai-carbon-footprint-sustainability-advisor", "kind": "repo", "label": "vamshiiyer/ai-carbon-footprint-sustainability-advisor (0\u2605) \u2014 AI-based sustainability advisor using machine learning", "url": "https://github.com/vamshiiyer/ai-carbon-footprint-sustainability-advisor", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:krishiv-dev07--ecofootprint-analyzer", "kind": "repo", "label": "krishiv-dev07/EcoFootprint-Analyzer (0\u2605) \u2014 Machine Learning and GenAI based Carbon Footprint Estimation System", "url": "https://github.com/krishiv-dev07/EcoFootprint-Analyzer", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:guan404ming--carbon-footprint-reporting", "kind": "repo", "label": "guan404ming/carbon-footprint-reporting (0\u2605) \u2014 [ICML 2026] Position: Carbon Footprint Reporting Should Be Routine in Machine Learning Research", "url": "https://github.com/guan404ming/carbon-footprint-reporting", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:aarti-paridwal--ai_carbon_footprint_predictor", "kind": "repo", "label": "aarti-paridwal/AI_Carbon_Footprint_Predictor (0\u2605) \u2014 Machine Learning model to predict Carbon Footprint using Linear Regression.", "url": "https://github.com/aarti-paridwal/AI_Carbon_Footprint_Predictor", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:viivianreine--carbon-footprint-calculator-using-advanced-machine-learning-cnn-", "kind": "repo", "label": "ViivianREINE/Carbon-Footprint-Calculator-using-Advanced-Machine-Learning-CNN- (0\u2605) \u2014 \ud83c\udf0d An AI-powered Carbon Footprint Calculator built with Python, TensorFlow (CNNs), and Streamlit. Delivers real-time emission predictions, visual insights, and country-wise comparisons from user lifest", "url": "https://github.com/ViivianREINE/Carbon-Footprint-Calculator-using-Advanced-Machine-Learning-CNN-", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:ridhis110--carbon-footprint-fashion-ml", "kind": "repo", "label": "ridhis110/carbon-footprint-fashion-ml (0\u2605) \u2014  Estimate carbon footprint in the fashion supply chain using machine learning", "url": "https://github.com/ridhis110/carbon-footprint-fashion-ml", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:elizavetabugaeva--emissions_estimator", "kind": "repo", "label": "ElizavetaBugaeva/Emissions_estimator (0\u2605) \u2014 Corporate Carbon Footprint Estimations using Machine Learning ", "url": "https://github.com/ElizavetaBugaeva/Emissions_estimator", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:cyrilbaah--carboncue", "kind": "repo", "label": "CyrilBaah/carboncue (1\u2605) \u2014 Carbon-aware computing tools for sustainable software development: Python SDK, CLI, and GitHub Action with multi-cloud support and real-time carbon intensity data.", "url": "https://github.com/CyrilBaah/carboncue", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:saintslab--carbontracker", "kind": "repo", "label": "saintslab/carbontracker (479\u2605) \u2014 Track and predict the energy consumption and carbon footprint of training deep learning models.", "url": "https://github.com/saintslab/carbontracker", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:mlco2--codecarbon", "kind": "repo", "label": "mlco2/codecarbon (1877\u2605) \u2014 Track emissions from Compute and recommend ways to reduce their impact on the environment.", "url": "https://github.com/mlco2/codecarbon", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:juanjoowendler--co-emissions-tracking-for-ollama-ai-using-codecarbon", "kind": "repo", "label": "juanjoowendler/CO-Emissions-Tracking-for-Ollama-AI-using-CodeCarbon (2\u2605) \u2014 Python tool that measures energy consumption and CO\u2082 emissions generated by the execution of code generated with artificial intelligence.", "url": "https://github.com/juanjoowendler/CO-Emissions-Tracking-for-Ollama-AI-using-CodeCarbon", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:alexhroom--pytest-codecarbon", "kind": "repo", "label": "alexhroom/pytest-codecarbon (0\u2605) \u2014 Pytest plugin for tracking carbon emissions", "url": "https://github.com/alexhroom/pytest-codecarbon", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:florisvdf--ai-environmental-impact", "kind": "repo", "label": "florisvdf/ai-environmental-impact (6\u2605) \u2014 Mini workshop to provide a peak of what\u2019s happening under the hood of models currently at the frontier of the AI revolution, and about how we can track the emissions of our own code.", "url": "https://github.com/florisvdf/ai-environmental-impact", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:coluciana--codecarbon.jl", "kind": "repo", "label": "COLuciana/CodeCarbon.jl (0\u2605) \u2014 Unofficial Julia wrapper of the Python library codecarbon for tracking emissions from compute.", "url": "https://github.com/COLuciana/CodeCarbon.jl", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:gaurav-van--exploring-codecarbon", "kind": "repo", "label": "Gaurav-Van/Exploring-CodeCarbon (0\u2605) \u2014 Diving into the world of Tracking CO2 Emissions from our software or code.  Code Carbon is a lightweight open-source Python Library that lets you track the Co2 emissions produced by running code. ", "url": "https://github.com/Gaurav-Van/Exploring-CodeCarbon", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:managerbanneaaya--carbon_tracker", "kind": "repo", "label": "managerbanneaaya/Carbon_Tracker (1\u2605) \u2014 CodeCarbon is a lightweight Python library that tracks the energy consumption and carbon emissions of a Python program.", "url": "https://github.com/managerbanneaaya/Carbon_Tracker", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:aswathy-k--sparsegpt-int8-quantization-codecarbon", "kind": "repo", "label": "Aswathy-K/SparseGPT-INT8-Quantization-CodeCarbon (0\u2605) \u2014 This notebook implements:  SparseGPT (Frantar & Alistarh, 2023) \u2014 Hessian-guided one-shot pruning INT8 Quantization \u2014 post-pruning absmax symmetric quantization CodeCarbon \u2014 CO\u2082 emission tracking for ", "url": "https://github.com/Aswathy-K/SparseGPT-INT8-Quantization-CodeCarbon", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:albertovalerio--sustainability-of-recsys", "kind": "repo", "label": "albertovalerio/sustainability-of-recsys (0\u2605) \u2014 The system tracks the emissions of a given recommendation algorithm on a given dataset.", "url": "https://github.com/albertovalerio/sustainability-of-recsys", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:ajita07--carbon-efficient-chatbot", "kind": "repo", "label": "ajita07/Carbon-Efficient-Chatbot (0\u2605) \u2014 \ud83c\udf31 A Flask-based chatbot powered by Groq API with real-time carbon emission tracking using CodeCarbon. Deployed on Render.", "url": "https://github.com/ajita07/Carbon-Efficient-Chatbot", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:sukanya-lahkar--green-ml-experiments", "kind": "repo", "label": "sukanya-lahkar/green-ml-experiments (0\u2605) \u2014 A reproducible project comparing CodeCarbon and CarbonTracker on Keras ML workloads. Tracks energy consumption, carbon emissions, and model performance across computer vision, NLP, structured, time se", "url": "https://github.com/sukanya-lahkar/green-ml-experiments", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:izzulroslan--greenmodel-ai-carbon-emission-tracker", "kind": "repo", "label": "izzulroslan/GreenModel-AI-Carbon-Emission-Tracker (0\u2605) \u2014 GreenModel: AI Carbon Emission Tracker is a user-friendly Streamlit platform that helps users train machine learning models while tracking their carbon emissions in real time. It promotes sustainable ", "url": "https://github.com/izzulroslan/GreenModel-AI-Carbon-Emission-Tracker", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:riddhiijoshi--e-commerce-green-software-development", "kind": "repo", "label": "riddhiijoshi/e-commerce-Green-Software-Development (0\u2605) \u2014 The application integrates the CodeCarbon library to track the carbon emissions associated with the online shopping activities. This enables users to gain insights into the environmental impact of the", "url": "https://github.com/riddhiijoshi/e-commerce-Green-Software-Development", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:manojs15--carbon-footprint", "kind": "repo", "label": "manojs15/carbon-footprint (0\u2605) \u2014 Calculate and track your project's carbon footprint on GitHub using tools like \"GHG\" or \"CodeCarbon\" to estimate greenhouse gas emissions from code contributions, promoting environmental awareness and", "url": "https://github.com/manojs15/carbon-footprint", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:bonjourdave--ml-pipeline-project", "kind": "repo", "label": "bonjourdave/ml-pipeline-project (0\u2605) \u2014 This project is to design end-to-end MLOps pipeline predicting CrossFit athlete total lift using Airflow for orchestration, MLFlow for experiment tracking, Feast for feature management, and CodeCarbon", "url": "https://github.com/bonjourdave/ml-pipeline-project", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:rohitsah13--eco-ops-green-computing-analytics-", "kind": "repo", "label": "RohitSah13/Eco-Ops-Green-Computing-Analytics- (0\u2605) \u2014 Eco-Ops is a carbon-aware ML framework that tracks energy usage and CO\u2082 emissions during model training. It uses CodeCarbon and Streamlit to provide benchmarking, visualization, and sustainability ana", "url": "https://github.com/RohitSah13/Eco-Ops-Green-Computing-Analytics-", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:051188-rk--greenml", "kind": "repo", "label": "051188-rk/GreenML (1\u2605) \u2014 GreenML Dashboard is a sustainable AI project that predicts household appliance energy consumption using machine learning and environmental sensor data. It integrates CodeCarbon to track CO\u2082 emissions", "url": "https://github.com/051188-rk/GreenML", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:rohan-excelr--automl-green-model-selector", "kind": "repo", "label": "Rohan-Excelr/AutoML-Green-Model-Selector (0\u2605) \u2014 EcoML is a green AutoML pipeline that selects optimal ML models using Optuna and tracks carbon emissions via CodeCarbon. It balances model performance with environmental impact. Final model: Logistic ", "url": "https://github.com/Rohan-Excelr/AutoML-Green-Model-Selector", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:vanshini04--ai-for-the-ai", "kind": "repo", "label": "Vanshini04/AI-for-the-AI (0\u2605) \u2014  AI-powered dashboard that tracks and predicts carbon emissions from computing tasks. Built with Streamlit, Scikit-learn, and CodeCarbon, it suggests eco-friendly schedules using real-time grid data. ", "url": "https://github.com/Vanshini04/AI-for-the-AI", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:sb-ai-lab--eco2ai", "kind": "repo", "label": "sb-ai-lab/Eco2AI (276\u2605) \u2014 eco2AI is a python library which accumulates statistics about power consumption and CO2 emission during running code. ", "url": "https://github.com/sb-ai-lab/Eco2AI", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:vladimir-laz--eco2ai_prototype", "kind": "repo", "label": "vladimir-laz/eco2ai_prototype (2\u2605)", "url": "https://github.com/vladimir-laz/eco2ai_prototype", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:justlab-ai--eco2ai-backend", "kind": "repo", "label": "justlab-ai/eco2ai-backend (0\u2605) \u2014 eco2ai backend", "url": "https://github.com/justlab-ai/eco2ai-backend", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:andvarfolomeev--eco2ai-playground", "kind": "repo", "label": "andvarfolomeev/Eco2AI-playground (0\u2605) \u2014 Server side application to receive and storage data of Eco2ai library", "url": "https://github.com/andvarfolomeev/Eco2AI-playground", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:fijishi-enterprises--eco2ai-power-comsumption", "kind": "repo", "label": "Fijishi-Enterprises/ECO2AI-Power-Comsumption (1\u2605)", "url": "https://github.com/Fijishi-Enterprises/ECO2AI-Power-Comsumption", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:pikvic--fefu-eco2ai", "kind": "repo", "label": "pikvic/fefu-eco2ai (1\u2605)", "url": "https://github.com/pikvic/fefu-eco2ai", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:danieleschmidt--hf-eco2ai-plugin", "kind": "repo", "label": "danieleschmidt/hf-eco2ai-plugin (1\u2605) \u2014 A Hugging Face Trainer callback that logs CO\u2082, kWh, and regional grid intensity for every epoch. Built on Eco2AI's strong energy tracking.", "url": "https://github.com/danieleschmidt/hf-eco2ai-plugin", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:yinuoyang327--eco2ai_dashboard", "kind": "repo", "label": "YinuoYang327/Eco2AI_dashboard (0\u2605)", "url": "https://github.com/YinuoYang327/Eco2AI_dashboard", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:kp-156--eco2ai-implementation-minor-project-", "kind": "repo", "label": "kp-156/eco2ai-implementation-minor-project- (0\u2605)", "url": "https://github.com/kp-156/eco2ai-implementation-minor-project-", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:breakend--experiment-impact-tracker", "kind": "repo", "label": "Breakend/experiment-impact-tracker (293\u2605)", "url": "https://github.com/Breakend/experiment-impact-tracker", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:tomlouismurphy--velocitytracker", "kind": "repo", "label": "tomlouismurphy/velocityTracker (0\u2605) \u2014 Experiment to check impact of fastball velocity on MLB starting pitchers throughout their games", "url": "https://github.com/tomlouismurphy/velocityTracker", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:aqui001--web-dev-journey-from-zero-to-impact-", "kind": "repo", "label": "Aqui001/Web-Dev-Journey-From-Zero-to-Impact- (2\u2605) \u2014 Hi there! \ud83d\udc4b I'm Aquilo-Dominic, diving headfirst into web development with loads of excitement and hope to make a difference. This repo tracks my learning journey \u2013 experiments, projects, wins, and le", "url": "https://github.com/Aqui001/Web-Dev-Journey-From-Zero-to-Impact-", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:2236117534--experimental-data-sharing-", "kind": "repo", "label": "2236117534/Experimental-data-sharing- (0\u2605) \u2014 The data supports the study \"A Comparative Investigation into the Impact of Directionality on Human Translation and Post-Editing Effort: An Eye Tracking and Keylogging Experiment involving Student Tra", "url": "https://github.com/2236117534/Experimental-data-sharing-", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:2236117534--analysis-code-and-experimental-materials", "kind": "repo", "label": "2236117534/Analysis-Code-and-Experimental-Materials (0\u2605) \u2014 The data supports the study : \"A Comparative Investigation into the Impact of Directionality on Human Translation and Post-Editing Effort: An Eye Tracking and Keylogging Experiment involving Student T", "url": "https://github.com/2236117534/Analysis-Code-and-Experimental-Materials", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:moeghashim--10x-shot", "kind": "repo", "label": "moeghashim/10x-shot (0\u2605) \u2014 Tracking the real-world impact of AI on productivity across live experiments, tools, and systems behind 10claws.", "url": "https://github.com/moeghashim/10x-shot", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:varsha199--vanguard-digital-redesign-impact-study", "kind": "repo", "label": "varsha199/Vanguard-Digital-Redesign-Impact-Study (0\u2605) \u2014 Analysis of Vanguard\u2019s A/B test measuring the impact of a redesigned digital interface with in-context prompts on client process completion rates. Includes data cleaning, EDA, KPI tracking, hypothesis", "url": "https://github.com/varsha199/Vanguard-Digital-Redesign-Impact-Study", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:cagriertem--eye-tracking-experiment", "kind": "repo", "label": "cagriertem/eye-tracking-experiment (0\u2605) \u2014 By conducting an eye-tracking experiment, we test the impact of Gestalt properties in photographic arts. Heat maps that were derived via raw eye-tracking data were used to predict the categories of th", "url": "https://github.com/cagriertem/eye-tracking-experiment", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:surfab--product-discovery-canvas", "kind": "repo", "label": "Surfab/product-discovery-canvas (1\u2605) \u2014 Interactive Product Discovery Canvas with Impact/Effort Matrix, Assumption Validation, Experiment Tracking and Visual Traceability. Offline-first. Multilingual.", "url": "https://github.com/Surfab/product-discovery-canvas", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:ronithjuluri18--causal-impact-of-promotions-on-customer-retention", "kind": "repo", "label": "ronithjuluri18/Causal-Impact-of-Promotions-on-Customer-Retention (0\u2605) \u2014 Causal inference study estimating the effect of promotional campaigns on customer retention using Propensity Score Matching and Double ML (EconML). Built with Python, PySpark, scikit-learn, and MLflow", "url": "https://github.com/ronithjuluri18/Causal-Impact-of-Promotions-on-Customer-Retention", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:rayyan-ridwan--greengrad", "kind": "repo", "label": "rayyan-ridwan/GreenGrad (0\u2605) \u2014 An energy-efficient training framework that minimizes GPU and power usage during deep learning training. Visualizes resource consumption and promotes sustainable AI development.", "url": "https://github.com/rayyan-ridwan/GreenGrad", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:karankadhir86--green-ai-optimization-techniques-and-performance-energy-trade-off-studies.", "kind": "repo", "label": "karankadhir86/Green-AI-optimization-techniques-and-performance-energy-trade-off-studies. (0\u2605) \u2014 This dataset contains 100,000 synthetic samples for analyzing energy-efficient AI models. It includes model type, dataset, training parameters, accuracy, energy consumption, and carbon emissions. The ", "url": "https://github.com/karankadhir86/Green-AI-optimization-techniques-and-performance-energy-trade-off-studies.", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:zwonziss--green-recipes", "kind": "repo", "label": "zwonziss/green-recipes (1\u2605) \u2014 A collection of runnable recipes for efficient AI training \u2014 measure energy, VRAM, and speed tradeoffs of different optimization techniques. Learn what actually saves compute without sacrificing quali", "url": "https://github.com/zwonziss/green-recipes", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:hewwee--ai-in-manufacturing", "kind": "repo", "label": "hewwee/ai-in-manufacturing (0\u2605) \u2014 Developing a Green AI Framework for manufacturing, supported by a sustainable action layer that guides energy-efficient model training, carbon-aware workload scheduling, and sustainable data-handling ", "url": "https://github.com/hewwee/ai-in-manufacturing", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:satyanshu404--ai-carbon-footprint-manager", "kind": "repo", "label": "satyanshu404/AI-carbon-footprint-manager (4\u2605) \u2014 This Hitachi AI research project aims to design an automated agentic application for carbon footprint management, handling tasks like data model extraction, footprint calculation, and decarbonization ", "url": "https://github.com/satyanshu404/AI-carbon-footprint-manager", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:uygarkurt--llm-carbon-footprint", "kind": "repo", "label": "uygarkurt/LLM-Carbon-Footprint (2\u2605)", "url": "https://github.com/uygarkurt/LLM-Carbon-Footprint", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:greenscale-ai--genai-carbon-footprint", "kind": "repo", "label": "greenscale-ai/genai-carbon-footprint (3\u2605) \u2014 GenAI Carbon Footprint is a tool to estimate energy use (kWh) and carbon emissions (gCO2eq) from LLM usage", "url": "https://github.com/greenscale-ai/genai-carbon-footprint", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:rebeccahihi--llm", "kind": "repo", "label": "rebeccahihi/LLM (0\u2605) \u2014 LLM carbon footprint calculator", "url": "https://github.com/rebeccahihi/LLM", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:maymiled--carbon-footprint-llm", "kind": "repo", "label": "maymiled/carbon-footprint-llm (0\u2605)", "url": "https://github.com/maymiled/carbon-footprint-llm", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:talyke--javallmcarbonfootprint", "kind": "repo", "label": "talyke/JavaLLMCarbonFootPrint (0\u2605) \u2014 java calculator OOP carbon footprint calculator", "url": "https://github.com/talyke/JavaLLMCarbonFootPrint", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:dhiksha-713--llm-carbon-footprint-research-portal", "kind": "repo", "label": "dhiksha-713/llm-carbon-footprint-research-portal (0\u2605) \u2014 Carbon footprint measurement and evaluation of Large Language Models based on RAG (Green AI research project)", "url": "https://github.com/dhiksha-713/llm-carbon-footprint-research-portal", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:pyladiesams--optimize-ai-prompts-jun2025", "kind": "repo", "label": "pyladiesams/optimize-ai-prompts-jun2025 (2\u2605) \u2014 Optimize AI prompts to reduce verbosity and carbon footprint with ScaleDown", "url": "https://github.com/pyladiesams/optimize-ai-prompts-jun2025", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:lueasf--hack-loria", "kind": "repo", "label": "lueasf/Hack-LORIA (0\u2605) \u2014 Hackathon about LLM's carbon footprint", "url": "https://github.com/lueasf/Hack-LORIA", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:jmdevita--carbon-proxy", "kind": "repo", "label": "jmdevita/carbon-proxy (1\u2605) \u2014 Carbon footprint tracking for self-hosted LLMs.", "url": "https://github.com/jmdevita/carbon-proxy", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:vivekaradshan--llm-inference-carbon-tracker", "kind": "repo", "label": "vivekaradshan/LLM-inference-carbon-tracker (0\u2605) \u2014 Repo is to track carbon footprint during LLM inference", "url": "https://github.com/vivekaradshan/LLM-inference-carbon-tracker", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:boettiger-lab--nrp-carbon-api", "kind": "repo", "label": "boettiger-lab/nrp-carbon-api (0\u2605) \u2014 Monitoring carbon footprint of LLMs on NRP", "url": "https://github.com/boettiger-lab/nrp-carbon-api", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:divyansh0208--carbon-footprint-awareness", "kind": "repo", "label": "Divyansh0208/Carbon-Footprint-Awareness (0\u2605) \u2014 Carbon Footprint Education Platform built with Django. Understand \u2192 Track \u2192 Reduce your emissions. Powered by NVIDIA NIM (LLM) for personalized AI insights, recommendations, and Q&A.", "url": "https://github.com/Divyansh0208/Carbon-Footprint-Awareness", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:prasun-sitaula--carbonwise", "kind": "repo", "label": "PRASUN-SITAULA/carbonWise (1\u2605) \u2014  A LLM powered web app that calculates the carbon footprint of a family and gives advisory to reduce the carbon footprint.", "url": "https://github.com/PRASUN-SITAULA/carbonWise", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:wyl2607--llm-carbon-index", "kind": "repo", "label": "wyl2607/llm-carbon-index (0\u2605) \u2014 Estimates the CO2 footprint of OpenRouter-visible LLM inference \u2014 estimates with uncertainty ranges, not measurements.", "url": "https://github.com/wyl2607/llm-carbon-index", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:bigscience-workshop--carbon-footprint", "kind": "repo", "label": "bigscience-workshop/carbon-footprint (13\u2605) \u2014 A repository for `codecarbon` logs.", "url": "https://github.com/bigscience-workshop/carbon-footprint", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:conda-forge--codecarbon-feedstock", "kind": "repo", "label": "conda-forge/codecarbon-feedstock (2\u2605) \u2014 A conda-smithy repository for codecarbon.", "url": "https://github.com/conda-forge/codecarbon-feedstock", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:mlco2--vscode-extension-codecarbon", "kind": "repo", "label": "mlco2/vscode-extension-codecarbon (4\u2605) \u2014 VS Code extension for CodeCarbon", "url": "https://github.com/mlco2/vscode-extension-codecarbon", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:mlco2--codecarbon-static-website", "kind": "repo", "label": "mlco2/codecarbon-static-website (3\u2605) \u2014 Static website for CodeCarbon.io", "url": "https://github.com/mlco2/codecarbon-static-website", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:vienneraphael--scalene-codecarbon-workshop", "kind": "repo", "label": "vienneraphael/scalene-codecarbon-workshop (1\u2605)", "url": "https://github.com/vienneraphael/scalene-codecarbon-workshop", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:fnndsc--pypx-repack-codecarbon-datalad", "kind": "repo", "label": "FNNDSC/pypx-repack-codecarbon-datalad (6\u2605) \u2014 Comparing energy efficiency of a Rust rewrite of a program for DICOM management.", "url": "https://github.com/FNNDSC/pypx-repack-codecarbon-datalad", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:sabrinamuh--projectcodecarbon-javascript-program", "kind": "repo", "label": "SabrinaMuh/ProjectCodecarbon-Javascript-Program (3\u2605)", "url": "https://github.com/SabrinaMuh/ProjectCodecarbon-Javascript-Program", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:greatdevaks--iiit-codecarbon", "kind": "repo", "label": "greatdevaks/iiit-codecarbon (2\u2605) \u2014 Repository containing the slides and resources used for delivering talk titled \"Towards Green AI: Tracking and Curtailing Carbon Footprint of AI Python Code with CodeCarbon\"at IIIT Kottayam 2022", "url": "https://github.com/greatdevaks/iiit-codecarbon", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:raphischer--ai-energy-validation", "kind": "repo", "label": "raphischer/ai-energy-validation (4\u2605) \u2014 Ground-Truthing AI Energy Consumption: Validating CodeCarbon Against External Measurements", "url": "https://github.com/raphischer/ai-energy-validation", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:up1--demo-codecarbon", "kind": "repo", "label": "up1/demo-codecarbon (2\u2605)", "url": "https://github.com/up1/demo-codecarbon", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:blessinvarkey--ecocoding", "kind": "repo", "label": "blessinvarkey/ecocoding (4\u2605) \u2014 Energy Consumption of various Machine Learning and Deep Learning Models using codecarbon", "url": "https://github.com/blessinvarkey/ecocoding", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:zkan--hello-codecarbon", "kind": "repo", "label": "zkan/hello-codecarbon (0\u2605) \u2014 Hello, CodeCarbon!", "url": "https://github.com/zkan/hello-codecarbon", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:koosuyeon--codecarbonforjetson", "kind": "repo", "label": "KooSuYeon/codecarbonForJetson (1\u2605)", "url": "https://github.com/KooSuYeon/codecarbonForJetson", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:mlcommons--power-dev", "kind": "repo", "label": "mlcommons/power-dev (28\u2605) \u2014 Dev repo for power measurement for the MLPerf\u2122 benchmarks", "url": "https://github.com/mlcommons/power-dev", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:helmholtz-ai-energy--perun", "kind": "repo", "label": "Helmholtz-AI-Energy/perun (92\u2605) \u2014 Perun is a Python package that measures the energy consumption of your applications.", "url": "https://github.com/Helmholtz-AI-Energy/perun", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:powerapi-ng--pyjoules", "kind": "repo", "label": "powerapi-ng/pyJoules (94\u2605) \u2014 A Python library to capture the energy consumption of code snippets", "url": "https://github.com/powerapi-ng/pyJoules", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:amaurytiss--tf_energy_consumption", "kind": "repo", "label": "Amaurytiss/tf_energy_consumption (0\u2605) \u2014 Small script with pyJoules and tensorflow to evaluate energy consumption of a device", "url": "https://github.com/Amaurytiss/tf_energy_consumption", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:raghavsingraur--energy-_efficient-_systems", "kind": "repo", "label": "raghavsingraur/Energy-_Efficient-_Systems (0\u2605) \u2014 The development and features of a Flask-based web application designed for testing and training purposes, integrating terminal functionality smoothly. Additionally, the application incorporates PyJo", "url": "https://github.com/raghavsingraur/Energy-_Efficient-_Systems", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:sense-gvt--fast-bev", "kind": "repo", "label": "Sense-GVT/Fast-BEV (818\u2605) \u2014 Fast-BEV: A Fast and Strong Bird\u2019s-Eye View Perception Baseline", "url": "https://github.com/Sense-GVT/Fast-BEV", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ankita-kalra--pixor", "kind": "repo", "label": "ankita-kalra/PIXOR (95\u2605) \u2014 Bird's Eye View Object Detection Algorithm for self-driving Cars", "url": "https://github.com/ankita-kalra/PIXOR", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:chaytonmin--awesome-bev-perception-multi-cameras", "kind": "repo", "label": "chaytonmin/Awesome-BEV-Perception-Multi-Cameras (1112\u2605) \u2014 Awesome papers about Multi-Camera 3D Object Detection and Segmentation in Bird's-Eye-View, such as DETR3D, BEVDet, BEVFormer, BEVDepth, UniAD", "url": "https://github.com/chaytonmin/Awesome-BEV-Perception-Multi-Cameras", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:kkk324--vehicle-distance-detection", "kind": "repo", "label": "kkk324/Vehicle-Distance-Detection (75\u2605) \u2014 Using Perspective Transform to leverage bird's eye view (BEV) to estimate distance between objects. ", "url": "https://github.com/kkk324/Vehicle-Distance-Detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:vdigpku--rcbevdet", "kind": "repo", "label": "VDIGPKU/RCBEVDet (270\u2605) \u2014 [CVPR 2024] RCBEVDet: Radar-camera Fusion in Bird\u2019s Eye View for 3D Object Detection", "url": "https://github.com/VDIGPKU/RCBEVDet", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:bharath5673--yolo_bev", "kind": "repo", "label": "bharath5673/yolo_BEV (102\u2605) \u2014 Simple and Easy simulator YOLO Object Detection with Bird's Eye View", "url": "https://github.com/bharath5673/yolo_BEV", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:uranus4ever--advanced-lane-detection", "kind": "repo", "label": "uranus4ever/Advanced-Lane-Detection (54\u2605) \u2014 Camera Calibration; Distortion Correction; Perspective transform (\"bird-eye view\"); Compute curvature and vehicle position.", "url": "https://github.com/uranus4ever/Advanced-Lane-Detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ziningwang--sparse_pooling", "kind": "repo", "label": "ZiningWang/Sparse_Pooling (57\u2605) \u2014 SHPL: Fusing Bird's Eye View LIDAR Point Cloud and Front View Camera Image for Deep Object Detection", "url": "https://github.com/ZiningWang/Sparse_Pooling", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:tteepe--tracktacular", "kind": "repo", "label": "tteepe/TrackTacular (62\u2605) \u2014 Official Code for \"Lifting Multi-View Detection and Tracking to the Bird\u2019s Eye View\"", "url": "https://github.com/tteepe/TrackTacular", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:overfitover--pixor_pytorch", "kind": "repo", "label": "overfitover/pixor_pytorch (41\u2605) \u2014 [Bird's Eye View Object Detection Algorithm for self-driving Cars]  pytorch for PIXOR", "url": "https://github.com/overfitover/pixor_pytorch", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:megvii-research--cvpr2023-unidistill", "kind": "repo", "label": "megvii-research/CVPR2023-UniDistill (119\u2605) \u2014 CVPR2023 (highlight) - UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird's-Eye View", "url": "https://github.com/megvii-research/CVPR2023-UniDistill", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:tmadl--ros-road-line-junction-extraction", "kind": "repo", "label": "tmadl/ROS-road-line-junction-extraction (34\u2605) \u2014 3D road line extraction, bird's-eye view projection, and junction detection for ROS stereo images", "url": "https://github.com/tmadl/ROS-road-line-junction-extraction", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:mengtan00--sa-bev", "kind": "repo", "label": "mengtan00/SA-BEV (82\u2605) \u2014 This is the implementation of the paper \"SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detection\" (ICCV 2023)", "url": "https://github.com/mengtan00/SA-BEV", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:zzj403--bev_robust", "kind": "repo", "label": "zzj403/BEV_Robust (32\u2605) \u2014 [CVPR 2023] Understanding the Robustness of 3D Object Detection With Bird's-Eye-View Representations in Autonomous Driving", "url": "https://github.com/zzj403/BEV_Robust", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:pierluigiferrari--ssd3dbv", "kind": "repo", "label": "pierluigiferrari/ssd3Dbv (5\u2605) \u2014 A Keras SSD model for 3D object detection in bird's eye view images", "url": "https://github.com/pierluigiferrari/ssd3Dbv", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:arcanaxion--cracked-egg-detection", "kind": "repo", "label": "arcanaxion/cracked-egg-detection (5\u2605) \u2014 Computer Vision system to detect cracked eggs from a birds-eye view image of an egg tray.", "url": "https://github.com/arcanaxion/cracked-egg-detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:norlab-ulaval--mask_bev", "kind": "repo", "label": "norlab-ulaval/mask_bev (19\u2605) \u2014 Source code for \"MaskBEV: Joint Object Detection and Footprint Completion for Bird's-eye View 3D Point Clouds\"", "url": "https://github.com/norlab-ulaval/mask_bev", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:manaliagarwal--advanced-lane-detection", "kind": "repo", "label": "Manaliagarwal/Advanced-Lane-Detection (17\u2605) \u2014 Homography based IPM. In computer vision, homography is a transformation matrix H when applied on a projective plane maps it to another plane (or image). In the case of Inverse Perspective Mapping (IP", "url": "https://github.com/Manaliagarwal/Advanced-Lane-Detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:parkerfrisk--bird-s-eye-view", "kind": "repo", "label": "parkerFrisk/Bird-s-eye-view (3\u2605) \u2014 Master thesis Bird\u00b4s-eye view with human detection", "url": "https://github.com/parkerFrisk/Bird-s-eye-view", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:cdemutiis--advanced_lanes_detection", "kind": "repo", "label": "cdemutiis/Advanced_Lanes_Detection (6\u2605) \u2014 Advanced Lanes Detection using camera calibration, gradient/colour thresholding, a bird's-eye view perspective transform, a sliding window search and quadratic polynomial fits", "url": "https://github.com/cdemutiis/Advanced_Lanes_Detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:handsomeyun--mic-bev", "kind": "repo", "label": "HandsomeYun/MIC-BEV (18\u2605) \u2014 MIC-BEV: Multi-Infrastructure Camera Bird\u2019s-Eye-View Perception Transformer for 3D Object Detection", "url": "https://github.com/HandsomeYun/MIC-BEV", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:aj-wuu--soccernetplus", "kind": "repo", "label": "AJ-Wuu/SoccerNetPlus (8\u2605) \u2014 Computer Vision on Soccer to help you understand the game, including player detection, bird-eye view transformation and movement tracking.", "url": "https://github.com/AJ-Wuu/SoccerNetPlus", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:shishir-pokhrel--bevlanedetection", "kind": "repo", "label": "Shishir-Pokhrel/BEVLaneDetection (0\u2605) \u2014 Bird Eye view transformation and lane detection in automotive", "url": "https://github.com/Shishir-Pokhrel/BEVLaneDetection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:lienghongky--cmx-hmi", "kind": "repo", "label": "lienghongky/cmx-hmi (16\u2605) \u2014 Unity 3D HMI for Lift-Splat-Blob (LSB) A real-time Human-Machine Interface (HMI) built in Unity 3D to visualize Bird's Eye View (BEV) outputs and blob detection results from the LSB vehicle detection ", "url": "https://github.com/lienghongky/cmx-hmi", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:autocompsyslab--dctnet", "kind": "repo", "label": "AutoCompSysLab/DCTNet (24\u2605) \u2014 ArXiv (2022), 'A Dual-Cycled Cross-View Transformer Network for Unified Road Layout Estimation and 3D Object Detection in the Bird's-Eye-View'", "url": "https://github.com/AutoCompSysLab/DCTNet", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:soubhikmajumdar--3d-lidar-based-birds-eye-view-object-detection-via-bevfusion", "kind": "repo", "label": "SoubhikMajumdar/3D-LiDAR-Based-Birds-Eye-View-Object-Detection-via-BEVFusion (5\u2605) \u2014 3D LiDAR Point Cloud based Bird's-Eye View (BEV) Object Detection framework using BEVFusion. Features inference, visualization, fine-tuning, and evaluation on nuScenes", "url": "https://github.com/SoubhikMajumdar/3D-LiDAR-Based-Birds-Eye-View-Object-Detection-via-BEVFusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:min60--lane_detection", "kind": "repo", "label": "MIN60/Lane_Detection (3\u2605) \u2014 Lane Detection Using Hough Transform and Bird's Eye View", "url": "https://github.com/MIN60/Lane_Detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:cp-security--cp-guard", "kind": "repo", "label": "CP-Security/CP-Guard (11\u2605) \u2014 [AAAI 2025 Oral] This is the official implenmentation of \"CP-Guard: Malicious agent detection and defense in collaborative bird's eye view segmentation\"", "url": "https://github.com/CP-Security/CP-Guard", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:trustai--robustbev", "kind": "repo", "label": "TrustAI/RobustBEV (3\u2605) \u2014 A Black-Box Evaluation Framework for Semantic Robustness in Bird\u2019s Eye View Detection", "url": "https://github.com/TrustAI/RobustBEV", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:kulmanferdi--rail-detection", "kind": "repo", "label": "kulmanferdi/rail-detection (1\u2605) \u2014 Railway detection python library, birds eye view transformation and TCOM calculation", "url": "https://github.com/kulmanferdi/rail-detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:adlab-autodrive--bevfusion", "kind": "repo", "label": "ADLab-AutoDrive/BEVFusion (970\u2605) \u2014 Offical PyTorch implementation of \"BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework\"", "url": "https://github.com/ADLab-AutoDrive/BEVFusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:linclubs--bevfusion-ros-tensorrt", "kind": "repo", "label": "linClubs/BEVFusion-ROS-TensorRT (240\u2605) \u2014 BEVFusion-ROS-TensorRT-CPP real time inference including ros1 & ros2.", "url": "https://github.com/linClubs/BEVFusion-ROS-TensorRT", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:maxleo-lmz--bevfusion_learningnote", "kind": "repo", "label": "MaxLeo-LMZ/BEVFusion_Learningnote (113\u2605) \u2014 \u672cFork\u4ee3\u7801\u4ed3\u5e93\u4f5c\u4e3a\u672c\u4eba\u8bb0\u5f55\u5b66\u4e60BEVFusion\u7684\u5b66\u4e60\u7b14\u8bb0\u4f7f\u7528\uff0c\u4f1a\u9010\u6b65\u7406\u89e3\u4ee3\u7801\u5e76\u6dfb\u52a0\u5927\u91cf\u4e2d\u6587\u6ce8\u91ca\u3002 \u672c\u4ed3\u5e93\u4ee3\u7801\u5df2\u53c2\u7167\u300abevfusion\u5355\u663e\u5361\u8bad\u7ec3/\u6d4b\u8bd5\u300b\u505a\u4e86\u5355GPU\u8bad\u7ec3\u548c\u6d4b\u8bd5\u7684\u4fee\u6539\u3002 \u5e76\u5728\u672c\u4eba\u4e3b\u673a\u4e0a\u505a\u8fc7\u4e86\u6d4b\u8bd5\u3002", "url": "https://github.com/MaxLeo-LMZ/BEVFusion_Learningnote", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:nvidia-ai-iot--lidar_ai_solution", "kind": "repo", "label": "NVIDIA-AI-IOT/Lidar_AI_Solution (1843\u2605) \u2014 A project demonstrating Lidar related AI solutions, including three GPU accelerated Lidar/camera DL networks (PointPillars, CenterPoint, BEVFusion) and the related libs (cuPCL, 3D SparseConvolution, Y", "url": "https://github.com/NVIDIA-AI-IOT/Lidar_AI_Solution", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:seunghwi0613--ros2_bevfusion_demo", "kind": "repo", "label": "SeungHwi0613/ros2_bevfusion_demo (32\u2605)", "url": "https://github.com/SeungHwi0613/ros2_bevfusion_demo", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:egemenkopuz--temporal-bevfusion", "kind": "repo", "label": "egemenkopuz/temporal-bevfusion (19\u2605) \u2014 Master's thesis research on 3D object detection using LiDAR and Camera data for infrastructure and railway domains, emphasizing inference optimization and utilization of temporal information for dista", "url": "https://github.com/egemenkopuz/temporal-bevfusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:knzo25--bevfusion_ros2", "kind": "repo", "label": "knzo25/bevfusion_ros2 (32\u2605) \u2014 BEVFusion implementation in ROS2", "url": "https://github.com/knzo25/bevfusion_ros2", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:shouxieai--bevfusion_02hero", "kind": "repo", "label": "shouxieai/bevfusion_02hero (17\u2605)", "url": "https://github.com/shouxieai/bevfusion_02hero", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:mx2013713828--cuda_bevfusion", "kind": "repo", "label": "mx2013713828/CUDA_BEVFusion (9\u2605) \u2014 Nvidia-IOT-CUDA_BEVFusion with lidar-only mode, deployed on Nvidia AGX ORIN.", "url": "https://github.com/mx2013713828/CUDA_BEVFusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:dreamdreams8--bevfusion_custom", "kind": "repo", "label": "Dreamdreams8/bevfusion_custom (5\u2605)", "url": "https://github.com/Dreamdreams8/bevfusion_custom", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:barrydoooit--bevfusion4kitti", "kind": "repo", "label": "barrydoooit/bevfusion4kitti (8\u2605) \u2014 This tells you how to tune bevfusion (mmdet3d ver) for KITTI dataset", "url": "https://github.com/barrydoooit/bevfusion4kitti", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:iei-ap--iei-bevfusion_plus_plus", "kind": "repo", "label": "IEI-AP/IEI-BEVFusion_plus_plus (15\u2605)", "url": "https://github.com/IEI-AP/IEI-BEVFusion_plus_plus", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:newintelligence4--bevfusion_preprocess", "kind": "repo", "label": "newintelligence4/BEVfusion_preprocess (11\u2605) \u2014 Multiple Lidar preprocessor for BEVfusion", "url": "https://github.com/newintelligence4/BEVfusion_preprocess", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:sharkls--bevfusione2e", "kind": "repo", "label": "sharkls/BEVFusionE2E (5\u2605) \u2014 BEVFusion\u90e8\u7f72\u5de5\u7a0b", "url": "https://github.com/sharkls/BEVFusionE2E", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:mukaffi28--banglacalamitymmd-a-comprehensive-benchmark-dataset-for-multimodal-disaster-identification", "kind": "repo", "label": "Mukaffi28/BanglaCalamityMMD-A-Comprehensive-Benchmark-Dataset-for-Multimodal-Disaster-Identification (7\u2605) \u2014 This study presents a novel multimodal fusion technique for disaster identification in Bangla, combining text and image data using the \"BanglaCalamityMMD\" dataset. Employing DisasterTextNet, D", "url": "https://github.com/Mukaffi28/BanglaCalamityMMD-A-Comprehensive-Benchmark-Dataset-for-Multimodal-Disaster-Identification", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:hoangquy18--multimodal-aspect-category-sentiment-analysis", "kind": "repo", "label": "hoangquy18/Multimodal-Aspect-Category-Sentiment-Analysis (14\u2605) \u2014 Dataset and codes for our paper \"New Benchmark Dataset and Fine-Grained Cross-Modal Fusion Framework for Vietnamese Multimodal Aspect-Category Sentiment Analysis\"", "url": "https://github.com/hoangquy18/Multimodal-Aspect-Category-Sentiment-Analysis", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:neticus--dreamer-multimodal-emotion-recognition", "kind": "repo", "label": "NeTicus/DREAMER-Multimodal-Emotion-Recognition (0\u2605) \u2014 Standardized benchmark for multimodal emotion recognition, evaluating fusion methods across audio, visual, and physiological data using the DREAMER dataset.", "url": "https://github.com/NeTicus/DREAMER-Multimodal-Emotion-Recognition", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:nhdnguyenhoangduc--llvip-pedestrian-detection", "kind": "repo", "label": "Nhdnguyenhoangduc/llvip-pedestrian-detection (0\u2605) \u2014 Low-light pedestrian detection via visible-infrared pixel fusion + YOLOv8s fine-tuning on the LLVIP benchmark dataset", "url": "https://github.com/Nhdnguyenhoangduc/llvip-pedestrian-detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:simondlevy--sensorfusion", "kind": "repo", "label": "simondlevy/SensorFusion (177\u2605) \u2014 A simple Matlab example of sensor fusion using a Kalman filter", "url": "https://github.com/simondlevy/SensorFusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:sharathsrini--kalman-filter-for-sensor-fusion", "kind": "repo", "label": "sharathsrini/Kalman-Filter-for-Sensor-Fusion (154\u2605) \u2014 A Sensor Fusion Algorithm that can predict a State Estimate and Update if it is uncertain", "url": "https://github.com/sharathsrini/Kalman-Filter-for-Sensor-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:paulyehtw--lidar-and-radar-sensor-fusion-with-extended-kalman-filter", "kind": "repo", "label": "paulyehtw/Lidar-and-Radar-sensor-fusion-with-Extended-Kalman-Filter (150\u2605) \u2014 Fusing Lidar and Radar data with Extended Kalman Filter (EKF)", "url": "https://github.com/paulyehtw/Lidar-and-Radar-sensor-fusion-with-Extended-Kalman-Filter", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:technitute--akfsf-simulation-cpp", "kind": "repo", "label": "technitute/AKFSF-Simulation-CPP (111\u2605) \u2014 Simulation Environment for Advanced Kalman Filtering for Sensor Fusion Course", "url": "https://github.com/technitute/AKFSF-Simulation-CPP", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:diegoavillegasg--imu-gnss-lidar-sensor-fusion-using-extended-kalman-filter-for-state-estimation", "kind": "repo", "label": "diegoavillegasg/IMU-GNSS-Lidar-sensor-fusion-using-Extended-Kalman-Filter-for-State-Estimation (279\u2605) \u2014 State Estimation and Localization of an autonomous vehicle based on IMU (high rate), GNSS (GPS) and Lidar data with sensor fusion techniques using the Extended Kalman Filter (EKF).", "url": "https://github.com/diegoavillegasg/IMU-GNSS-Lidar-sensor-fusion-using-Extended-Kalman-Filter-for-State-Estimation", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:jeff-zhouxiaolong--demo_for_kalmanfilter", "kind": "repo", "label": "Jeff-Zhouxiaolong/demo_for_kalmanFilter (4\u2605) \u2014 fusion location with only ranging and 6-axis imu sensor in similink data", "url": "https://github.com/Jeff-Zhouxiaolong/demo_for_kalmanFilter", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:williamhyin--sfnd_unscented_kalman_filter", "kind": "repo", "label": "williamhyin/SFND_Unscented_Kalman_Filter (63\u2605) \u2014 Unscented_Kalman_Filter, CTRV model, Sensor fusion of lidar and radar, multiobject detection", "url": "https://github.com/williamhyin/SFND_Unscented_Kalman_Filter", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ptiwari0664--sensorfusionnanodegree", "kind": "repo", "label": "ptiwari0664/SensorFusionNanoDegree (59\u2605) \u2014 Learn to detect obstacles in lidar point clouds through clustering and segmentation, apply thresholds and filters to radar data in order to accurately track objects, and augment your perception by pro", "url": "https://github.com/ptiwari0664/SensorFusionNanoDegree", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:asuri2--carnd-extended-kalman-filter-p6", "kind": "repo", "label": "asuri2/CarND-Extended-Kalman-Filter-P6 (26\u2605) \u2014 Self Driving Car Project 6 - Sensor Fusion(Extended Kalman Filter)", "url": "https://github.com/asuri2/CarND-Extended-Kalman-Filter-P6", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:niksknocksu--decentralized_kalmanfilter", "kind": "repo", "label": "niksknocksu/Decentralized_KalmanFilter (12\u2605) \u2014 A decentralized version of extended Kalman filter for a sensor network of over 100 nodes. Uses consensus algorithm for sensor fusion", "url": "https://github.com/niksknocksu/Decentralized_KalmanFilter", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:neksfyris--esekf_imu_gnss_lidar", "kind": "repo", "label": "NekSfyris/ESEKF_IMU_GNSS_Lidar (88\u2605) \u2014 Sensor fusion between IMU, GNSS and Lidar data using an Error State Extended Kalman Filter.", "url": "https://github.com/NekSfyris/ESEKF_IMU_GNSS_Lidar", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:srnand--object-tracking-and-state-prediction-with-unscented-and-extended-kalman-filters", "kind": "repo", "label": "srnand/Object-Tracking-and-State-Prediction-with-Unscented-and-Extended-Kalman-Filters (65\u2605) \u2014 Radar and Lidar Sensor Fusion using Simple, Extended, and Unscented Kalman Filter for Object Tracking and State Prediction.", "url": "https://github.com/srnand/Object-Tracking-and-State-Prediction-with-Unscented-and-Extended-Kalman-Filters", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:rahul-sb--vins", "kind": "repo", "label": "rahul-sb/VINS (31\u2605) \u2014 Sensor Fusion using Extended Kalman Filter", "url": "https://github.com/rahul-sb/VINS", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:janudis--extended-kalman-filter-gps_imu", "kind": "repo", "label": "Janudis/Extended-Kalman-Filter-GPS_IMU (52\u2605) \u2014 Sensor Fusion of GPS and IMU with Extended Kalman Filter for Localization in Autonomous Driving", "url": "https://github.com/Janudis/Extended-Kalman-Filter-GPS_IMU", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:informramiz--unscented-kalman-filter", "kind": "repo", "label": "informramiz/Unscented-Kalman-Filter (15\u2605) \u2014 Unscented Kalman Filter (C++) for sensor fusion of Lidar and Radar to localize a vehicle position and velocity. ", "url": "https://github.com/informramiz/Unscented-Kalman-Filter", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:paulyehtw--sensor-fusion-using-es-ekf", "kind": "repo", "label": "paulyehtw/Sensor-Fusion-Using-ES-EKF (32\u2605) \u2014 Implement Error-State Extended Kalman Filter on fusing data from IMU, Lidar and GNSS.  ", "url": "https://github.com/paulyehtw/Sensor-Fusion-Using-ES-EKF", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:raghuramshankar--kalman-filter-localization", "kind": "repo", "label": "raghuramshankar/kalman-filter-localization (20\u2605) \u2014 Implementation of sensor fusion using Kalman Filters for localization of autonomous vehicles.", "url": "https://github.com/raghuramshankar/kalman-filter-localization", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:betabison--gnss-sensor-fusion", "kind": "repo", "label": "betaBison/gnss-sensor-fusion (60\u2605) \u2014 Extended Kalman Filter (EKF) for position estimation using raw GNSS signals, IMU data, and barometer", "url": "https://github.com/betaBison/gnss-sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:cawfree--react-native-sensor-fusion", "kind": "repo", "label": "cawfree/react-native-sensor-fusion (32\u2605) \u2014 Robust absolute positioning in React Native.", "url": "https://github.com/cawfree/react-native-sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:vannizhou--dwd_sensor_fusion", "kind": "repo", "label": "VanniZhou/DWD_sensor_fusion (42\u2605) \u2014 Lidar, camera, Radar multi-sensor fusion and Dynamic Weight Distribution (DWD) algorithm (ROS) . This project is able to fusion the targets of lidar, radar and camera, and assign them dynamic weights ", "url": "https://github.com/VanniZhou/DWD_sensor_fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:sargisyonan--ukal", "kind": "repo", "label": "SargisYonan/uKal (43\u2605) \u2014 Micro Kalman Filter for linear and nonlinear systems", "url": "https://github.com/SargisYonan/uKal", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:shantanubhadoria--go-kalmanfilter", "kind": "repo", "label": "shantanubhadoria/go-kalmanfilter (37\u2605) \u2014 Golang Library for Kalman Filter(also known as Linear Quadratic Estimation) used in sensor fusion", "url": "https://github.com/shantanubhadoria/go-kalmanfilter", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:pangsu0613--clocs", "kind": "repo", "label": "pangsu0613/CLOCs (404\u2605) \u2014 CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection", "url": "https://github.com/pangsu0613/CLOCs", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:timkie--yolo-lidar-fusion", "kind": "repo", "label": "TimKie/YOLO-LiDAR-Fusion (78\u2605) \u2014 LiDAR-Camera Fusion for 3D Object Detection in Autonomous Driving Systems", "url": "https://github.com/TimKie/YOLO-LiDAR-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:loahit5101--pointpillars-camera-lidar-fusion", "kind": "repo", "label": "Loahit5101/PointPillars-Camera-LiDAR-Fusion (52\u2605) \u2014 Implementation of PointPillars Network with LiDAR-camera fusion for 3D Object Detection in Autonomous Driving.", "url": "https://github.com/Loahit5101/PointPillars-Camera-LiDAR-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:rasd3--3d-cvf", "kind": "repo", "label": "rasd3/3D-CVF (131\u2605) \u2014 [ECCV 2020] This is the official implementation of 3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object Detection", "url": "https://github.com/rasd3/3D-CVF", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ram-godavarthi--sensor_fusion_3d_object_tracking_lidar-camera", "kind": "repo", "label": "Ram-Godavarthi/Sensor_Fusion_3D_Object_Tracking_Lidar-Camera (35\u2605) \u2014 Collision Avoidance System with Camera and Lidar - Track an Object in 3D Space - Object Detection with YOLO - Descriptors and Keypoint Matching", "url": "https://github.com/Ram-Godavarthi/Sensor_Fusion_3D_Object_Tracking_Lidar-Camera", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:laiqingsi--clocs_lqs", "kind": "repo", "label": "Laiqingsi/CLOCs_LQS (52\u2605) \u2014 An implementation of CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection.", "url": "https://github.com/Laiqingsi/CLOCs_LQS", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:rasd3--3d-dual-fusion", "kind": "repo", "label": "rasd3/3D-Dual-Fusion (78\u2605) \u2014 [Arxiv 2022] This is the official implementation of 3D Dual-Fusion: Dual-Domain Dual-Query Camera-LiDAR Fusion for 3D Object Detection ", "url": "https://github.com/rasd3/3D-Dual-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:xiongweiyi--lxl", "kind": "repo", "label": "XiongWeiyi/LXL (26\u2605) \u2014 Code for paper: [IEEE T-IV 2024] LXL: LiDAR Excluded Lean 3D Object Detection With 4D Imaging Radar and Camera Fusion", "url": "https://github.com/XiongWeiyi/LXL", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ika-rwth-aachen--multicorrupt", "kind": "repo", "label": "ika-rwth-aachen/MultiCorrupt (86\u2605) \u2014 [IV2024] MultiCorrupt: A benchmark for robust multi-modal 3D object detection, evaluating LiDAR-Camera fusion models in autonomous driving. Includes diverse corruption types (e.g., misalignment, misca", "url": "https://github.com/ika-rwth-aachen/MultiCorrupt", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:adlab-autodrive--lidar-camera-robust-benchmark", "kind": "repo", "label": "ADLab-AutoDrive/lidar-camera-robust-benchmark (27\u2605) \u2014 Code release for \"Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection\"", "url": "https://github.com/ADLab-AutoDrive/lidar-camera-robust-benchmark", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:yinjunbo--centerpoint-fusion", "kind": "repo", "label": "yinjunbo/CenterPoint-Fusion (97\u2605) \u2014 The proposed approach enhances the CenterPoint baseline with a multimodal fusion mechanism. First, inspired by PointPainting, an off-the-shelf Mask-RCNN model trained from nuImages is employed to gene", "url": "https://github.com/yinjunbo/CenterPoint-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:shiluyang96--camera-lidar-map-fusion-model", "kind": "repo", "label": "ShiluYang96/Camera-LiDAR-Map-Fusion-Model (13\u2605) \u2014 A multi-modal 3D detection network for autonomous driving", "url": "https://github.com/ShiluYang96/Camera-LiDAR-Map-Fusion-Model", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:azitt--lidar-camerafusion-3dobjectdetection", "kind": "repo", "label": "Azitt/Lidar-CameraFusion-3DobjectDetection (6\u2605)", "url": "https://github.com/Azitt/Lidar-CameraFusion-3DobjectDetection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:gokulk1994--3d-object-tracking-lidar-camera-fusion", "kind": "repo", "label": "Gokulk1994/3D-Object-Tracking-Lidar-Camera-Fusion (9\u2605) \u2014 Track 3D objects in KITTI dataset, using Lidar and Camera sensor fusion and YOLO based object detection.", "url": "https://github.com/Gokulk1994/3D-Object-Tracking-Lidar-Camera-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:iranqin--supfusion", "kind": "repo", "label": "IranQin/SupFusion (18\u2605) \u2014 This is the official code of the paper \"SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection\"", "url": "https://github.com/IranQin/SupFusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:xxlbigbrother--fusion-rcnn", "kind": "repo", "label": "xxlbigbrother/Fusion-RCNN (15\u2605) \u2014 This is the official code of FusionRCNN: LiDAR-Camera Fusion for Two-stage 3D Object Detection.", "url": "https://github.com/xxlbigbrother/Fusion-RCNN", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:amolloma--nd013-c2-sensor-fusion", "kind": "repo", "label": "amolloma/nd013-c2-sensor-fusion (9\u2605) \u2014 Course submission material for Lidar point cloud based 3D Detection using Yolo, followed by Sensor Fusion and Camera Based Tracking using Extended Kalman Filters for Udacity Self Driving Nanodegree", "url": "https://github.com/amolloma/nd013-c2-sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:mingqj--depthfusion", "kind": "repo", "label": "Mingqj/DepthFusion (8\u2605) \u2014 DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection", "url": "https://github.com/Mingqj/DepthFusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:jigmiey--clocs", "kind": "repo", "label": "Jigmiey/CLOCs (9\u2605) \u2014 Multimodal Fusion of Camera Image data and LIDAR data for 3D object detection.", "url": "https://github.com/Jigmiey/CLOCs", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:liyih--corenet", "kind": "repo", "label": "liyih/CoreNet (28\u2605) \u2014 [Information Fusion 2025] CoreNet: Conflict Resolution Network for point-pixel misalignment and sub-task suppression of 3D LiDAR-camera object detection", "url": "https://github.com/liyih/CoreNet", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:denyz--fadn", "kind": "repo", "label": "denyz/FADN (11\u2605) \u2014 A 3D object detection neural network in the fusion of lidar point clouds and camera images", "url": "https://github.com/denyz/FADN", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:rsade090--relifusion", "kind": "repo", "label": "rsade090/Relifusion (8\u2605) \u2014 Reliability-aware LiDAR-Camera fusion framework for robust 3D object detection in autonomous driving.", "url": "https://github.com/rsade090/Relifusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:mingqj--dfu3d", "kind": "repo", "label": "Mingqj/DFU3D (11\u2605) \u2014 [ACM MM 2025] Enhancing Pseudo-Boxes via Data-Level LiDAR-Camera Fusion for Unsupervised 3D Object Detection", "url": "https://github.com/Mingqj/DFU3D", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:morganm94--multicorrupt", "kind": "repo", "label": "morganm94/MultiCorrupt (5\u2605) \u2014 A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection.", "url": "https://github.com/morganm94/MultiCorrupt", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:dr-utopia--lidar-camera-fusion-3d-detection", "kind": "repo", "label": "Dr-Utopia/LiDAR-Camera-Fusion-3D-Detection (0\u2605) \u2014 A lightweight 3D small object detection and multi-sensor fusion platform based on YOLOv8 and improved PointPillars.", "url": "https://github.com/Dr-Utopia/LiDAR-Camera-Fusion-3D-Detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:tasarma--lidar-camera-fusion-3d-object-detection", "kind": "repo", "label": "tasarma/lidar-camera-fusion-3D-object-detection (0\u2605) \u2014 Master's thesis project exploring how combining two sensor types (camera + LiDAR) can improve how machines perceive and detect objects in 3D space.", "url": "https://github.com/tasarma/lidar-camera-fusion-3D-object-detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:jynxzzz--dual-camera-lidar-fusion", "kind": "repo", "label": "Jynxzzz/dual-camera-lidar-fusion (0\u2605) \u2014 Dual-Camera LiDAR Fusion for Occlusion-Robust 3D Detection in Autonomous Driving (CARLA)", "url": "https://github.com/Jynxzzz/dual-camera-lidar-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:jylee-114--is-fusion", "kind": "repo", "label": "jylee-114/IS-Fusion (1\u2605) \u2014 Camera\u2013LiDAR sensor fusion for 3D object detection", "url": "https://github.com/jylee-114/IS-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:praveenkottari--multi-modal-sensor-fusion", "kind": "repo", "label": "Praveenkottari/Multi-modal-sensor-fusion (4\u2605) \u2014 The study presents a Multi-Modal Fusion Pipeline that integrates Lidar, Camera, and IMU sensors for end-to end 3D object detection, mapping and global localization, particularly suited for real world ", "url": "https://github.com/Praveenkottari/Multi-modal-sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:redddddyyyyy--lidar-camera-fusion", "kind": "repo", "label": "redddddyyyyy/lidar-camera-fusion (0\u2605) \u2014 LiDAR-camera sensor fusion with YOLOv8 for 3D object detection. Frustum-based pipeline with ROS2 node, KITTI support, and temporal tracking.", "url": "https://github.com/redddddyyyyy/lidar-camera-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ashwinnraj--3d-obstacle-detection-with-lidar-camera", "kind": "repo", "label": "Ashwinnraj/3D-obstacle-Detection-with-LiDar-Camera (0\u2605) \u2014 This repository is built for Udacity course - SENSOR FUSION, Lesson 2; Third Project.", "url": "https://github.com/Ashwinnraj/3D-obstacle-Detection-with-LiDar-Camera", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:andia76--sdcnd02-03_3d_object_detection_and_tracking", "kind": "repo", "label": "AndiA76/SDCND02-03_3D_Object_Detection_and_Tracking (4\u2605) \u2014 Project 2 and 3 of Udacity's \"Self-Driving Car Engineer\" Nanodegree Program about 3D object detection and 3D object tracking over time using sensor fusion of Lidar and Camera measurements with an exte", "url": "https://github.com/AndiA76/SDCND02-03_3D_Object_Detection_and_Tracking", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ka234388--lidar-camera-fusion-for-3d-object-detection", "kind": "repo", "label": "ka234388/LiDAR-Camera-Fusion-for-3D-Object-Detection (0\u2605)", "url": "https://github.com/ka234388/LiDAR-Camera-Fusion-for-3D-Object-Detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:nishanth-cryptos--3d-object-detection-bev-fusion-lidar-radar-camera-", "kind": "repo", "label": "nishanth-cryptos/3d-Object-detection-bev-fusion-lidar-radar-camera- (0\u2605)", "url": "https://github.com/nishanth-cryptos/3d-Object-detection-bev-fusion-lidar-radar-camera-", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:saif-ashraf99--lidar-camera-fusion-for-3d-object-detection", "kind": "repo", "label": "saif-ashraf99/LiDAR-Camera-Fusion-for-3D-Object-Detection (0\u2605)", "url": "https://github.com/saif-ashraf99/LiDAR-Camera-Fusion-for-3D-Object-Detection", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:mhatre-shubham--camera-lidar-sensor-fusion", "kind": "repo", "label": "mhatre-shubham/camera-lidar-sensor-fusion (1\u2605) \u2014 Camera LiDAR sensor fusion pipeline for autonomous driving, enabling robust perception through sensor data processing, 3D object detection, and multi-object tracking.", "url": "https://github.com/mhatre-shubham/camera-lidar-sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:lorenzofaoro--porject-data-fusion3d-object-detection-with-lidar-camera-fusion", "kind": "repo", "label": "lorenzofaoro/porject-data-fusion3D-Object-Detection-with-LiDAR-Camera-Fusion (0\u2605) \u2014 3D Object Detection with LiDAR-Camera Fusion with PointPillars + ResNet Architecture on KITTI-360 Dataset", "url": "https://github.com/lorenzofaoro/porject-data-fusion3D-Object-Detection-with-LiDAR-Camera-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:whymesomeng--rgh-fusion", "kind": "repo", "label": "whymesomeng/RGH-Fusion (0\u2605) \u2014  RGH-Fusion for LiDAR-Camera 3D object detection on KITTI dataset", "url": "https://github.com/whymesomeng/RGH-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:farhanaristo--ffcl3d", "kind": "repo", "label": "farhanaristo/FFCL3D (1\u2605) \u2014 Fusion 2D Camera Object Detection + 3D Lidar Object Detection (Kitti dataset)", "url": "https://github.com/farhanaristo/FFCL3D", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:advaitp--clocs-pointpillars-and-cascade-rcnn-", "kind": "repo", "label": "advaitp/CLOCS-PointPillars-and-Cascade-RCNN- (0\u2605) \u2014 CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection", "url": "https://github.com/advaitp/CLOCS-PointPillars-and-Cascade-RCNN-", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:iceory--pmf", "kind": "repo", "label": "ICEORY/PMF (231\u2605) \u2014 Perception-aware multi-sensor fusion for 3D LiDAR semantic segmentation (ICCV 2021)", "url": "https://github.com/ICEORY/PMF", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:lyon2020--msp-attacks", "kind": "repo", "label": "Lyon2020/MSP-Attacks (75\u2605) \u2014 [NEUCOM] A comprehensive repository of research papers and resources on adversarial attacks targeting autonomous driving perception systems, focusing on single-sensor vulnerabilities and multi-sensor ", "url": "https://github.com/Lyon2020/MSP-Attacks", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:asguard-uci--msf-adv", "kind": "repo", "label": "ASGuard-UCI/MSF-ADV (84\u2605) \u2014 MSF-ADV is a novel physical-world adversarial attack method, which can fool the Multi Sensor Fusion (MSF) based autonomous driving (AD) perception in the victim autonomous vehicle (AV) to fail in dete", "url": "https://github.com/ASGuard-UCI/MSF-ADV", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:oskarnatan--compact-perception", "kind": "repo", "label": "oskarnatan/compact-perception (9\u2605) \u2014 Implementation code for: O. Natan and J. Miura, \u201cTowards Compact Autonomous Driving Perception with Balanced Learning and Multi-sensor Fusion,\u201d IEEE Transactions on Intelligent Transportation Systems,", "url": "https://github.com/oskarnatan/compact-perception", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ipranaysatija--multi-sensor-fusion", "kind": "repo", "label": "ipranaysatija/Multi-Sensor-Fusion (2\u2605) \u2014 A ROS2 Python node that fuses 2D LiDAR and RGB camera data by synchronizing topics, applying tf2-based extrinsics, and projecting LiDAR points into the image plane. Supports undistortion, PointCloud2 ", "url": "https://github.com/ipranaysatija/Multi-Sensor-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:mh-kav-institute--multi_sensor_perception_fusion", "kind": "repo", "label": "mh-kav-institute/multi_sensor_perception_fusion (0\u2605) \u2014 Camera and LiDAR data fusion, tracking and filtering framework", "url": "https://github.com/mh-kav-institute/multi_sensor_perception_fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:msftest--multitest", "kind": "repo", "label": "MSFTest/MultiTest (5\u2605) \u2014 This repository provides the code of the paper \"MultiTest: Physical-Aware Object Insertion for Testing Multi-sensor Fusion Perception Systems\"", "url": "https://github.com/MSFTest/MultiTest", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:yeshwanthkumar-sa--multi-sensor-fusion", "kind": "repo", "label": "yeshwanthKumar-sa/multi-sensor-fusion (0\u2605) \u2014 Multi-Sensor Fusion for Autonomous Vehicle Perception", "url": "https://github.com/yeshwanthKumar-sa/multi-sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:aicha-el-idrissi--adas-multisensor-perception", "kind": "repo", "label": "AICHA-El-idrissi/ADAS-MultiSensor-Perception (0\u2605) \u2014 Multi-sensor ADAS system \u2014 LiDAR/Radar/Stereo Camera/IMU fusion with YOLOv8 detection, DeepSORT tracking, Lane Keeping Assist & Collision Avoidance in Webots + ROS 2 + MATLAB/Simulink", "url": "https://github.com/AICHA-El-idrissi/ADAS-MultiSensor-Perception", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:hdb1301040027--multi-sensor-fusion-for-perception", "kind": "repo", "label": "hdb1301040027/Multi-Sensor-Fusion-for-Perception (1\u2605)", "url": "https://github.com/hdb1301040027/Multi-Sensor-Fusion-for-Perception", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:gauravr2001--autonomous-vehicle-multi-sensor-fusion-perception", "kind": "repo", "label": "GauravR2001/Autonomous-Vehicle-Multi-Sensor-Fusion-Perception (0\u2605)", "url": "https://github.com/GauravR2001/Autonomous-Vehicle-Multi-Sensor-Fusion-Perception", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:afondiel--multimodal-sensor-fusion", "kind": "repo", "label": "afondiel/multimodal-sensor-fusion (1\u2605) \u2014 A curated list of resources, libraries, tools, frameworks for Multimodal sensor fusion.", "url": "https://github.com/afondiel/multimodal-sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:supergokou--sensor-fusion", "kind": "repo", "label": "SuperGokou/sensor-fusion (0\u2605) \u2014 Multi-sensor fusion perception (LiDAR / 4D radar / camera)", "url": "https://github.com/SuperGokou/sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:adityasonawane1155--multi-sensor-fusion-for-advanced-perception-and-estimation-", "kind": "repo", "label": "AdityaSonawane1155/Multi-Sensor-Fusion-for-Advanced-Perception-and-Estimation- (0\u2605)", "url": "https://github.com/AdityaSonawane1155/Multi-Sensor-Fusion-for-Advanced-Perception-and-Estimation-", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:rahmanfarhan555--multi-sensor-fusion-for-advanced-perception-and-estimation-", "kind": "repo", "label": "RahmanFarhan555/Multi-Sensor-Fusion-for-Advanced-Perception-and-Estimation- (0\u2605)", "url": "https://github.com/RahmanFarhan555/Multi-Sensor-Fusion-for-Advanced-Perception-and-Estimation-", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:mendesri--multimodal_sensor_fusion_for_perception_and_state_estimation", "kind": "repo", "label": "mendesri/Multimodal_sensor_fusion_for_perception_and_state_estimation (0\u2605)", "url": "https://github.com/mendesri/Multimodal_sensor_fusion_for_perception_and_state_estimation", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:rahulaloth--robosense-fusion", "kind": "repo", "label": "RahulAloth/RoboSense-Fusion (1\u2605) \u2014 ROS2\u2011based Multi\u2011Sensor Perception Framework in Modern C++", "url": "https://github.com/RahulAloth/RoboSense-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:muresaijaideepreddy--autonomous-vehicle-multi-sensor-perception-pipeline", "kind": "repo", "label": "muresaijaideepreddy/Autonomous-Vehicle-Multi-Sensor-Perception-Pipeline (0\u2605) \u2014 Real-time autonomous vehicle perception pipeline using LiDAR, C++, and Eigen, designed for sensor fusion and tracking.", "url": "https://github.com/muresaijaideepreddy/Autonomous-Vehicle-Multi-Sensor-Perception-Pipeline", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:chenyang-zhu--self-driving-fusion-perception-tracking", "kind": "repo", "label": "Chenyang-ZHU/self-driving-fusion-perception-tracking (1\u2605) \u2014 A self-griving project based on multi-sensor late fusion, including single sensor peception based on camera/lidar/radar, multi-sensor perception result fusion and tracking.", "url": "https://github.com/Chenyang-ZHU/self-driving-fusion-perception-tracking", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:poojasawantadas--adas-perception-sensor-fusion", "kind": "repo", "label": "poojasawantADAS/adas-perception-sensor-fusion (0\u2605) \u2014 Real-time multi-sensor perception and fusion pipeline for ADAS systems \u2014 C++20 & Python", "url": "https://github.com/poojasawantADAS/adas-perception-sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:yeshwanthkumar-sa--multi-sensor-fusion-autonomous-vehicle", "kind": "repo", "label": "yeshwanthKumar-sa/multi-sensor-fusion-autonomous-vehicle (0\u2605) \u2014 Exploration of multi-sensor fusion techniques for autonomous vehicle perception using camera, LiDAR, radar, PyTorch, and the nuScenes dataset.", "url": "https://github.com/yeshwanthKumar-sa/multi-sensor-fusion-autonomous-vehicle", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:sidkos--multi_sensor_fusion", "kind": "repo", "label": "sidkos/multi_sensor_fusion (1\u2605) \u2014 Python-based automation framework for validating multi-sensor fusion systems (Radar, Camera, Late Fusion) with strict KPI enforcement, advanced performance metrics, and full CI/CD integration. Designe", "url": "https://github.com/sidkos/multi_sensor_fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:jacksonzhang1116--astrionfusionengine", "kind": "repo", "label": "jacksonzhang1116/AstrionFusionEngine (1\u2605) \u2014 A next-generation multi-sensor fusion engine for intelligent positioning, navigation, and spatial perception.", "url": "https://github.com/jacksonzhang1116/AstrionFusionEngine", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:kvemuru--spacecraft-perception-extended-kalman", "kind": "repo", "label": "kvemuru/spacecraft-perception-extended-kalman (0\u2605) \u2014 Modular Extended Kalman Filter for spacecraft orbit determination, relative navigation, object tracking, and multi-sensor fusion", "url": "https://github.com/kvemuru/spacecraft-perception-extended-kalman", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ahmedzainsyed--ai-based-multi-sensor-fusion-engine-for-autonomous-systems", "kind": "repo", "label": "ahmedzainsyed/AI-Based-Multi-Sensor-Fusion-Engine-for-Autonomous-Systems (0\u2605) \u2014 Probabilistic sensor fusion and autonomous perception platform using Kalman filters, transformers, uncertainty modeling, digital twins, and edge AI simulation for robust localization.", "url": "https://github.com/ahmedzainsyed/AI-Based-Multi-Sensor-Fusion-Engine-for-Autonomous-Systems", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:msftest--drivence", "kind": "repo", "label": "MSFTest/Drivence (0\u2605) \u2014 Drivence: Realistic Driving Sequence Synthesis for Testing Multi-sensor Fusion Perception Systems", "url": "https://github.com/MSFTest/Drivence", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:chr3720-alt--a-robust-multi-sensor-fusion-framework-for-autonomous-vehicle", "kind": "repo", "label": "chr3720-alt/A-Robust-Multi-Sensor-Fusion-Framework-for-Autonomous-Vehicle (0\u2605) \u2014 A robust multi-sensor fusion framework combines data from cameras, LiDAR, radar, and IMU to improve perception, localization, and navigation in autonomous vehicles. The system enhances object detectio", "url": "https://github.com/chr3720-alt/A-Robust-Multi-Sensor-Fusion-Framework-for-Autonomous-Vehicle", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:sarathkumarkomathukattil--deep-learning-perception-system", "kind": "repo", "label": "SarathKumarKomathukattil/deep-learning-perception-system (1\u2605) \u2014 Deep learning perception system in PyTorch \u2014 YOLOv8 detection, ENet segmentation (87\u00d7 parameter reduction), multi-sensor fusion. Real-time edge deployment, sim-to-real analysis.", "url": "https://github.com/SarathKumarKomathukattil/deep-learning-perception-system", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:yuukijiang--fire_perception", "kind": "repo", "label": "yuukijiang/Fire_perception (1\u2605) \u2014 This is a project of fire perception. The codes in this project are related to the paper named \"Research on Multi-Sensor Fusion Indoor Fire Perception Algorithm Based on Improved TCN\".  ", "url": "https://github.com/yuukijiang/Fire_perception", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:joshleh--fusiontrack", "kind": "repo", "label": "joshleh/fusiontrack (1\u2605) \u2014 Multi-sensor UAV tracking via Extended Kalman Filter fusion of simulated radar and camera detections. Built to mirror perception and sensor fusion workflows in autonomous defense systems.", "url": "https://github.com/joshleh/fusiontrack", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:radwaelsobki--ros2-sensor-fusion-with-kalman-filter-for-real-time-multi-sensor-integration", "kind": "repo", "label": "RadwaElsobki/ROS2-Sensor-Fusion-with-Kalman-Filter-for-Real-Time-Multi-Sensor-Integration (1\u2605) \u2014 This project delivers a robust ROS2 sensor fusion framework using the Kalman Estimator to integrate multiple sensor data streams in real-time. It improves perception accuracy by filtering noise and pr", "url": "https://github.com/RadwaElsobki/ROS2-Sensor-Fusion-with-Kalman-Filter-for-Real-Time-Multi-Sensor-Integration", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:sothulthorn--mcformer", "kind": "repo", "label": "sothulthorn/MCFormer (2\u2605) \u2014 Unofficial PyTorch reimplementation of \"The bearing multi-sensor fault diagnosis method based on a multi-branch parallel perception network and feature fusion strategy\" (Reliability Engineering and Sy", "url": "https://github.com/sothulthorn/MCFormer", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:qeyphen--ekfcore", "kind": "repo", "label": "Qeyphen/EKFCore (1\u2605) \u2014 A template-based Extended Kalman Filter for N-dimensional state estimation and multi-sensor fusion in robotics and control.", "url": "https://github.com/Qeyphen/EKFCore", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:awakenfury--cyber-bio-neural-perception-hud", "kind": "repo", "label": "AwakenFury/Cyber-Bio-Neural-Perception-HUD (0\u2605) \u2014 This system is a prototype neural-sensor fusion engine under active development. It is not stable, not production-ready, and will change significantly over time. The goal is to explore real-time multi", "url": "https://github.com/AwakenFury/Cyber-Bio-Neural-Perception-HUD", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:dabbuharshini--autosense", "kind": "repo", "label": "dabbuharshini/AutoSense (0\u2605) \u2014 AutoSense \u2013 A multi-sensor fusion system for autonomous perception using camera, LiDAR, radar, GPS, and IMU data with deep learning\u2013based anomaly detection and trajectory prediction.", "url": "https://github.com/dabbuharshini/AutoSense", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:aminetouiouel--digital-twin-acc-sensor-fusion", "kind": "repo", "label": "aminetouiouel/Digital-Twin-ACC-Sensor-Fusion (0\u2605) \u2014 This repository contains the implementation of an Adaptive Cruise Control (ACC) system based on multi-sensor fusion for autonomous vehicles. The system integrates data from multiple sensors including ", "url": "https://github.com/aminetouiouel/Digital-Twin-ACC-Sensor-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:sania01082002--enhancing-autonomous-vehicle-capabilities-for-inclement-weather-conditions", "kind": "repo", "label": "Sania01082002/Enhancing-Autonomous-Vehicle-Capabilities-for-Inclement-Weather-Conditions (0\u2605) \u2014 A multi-sensor fusion system combining camera, LiDAR, and radar to improve autonomous vehicle perception in rain and fog. Includes Faster R-CNN, YOLOv2, radar clustering, JPDA tracking, and weather si", "url": "https://github.com/Sania01082002/Enhancing-Autonomous-Vehicle-Capabilities-for-Inclement-Weather-Conditions", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:slowakp--arm-ros-gaz-data", "kind": "repo", "label": "slowakp/arm-ros-gaz-data (0\u2605) \u2014 This repository contains a ROS 2 + Gazebo Classic simulation environment for controlled generation of multi-sensor data from a mobile robotic platform. The project is designed primarily for research, ", "url": "https://github.com/slowakp/arm-ros-gaz-data", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:nithineeswar--profile", "kind": "repo", "label": "nithineeswar/profile (0\u2605) \u2014 I am Nithin Eswarappa, Research Associate in DRDO sanctioned, Multi Sensor Image Fusion Lab, GITAM University, Bengaluru. My research interests are in the fields of computer vision, machine learning, ", "url": "https://github.com/nithineeswar/profile", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:cci9--ioucalculation", "kind": "repo", "label": "cci9/IOUCalculation (19\u2605) \u2014 IOU Calculation for 2D Quadrilaterals  The major functional components of autonomous vehicles are perception, control, planning, system management, and localization. Perception is a process that sense", "url": "https://github.com/cci9/IOUCalculation", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:chinmayak1197--visual-sensor-fusion", "kind": "repo", "label": "Chinmayak1197/Visual-Sensor-Fusion (3\u2605) \u2014 Combining RGB Camera and LiDAR point cloud data for object detection. ", "url": "https://github.com/Chinmayak1197/Visual-Sensor-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:guigor020--lidar-camera-sensor-fusion", "kind": "repo", "label": "Guigor020/LiDAR-Camera-Sensor-Fusion (0\u2605) \u2014 Implementation of a Sensor Fusion algorithm for Autonomous Driving using the KITTI dataset. Solved the problem of associating semantic 2D camera data (Object Detection) with precise 3D geometric infor", "url": "https://github.com/Guigor020/LiDAR-Camera-Sensor-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:umtclskn--carla-similator-collision-avoidance-module", "kind": "repo", "label": "umtclskn/Carla-Similator-Collision-Avoidance-Module (2\u2605) \u2014 Implement a Sample Collision-Detection-System / Collision-Avoidance-System. Running on Carla Simulator. Based on Sensor Fusion Camera & Lidar point cloud datas. Open3D,Carla Python Api, OpenCV", "url": "https://github.com/umtclskn/Carla-Similator-Collision-Avoidance-Module", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:charithlegend--lidar-camera-sensor-fusion-for-3d-object-detection-and-depth-estimation", "kind": "repo", "label": "Charithlegend/LiDAR-Camera-Sensor-Fusion-for-3D-Object-Detection-and-Depth-Estimation (0\u2605) \u2014 LiDAR-camera sensor fusion pipeline using YOLO instance segmentation and Velodyne point clouds on KITTI. Estimates depth via 5th percentile inlier filtering, evaluates bleed-out, and benchmarks YOLOv8", "url": "https://github.com/Charithlegend/LiDAR-Camera-Sensor-Fusion-for-3D-Object-Detection-and-Depth-Estimation", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:bhuvan-belliyappa--object-level-sensor-data-fusion-for-road-user-detection-and-motion-prediction-", "kind": "repo", "label": "bhuvan-belliyappa/Object-level-sensor-data-fusion-for-road-user-detection-and-motion-prediction- (1\u2605) \u2014 \u2022 Developed a custom DBSCAN algorithm to effectively cluster RADAR point clouds, improving data analysis accuracy.  \u2022 Retrained an object detection YOLO v8 model, tailoring it to meet specific app", "url": "https://github.com/bhuvan-belliyappa/Object-level-sensor-data-fusion-for-road-user-detection-and-motion-prediction-", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:addykore--road-detection-through-sensor-fusion-with-fully-convolutional-neural-networks", "kind": "repo", "label": "AddyKore/Road-Detection-through-Sensor-Fusion-with-Fully-Convolutional-Neural-Networks (1\u2605) \u2014 The work consists of Fully convoluted neural networks(FCNs) which are trained to carry out road detection by using one of the three input types as follows: RGB image of the scene, RGB image with a LID", "url": "https://github.com/AddyKore/Road-Detection-through-Sensor-Fusion-with-Fully-Convolutional-Neural-Networks", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:rajaasimmustafa--3d-lidar-object-detection-dbscan-kitti", "kind": "repo", "label": "rajaasimmustafa/3D-LiDAR-Object-Detection-DBSCAN-KITTI (0\u2605) \u2014 3D LiDAR Object Detection: ROS based project jismein 3D point cloud preprocessing, clustering (Euclidean/DBSCAN) aur bounding box generation hota hai. Dataset support (KITTI), visualization in RViz, a", "url": "https://github.com/rajaasimmustafa/3D-LiDAR-Object-Detection-DBSCAN-KITTI", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:gpanero--sensorfusionandtracking", "kind": "repo", "label": "GPanero/SensorFusionAndTracking (1\u2605) \u2014 This is the project for the Udacity Self-Driving Car Engineer Nanodegree Program : Sensor Fusion and Tracking.  In this project, LiDAR and camera and track vehicles over time. will be fused, object de", "url": "https://github.com/GPanero/SensorFusionAndTracking", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:tumftm--dpft", "kind": "repo", "label": "TUMFTM/DPFT (95\u2605) \u2014 Dual Perspective Fusion Transformer for Camera-Radar-based Object Detection", "url": "https://github.com/TUMFTM/DPFT", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:purduedigitaltwin--redformer", "kind": "repo", "label": "PurdueDigitalTwin/REDFormer (61\u2605) \u2014 [ITSC 23] Official codebase for the paper 'Radar Enlighten the Dark: Enhancing Low-Visibility Perception for Automated Vehicles with Camera-Radar Fusion", "url": "https://github.com/PurdueDigitalTwin/REDFormer", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:vanjeebeiyandeepmodeldevelopinggroup--innovusion_lidar_camera_radar_last_stage_fusion_perception", "kind": "repo", "label": "VanjeeBeiyanDeepModelDevelopingGroup/Innovusion_Lidar_Camera_Radar_Last_Stage_Fusion_Perception (9\u2605)", "url": "https://github.com/VanjeeBeiyanDeepModelDevelopingGroup/Innovusion_Lidar_Camera_Radar_Last_Stage_Fusion_Perception", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:kar-ab--ad_sensor_fusion", "kind": "repo", "label": "kar-ab/AD_Sensor_Fusion (13\u2605) \u2014 Sensor Fusion of Perception sensors ( Camera, Lidar and Radar) in Autonomous Driving", "url": "https://github.com/kar-ab/AD_Sensor_Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:collector-m--sensor_fusion", "kind": "repo", "label": "collector-m/Sensor_Fusion (7\u2605) \u2014 Detect obstacles in lidar point clouds through clustering and segmentation. Apply thresholds and filters to radar data in order to accurately track objects, and augment your perception by projecting c", "url": "https://github.com/collector-m/Sensor_Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:guihaik--rcperception", "kind": "repo", "label": "guihaik/RCPerception (4\u2605) \u2014 This repository is the paperlist on Perception Algorithms for Radar and Camera Fusion.", "url": "https://github.com/guihaik/RCPerception", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:hrid16-32572-2--radar-camera-fusion-3d-perception", "kind": "repo", "label": "Hrid16-32572-2/radar-camera-fusion-3d-perception (0\u2605)", "url": "https://github.com/Hrid16-32572-2/radar-camera-fusion-3d-perception", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:zhinengz--sensor_fusion", "kind": "repo", "label": "zhinengz/Sensor_Fusion (4\u2605) \u2014 Detect obstacles in lidar point clouds through clustering and segmentation. Apply thresholds and filters to radar data in order to accurately track objects, and augment your perception by projecting c", "url": "https://github.com/zhinengz/Sensor_Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:cc-owner--rcdbf", "kind": "repo", "label": "CC-owner/RCDBF (0\u2605) \u2014 The  official implementation of RCDBF, our novel 4D radar-camera fusion architecture for 3D perception. ", "url": "https://github.com/CC-owner/RCDBF", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:xiaorun2345--traffic_event", "kind": "repo", "label": "xiaorun2345/Traffic_Event (1\u2605) \u2014 RK3588-based camera perception and camera-radar fusion process with RTSP   ingestion, RKNN object detection, tracking, localization, UDP reporting, and   LED warning integration.", "url": "https://github.com/xiaorun2345/Traffic_Event", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:330012--av-sensor-fusion", "kind": "repo", "label": "330012/av-sensor-fusion (0\u2605) \u2014 Hands-on exploration of multi-modal AV sensor data \u2014 processing and aligning camera and radar samples from the nuScenes dataset to understand cross-modal fusion fundamentals for autonomous driving per", "url": "https://github.com/330012/av-sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:omaremadaldin--end_to_end_perception_pipeline_with_3d_detection_tracking", "kind": "repo", "label": "OmarEmadAldin/End_to_End_perception_pipeline_with_3d_detection_tracking (0\u2605) \u2014 In This Repo I made an End to End solution for perception stack using the Nuscenes dataset and using all camera , lidar and radar data for detection , fusion and tracking the objects", "url": "https://github.com/OmarEmadAldin/End_to_End_perception_pipeline_with_3d_detection_tracking", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:thuvaragak--carla_project", "kind": "repo", "label": "thuvaragak/carla_project (0\u2605) \u2014 Developing an Enhanced Perception system in CARLA using ROS 2, integrating LiDAR, radar, and camera data for sensor fusion, real-time object tracking, and visualization using Open3D.", "url": "https://github.com/thuvaragak/carla_project", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:sguha16--multimodal-fusion-agent-negotiation", "kind": "repo", "label": "sguha16/multimodal-fusion-agent-negotiation (0\u2605) \u2014 Multi-agent sensor fusion for autonomous driving perception. Radar processes raw ADC \u2192 CFAR \u2192 DBSCAN clustering. Camera runs YOLOv8 detection. Cross-modal matching with 2-round LLM negotiation for dis", "url": "https://github.com/sguha16/multimodal-fusion-agent-negotiation", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:shrutik-panchal--masters-thesis-multimodal-feature-extraction-and-fusion", "kind": "repo", "label": "shrutik-panchal/masters-thesis-multimodal-feature-extraction-and-fusion (1\u2605) \u2014 Master\u2019s thesis repository exploring multimodal feature extraction and fusion techniques using the NuScenes dataset. The work investigates representation learning across camera, LiDAR, and radar data,", "url": "https://github.com/shrutik-panchal/masters-thesis-multimodal-feature-extraction-and-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:11rahi23--gusramoc", "kind": "repo", "label": "11rahi23/GUSRaMoC (0\u2605) \u2014 This is a sensor fusion model for improved 3D perception and obstacle avoidance on segmented terrain through a novel architecture. The system utilizes a Gaussian Uncertainty-based single Radar and sin", "url": "https://github.com/11rahi23/GUSRaMoC", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:opendilab--interfuser", "kind": "repo", "label": "opendilab/InterFuser (653\u2605) \u2014 [CoRL 2022] InterFuser: Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer", "url": "https://github.com/opendilab/InterFuser", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:virtual-vehicle--aa274_autoware_ws", "kind": "repo", "label": "virtual-vehicle/aa274_autoware_ws (34\u2605) \u2014 Hands-On example code for Sensor Fusion and Autonomous Driving Stack based on Autoware ", "url": "https://github.com/virtual-vehicle/aa274_autoware_ws", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:superxiaoying--autonomous_vehicle_paper_reading_list", "kind": "repo", "label": "superxiaoying/Autonomous_Vehicle_Paper_Reading_List (15\u2605) \u2014 A collection of papers focus on self-driving car. Many topics are covered including computer vison, sensor fusion, SLAM, decision and planning. The paper list will be timely updated. ", "url": "https://github.com/superxiaoying/Autonomous_Vehicle_Paper_Reading_List", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:say2l--gaussianfusion", "kind": "repo", "label": "Say2L/GaussianFusion (93\u2605) \u2014 [NeurIPS2025 Spotlight] Implementation of \"GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous Driving\"", "url": "https://github.com/Say2L/GaussianFusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:cmvs-lab--sac-residual-fusion-carla", "kind": "repo", "label": "CMVS-Lab/SAC-Residual-Fusion-CARLA (18\u2605) \u2014 Autonomous Driving using Residual Sensor Fusion and Deep Reinforcement Learning (ICROM, 2023)", "url": "https://github.com/CMVS-Lab/SAC-Residual-Fusion-CARLA", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:cakwok--autonomous-driving", "kind": "repo", "label": "cakwok/Autonomous-Driving (11\u2605) \u2014 Scene Understanding in autonomous driving by sensor fusion.  Detected vehicles and 3D objects from LiDAR sensor range images by building BEV vector space, tracked multiple objects using extended Kalma", "url": "https://github.com/cakwok/Autonomous-Driving", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:manojkannan0803--autonomous-driving-controls", "kind": "repo", "label": "Manojkannan0803/Autonomous-Driving-Controls (5\u2605) \u2014 Projects covering numerical ODE integration, PID, Kinematic vehicle modeling, sensor fusion (EKF), optimal control (LQR/MPC), motion planning (A*), and a fully integrated closed loop AV stack.", "url": "https://github.com/Manojkannan0803/Autonomous-Driving-Controls", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:visionpilot-project--visionpilot", "kind": "repo", "label": "visionpilot-project/VisionPilot (28\u2605) \u2014 Open-source modular autonomous driving simulation platform with computer vision, deep learning, and sensor fusion. Features lane detection, object recognition, various safety features, and adaptive co", "url": "https://github.com/visionpilot-project/VisionPilot", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:janudis--extented-kalman-filter-lidar-gps-imu", "kind": "repo", "label": "Janudis/Extented-Kalman-Filter-LIDAR-GPS-IMU (15\u2605) \u2014 Sensor Fusion of LiDAR, GPS and IMU with Extended Kalman Filter for Localization in Autonomous Driving.", "url": "https://github.com/Janudis/Extented-Kalman-Filter-LIDAR-GPS-IMU", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:yousefmansy--autonomous-highway-driving", "kind": "repo", "label": "YousefMansy/Autonomous-Highway-Driving (5\u2605) \u2014 The goal of this project is to design a path planner that is able to create smooth, safe paths for the car to follow along a 3 lane highway with traffic. A successful path planner will be able to keep", "url": "https://github.com/YousefMansy/Autonomous-Highway-Driving", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:loki-silvres--autonomous-driving-b3rb-buggy", "kind": "repo", "label": "Loki-Silvres/Autonomous-Driving-B3RB-buggy (2\u2605) \u2014 Autonomous Driving project for exploration of robotic perception, sensor fusion and autonomous navigation.", "url": "https://github.com/Loki-Silvres/Autonomous-Driving-B3RB-buggy", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:gopi-erabati--msf3ddetr", "kind": "repo", "label": "gopi-erabati/MSF3DDETR (4\u2605) \u2014 Official PyTorch implementation of the paper MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer for Autonomous Driving", "url": "https://github.com/gopi-erabati/MSF3DDETR", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:yashstudy2025-collab--sensor-fusion-autonomous-driving", "kind": "repo", "label": "yashstudy2025-collab/sensor-fusion-autonomous-driving (0\u2605)", "url": "https://github.com/yashstudy2025-collab/sensor-fusion-autonomous-driving", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:chandru-python--multi-sensor-data-fusion", "kind": "repo", "label": "chandru-python/multi-sensor-data-fusion (3\u2605) \u2014 This project performs real-time LiDAR\u2013camera sensor fusion to track object distance in autonomous driving scenarios. By applying calibration, 3D projection, and Kalman filtering, the system ensures re", "url": "https://github.com/chandru-python/multi-sensor-data-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:jeswanth-kanipakam--ros2-bumperbot", "kind": "repo", "label": "Jeswanth-Kanipakam/ROS2-Bumperbot (3\u2605) \u2014 Developing an autonomous self-driving robot using ROS2 and Python, focusing on odometry, control systems, and sensor fusion. Kalman Filters combine data from LiDAR, IMU, and cameras for enhanced local", "url": "https://github.com/Jeswanth-Kanipakam/ROS2-Bumperbot", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ece257b--sensor-fusion-for-autonomous-driving", "kind": "repo", "label": "ece257b/Sensor-Fusion-for-Autonomous-Driving (1\u2605) \u2014 P2SIF platform for sensor fusion in autonomous driving", "url": "https://github.com/ece257b/Sensor-Fusion-for-Autonomous-Driving", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:marianocaccavale--sensorfusion", "kind": "repo", "label": "MarianoCaccavale/SensorFusion (2\u2605) \u2014 C++ Ros2 node for sensor fusion of various data from different source, namely stereo-camera cones detection and LiDAR cones detections. Build in a larger context of a autonomous driving system for a F", "url": "https://github.com/MarianoCaccavale/SensorFusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:basictask--sensorfusion", "kind": "repo", "label": "basictask/SensorFusion (0\u2605) \u2014 3D Sensor Fusion Applications to support modeling, autonomous driving", "url": "https://github.com/basictask/SensorFusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:highsky7--my_project_work_ws", "kind": "repo", "label": "Highsky7/My_project_work_ws (7\u2605) \u2014 This repository contains a collection of ROS (Robot Operating System) based projects focused on autonomous driving, computer vision, and sensor fusion. It includes algorithms for perceiving the enviro", "url": "https://github.com/Highsky7/My_project_work_ws", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ronitsharan--autonomousdriving", "kind": "repo", "label": "ronitsharan/AutonomousDriving (0\u2605) \u2014 Open source and online coursework algorithms related to computer vision, sensor fusion, localizatio, planning and control related to autonomous vehicles", "url": "https://github.com/ronitsharan/AutonomousDriving", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:adamai-systems--autonomous", "kind": "repo", "label": "AdamAI-Systems/Autonomous (0\u2605) \u2014 Exploring autonomous intelligence through robotics, self-driving systems, sensor fusion, perception, planning, and decision-making.", "url": "https://github.com/AdamAI-Systems/Autonomous", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:aryanp2107--autonomous-perception-ensemble", "kind": "repo", "label": "aryanp2107/Autonomous-Perception-Ensemble (0\u2605) \u2014 Multi-model sensor fusion for autonomous driving scene understanding", "url": "https://github.com/aryanp2107/Autonomous-Perception-Ensemble", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:ra9hur--udacity-self-driving-car-nd-term2", "kind": "repo", "label": "ra9hur/Udacity-Self-Driving-Car-ND-Term2 (3\u2605) \u2014 To build the core robotic functions of an autonomous vehicle system: sensor fusion, localization and control. README includes GitHub repository links for 5 successfully completed projects.", "url": "https://github.com/ra9hur/Udacity-Self-Driving-Car-ND-Term2", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:robot-park--slam", "kind": "repo", "label": "robot-park/SLAM (0\u2605) \u2014 Lidar-Camera sensor fusion for autonomous driving", "url": "https://github.com/robot-park/SLAM", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:nikhil-xavier-ds--self_driving_car----sensor-fusion-localization---control", "kind": "repo", "label": "Nikhil-Xavier-DS/Self_Driving_Car----Sensor-Fusion-Localization---Control (1\u2605) \u2014 Sensor Fusion, Localization & Control projects for Autonomous Vehicles", "url": "https://github.com/Nikhil-Xavier-DS/Self_Driving_Car----Sensor-Fusion-Localization---Control", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:zar-e--sensor-fusion", "kind": "repo", "label": "zar-e/Sensor-Fusion (0\u2605) \u2014 A research into Sensor Fusion for Decision-Making in Autonomous Driving Systems", "url": "https://github.com/zar-e/Sensor-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:aryankrowser--early-sensor-fusion-and-object-detection-fro-autonomous-driving", "kind": "repo", "label": "aryankrowser/early-sensor-fusion-and-object-detection-fro-autonomous-driving (0\u2605)", "url": "https://github.com/aryankrowser/early-sensor-fusion-and-object-detection-fro-autonomous-driving", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:manvithmadhuvarsu--multimodal-autonomous-driving-ssl-pipeline", "kind": "repo", "label": "ManvithMadhuvarsu/multimodal-autonomous-driving-ssl-pipeline (0\u2605) \u2014 End-to-End multimodal autonomous driving pipeline with SSL, sensor fusion, GNN, RL, and inference modules.", "url": "https://github.com/ManvithMadhuvarsu/multimodal-autonomous-driving-ssl-pipeline", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:vadhri--cps-notebook", "kind": "repo", "label": "vadhri/cps-notebook (0\u2605) \u2014 Cyber physical systems - Sensor fusion, Robotics, Autonomous driving", "url": "https://github.com/vadhri/cps-notebook", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:adam-shawky23--autonomous-driving-simulator", "kind": "repo", "label": "Adam-Shawky23/autonomous-driving-simulator (0\u2605) \u2014 Grid-based autonomous driving simulator (C++17) with multi-modal sensor fusion,  waypoint navigation, traffic reasoning, and deterministic replay. Features FOV-based  perception, confidence-weighted f", "url": "https://github.com/Adam-Shawky23/autonomous-driving-simulator", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:michil91--adas-sensor-fusion", "kind": "repo", "label": "michil91/adas-sensor-fusion (0\u2605) \u2014 Sensor fusion prototype with VRU-aware safety classification and weather degradation analysis for autonomous driving", "url": "https://github.com/michil91/adas-sensor-fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:dawoodkhan9478--transformer-based-multi-modal-sensor-fusion-for-autonomous-driving-in-carla", "kind": "repo", "label": "Dawoodkhan9478/Transformer-Based-Multi-Modal-Sensor-Fusion-for-Autonomous-Driving-in-CARLA (0\u2605)", "url": "https://github.com/Dawoodkhan9478/Transformer-Based-Multi-Modal-Sensor-Fusion-for-Autonomous-Driving-in-CARLA", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:saanindia--adas-gpu-sensor-fusion-cuda", "kind": "repo", "label": "saanindia/ADAS-GPU-Sensor-Fusion-Cuda (0\u2605) \u2014 A simplified autonomous driving perception pipeline demonstrating GPU acceleration for sensor fusion workloads.", "url": "https://github.com/saanindia/ADAS-GPU-Sensor-Fusion-Cuda", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:dloc19--autonomous-driving-", "kind": "repo", "label": "dloc19/Autonomous-driving- (0\u2605) \u2014 \u0110\u1ed3 \u00e1n xe t\u1ef1 h\u00e0nh s\u1eed d\u1ee5ng CARLA 0.9.13 Simulator + PyTorch.   T\u1eadp trung v\u00e0o **Perception Pipeline**: Image Processing, Object Detection, Semantic Segmentation, Lane Detection, v\u00e0 Camera-LiDAR Sensor Fu", "url": "https://github.com/dloc19/Autonomous-driving-", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:quantumgizmos--bp_osd", "kind": "repo", "label": "quantumgizmos/bp_osd (107\u2605) \u2014 BP+OSD: Belief propagation with ordered statistics post-processing for decoding quantum LDPC codes", "url": "https://github.com/quantumgizmos/bp_osd", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:kit-cel--quantum-neural-bp4-demo", "kind": "repo", "label": "kit-cel/Quantum-Neural-BP4-demo (24\u2605) \u2014 Implementation of Neural Belief propagation decoder for QLDPC codes", "url": "https://github.com/kit-cel/Quantum-Neural-BP4-demo", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:weileizeng--belief-propagation", "kind": "repo", "label": "WeileiZeng/belief-propagation (0\u2605) \u2014 Using belief propagation to decode quantum codes", "url": "https://github.com/WeileiZeng/belief-propagation", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:yysf-brait--css_make", "kind": "repo", "label": "yysf-brait/css_make (4\u2605) \u2014 A Python package of the successor to `bp_osd`. Belief propagation with ordered statistics post-processing for decoding quantum LDPC codes.", "url": "https://github.com/yysf-brait/css_make", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:serco712--bplp", "kind": "repo", "label": "serco712/BPLP (0\u2605) \u2014 Belief Propagation and Linear Programming decoders for Quantum Error Correction", "url": "https://github.com/serco712/BPLP", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:maltmn--quantumldpc", "kind": "repo", "label": "maltmn/QuantumLDPC (0\u2605) \u2014 Comparing quantum error decoders: Belief Propagation, Feed Forward Neural Network, and the Astra Graph Neural Network", "url": "https://github.com/maltmn/QuantumLDPC", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:aumpatel07--quantum-error-correction", "kind": "repo", "label": "Aumpatel07/quantum-error-correction (1\u2605) \u2014 This repo contains code for a decoder based on belief propagation. The decoder also uses ordered statistics for choice of most probable error vector. Simulation of decoder on color and surface codes h", "url": "https://github.com/Aumpatel07/quantum-error-correction", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:zynerji--qec", "kind": "repo", "label": "Zynerji/QEC (0\u2605) \u2014 Dirac Ternary Quantum Error Correction \u2014 fractal soft-decision decoding with dark-memory belief propagation. Validated on IBM Marrakesh.", "url": "https://github.com/Zynerji/QEC", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:musikavanhu--biomimetic-quantum-error-correction-simulation", "kind": "repo", "label": "Musikavanhu/Biomimetic-Quantum-Error-Correction-simulation (0\u2605) \u2014 Re-evaluated the architectural logic of Quantum Error Correction (QEC) for classical sensor networks using rigorous, standard coding theory frameworks. The simulation benchmarks the Biomimetic QEC-Log", "url": "https://github.com/Musikavanhu/Biomimetic-Quantum-Error-Correction-simulation", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:dies-irae--bp-sf", "kind": "repo", "label": "Dies-Irae/BP-SF (6\u2605) \u2014 Source code for \"Fully Parallelized BP Decoding for Quantum LDPC Codes Can Outperform BP-OSD\" (HPCA 2026))", "url": "https://github.com/Dies-Irae/BP-SF", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:guillaumelessard--qector-decoder", "kind": "repo", "label": "GuillaumeLessard/qector-decoder (0\u2605) \u2014 Source-available Rust/Python quantum error correction decoder package with MWPM, Union-Find, BP-OSD, LDPC/qLDPC, CUDA batch decoding, PyMatching/Stim validation, and reproducible benchmark artifacts.", "url": "https://github.com/GuillaumeLessard/qector-decoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:quantumgizmos--ldpc", "kind": "repo", "label": "quantumgizmos/ldpc (214\u2605) \u2014 Software for decoding classical and quantum codes", "url": "https://github.com/quantumgizmos/ldpc", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:qldpcorg--qldpc", "kind": "repo", "label": "qLDPCOrg/qLDPC (238\u2605) \u2014 Tools for constructing and analyzing quantum low density parity check (qLDPC) codes.  Also stabilizer and subsystem codes more broadly.", "url": "https://github.com/qLDPCOrg/qLDPC", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:quantumgizmos--bias_tailored_qldpc", "kind": "repo", "label": "quantumgizmos/bias_tailored_qldpc (36\u2605) \u2014 Biased-tailored quantum LDPC codes", "url": "https://github.com/quantumgizmos/bias_tailored_qldpc", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:yuewuo--mwpf", "kind": "repo", "label": "yuewuo/mwpf (46\u2605) \u2014 Hypergraph Minimum-Weight Parity Factor (MWPF) Algorithm for Decoding General Quantum LDPC Codes", "url": "https://github.com/yuewuo/mwpf", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:seokhyung-lee--ldpc-post-selection", "kind": "repo", "label": "seokhyung-lee/ldpc-post-selection (9\u2605) \u2014 Python package for decoding quantum LDPC codes with cluster-based post-selection", "url": "https://github.com/seokhyung-lee/ldpc-post-selection", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:kasaikenta--gd-css-decoder", "kind": "repo", "label": "kasaikenta/gd-css-decoder (8\u2605) \u2014 Quantum error correction based on non-binary LDPC codes", "url": "https://github.com/kasaikenta/gd-css-decoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:diegoruiz-git--ldpcat", "kind": "repo", "label": "DiegoRuiz-Git/LDPCat (3\u2605) \u2014 Code for the LDPC-cat qubit architecture presented in the article 'LDPC-cat codes for low-overhead quantum computing in 2D'", "url": "https://github.com/DiegoRuiz-Git/LDPCat", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:perlinm--qldpc", "kind": "repo", "label": "perlinm/qLDPC (12\u2605) \u2014 Tools for constructing and analyzing quantum low density partity check (qLDPC) codes.", "url": "https://github.com/perlinm/qLDPC", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:maxtremblay--ldpc", "kind": "repo", "label": "maxtremblay/ldpc (7\u2605) \u2014 A set of data structure for classical and quantum LDPC codes", "url": "https://github.com/maxtremblay/ldpc", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:quantumsavory--pyqdecoders.jl", "kind": "repo", "label": "QuantumSavory/PyQDecoders.jl (9\u2605) \u2014 A Julia interface to popular python packages for decoding quantum error correcting codes.", "url": "https://github.com/QuantumSavory/PyQDecoders.jl", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:samyak-surti--qldpccodesim", "kind": "repo", "label": "Samyak-Surti/QLDPCCodeSim (4\u2605) \u2014 Simulating Quantum LDPC Codes", "url": "https://github.com/Samyak-Surti/QLDPCCodeSim", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:qec-pages--quantum_ldpc_codes", "kind": "repo", "label": "QEC-pages/Quantum_LDPC_Codes (3\u2605) \u2014 Collection of quantum LDPC codes", "url": "https://github.com/QEC-pages/Quantum_LDPC_Codes", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:qiskit-community--qcode-discovery", "kind": "repo", "label": "qiskit-community/qcode-discovery (15\u2605) \u2014 Discovering bivariate bicycle (BB) and perturbed bivariate bicycle (PBB) quantum LDPC codes via LLM-guided evolutionary search.", "url": "https://github.com/qiskit-community/qcode-discovery", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:iqubit-org--auto-stabilizer-check", "kind": "repo", "label": "iqubit-org/Auto-Stabilizer-Check (9\u2605) \u2014 DATE 2026: Auto-Stabilizer-Check: Optimal Compilation of Syndrome Extraction Circuits for General Quantum LDPC Codes", "url": "https://github.com/iqubit-org/Auto-Stabilizer-Check", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:kasaikenta--quantum-ldpc-decoder", "kind": "repo", "label": "kasaikenta/quantum-ldpc-decoder (2\u2605) \u2014 Decoder and P=32 CPM-lifted code data for arXiv:2604.20838", "url": "https://github.com/kasaikenta/quantum-ldpc-decoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:punkdit--ldpc2018", "kind": "repo", "label": "punkdit/ldpc2018 (0\u2605) \u2014 ideas about quantum ldpc codes", "url": "https://github.com/punkdit/ldpc2018", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:aleverrier--frontier", "kind": "repo", "label": "aleverrier/frontier (15\u2605) \u2014 Frontier decoder for quantum LDPC codes: pruned dynamic programming over boundary states for approximate logical maximum-likelihood decoding of sparse parity-check and detector-error-model matrices.", "url": "https://github.com/aleverrier/frontier", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:mdwoolls--quantumldpccodelist", "kind": "repo", "label": "MDWoolls/QuantumLDPCCodeList (1\u2605) \u2014 List of LDPC codes found.", "url": "https://github.com/MDWoolls/QuantumLDPCCodeList", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:prismaticflame--qec_decoder_transformer", "kind": "repo", "label": "PrismaticFlame/qec_decoder_transformer (0\u2605) \u2014 A quantum error correction decoder with a recurrent, transformer based neural network that works on the surface code.", "url": "https://github.com/PrismaticFlame/qec_decoder_transformer", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:quantumlib--tesseract-decoder", "kind": "repo", "label": "quantumlib/tesseract-decoder (113\u2605) \u2014 Search-based decoder for quantum error correction (QEC) written in C++ and Python.", "url": "https://github.com/quantumlib/tesseract-decoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:quantumlib--chromobius", "kind": "repo", "label": "quantumlib/chromobius (35\u2605) \u2014 Open-source implementation of a M\u00f6bius decoder for color codes used in quantum error correction (QEC)", "url": "https://github.com/quantumlib/chromobius", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:panqec--panqec", "kind": "repo", "label": "panqec/panqec (87\u2605) \u2014 Simulation and visualization of quantum error correcting codes", "url": "https://github.com/panqec/panqec", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:winfred666--surfacecode-mwpmdecoder", "kind": "repo", "label": "Winfred666/SurfaceCode-MWPMDecoder (0\u2605) \u2014 A newbie study on pymatching and MWPM Decoder in quantum informatics subject.", "url": "https://github.com/Winfred666/SurfaceCode-MWPMDecoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:dhruvbhq--surf_code_sim", "kind": "repo", "label": "dhruvbhq/surf_code_sim (0\u2605) \u2014 Program to simulate threshold of rotated surface code. The error model is one stochastic Pauli error after \"encoding\". The decoding algorithm is MWPM implemented in Pymatching package.", "url": "https://github.com/dhruvbhq/surf_code_sim", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:ariawu34--qec-surface-code-simulation", "kind": "repo", "label": "AriaWu34/qec-surface-code-simulation (0\u2605) \u2014 Modular quantum error correction simulator built in Python and Qiskit, featuring repetition codes, planar surface codes, configurable noise models, MWPM decoding, Monte Carlo benchmarking, and ongoing", "url": "https://github.com/AriaWu34/qec-surface-code-simulation", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:tqec--tqec", "kind": "repo", "label": "tqec/tqec (375\u2605) \u2014 Design automation software tools for Topological Quantum Error Correction", "url": "https://github.com/tqec/tqec", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:qiskit-community--qiskit-qec", "kind": "repo", "label": "qiskit-community/qiskit-qec (121\u2605) \u2014 Qiskit quantum error correction framework", "url": "https://github.com/qiskit-community/qiskit-qec", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:qiskit-community--qiskit-ignis", "kind": "repo", "label": "qiskit-community/qiskit-ignis (170\u2605) \u2014 Ignis (deprecated) provides tools for quantum hardware verification, noise characterization, and error correction.", "url": "https://github.com/qiskit-community/qiskit-ignis", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:deltakit--deltakit", "kind": "repo", "label": "Deltakit/deltakit (60\u2605) \u2014 Riverlane's quantum error correction SDK", "url": "https://github.com/Deltakit/deltakit", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:nvidia--ising-decoding", "kind": "repo", "label": "NVIDIA/Ising-Decoding (107\u2605) \u2014 A set of training recipes for AI Quantum Error Correction Decoders", "url": "https://github.com/NVIDIA/Ising-Decoding", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:latticesurgery-com--lattice-surgery-compiler", "kind": "repo", "label": "latticesurgery-com/lattice-surgery-compiler (85\u2605) \u2014 Lattice surgery quantum error correction compiler", "url": "https://github.com/latticesurgery-com/lattice-surgery-compiler", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:cgranade--python-quaec", "kind": "repo", "label": "cgranade/python-quaec (49\u2605) \u2014 A library for working with quantum error correction.", "url": "https://github.com/cgranade/python-quaec", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:yuewuo--fusion-blossom", "kind": "repo", "label": "yuewuo/fusion-blossom (83\u2605) \u2014 A fast minimum-weight perfect matching solver for quantum error correction", "url": "https://github.com/yuewuo/fusion-blossom", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:jolle-ag--qdx", "kind": "repo", "label": "jolle-ag/qdx (47\u2605) \u2014 Quantum error correction code AI-discovery with Jax", "url": "https://github.com/jolle-ag/qdx", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:qecsim--qecsim", "kind": "repo", "label": "qecsim/qecsim (95\u2605) \u2014 qecsim is a Python 3 package for simulating quantum error correction using stabilizer codes.", "url": "https://github.com/qecsim/qecsim", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:nzy1997--tensorqec.jl", "kind": "repo", "label": "nzy1997/TensorQEC.jl (71\u2605) \u2014 Tensor networks for quantum error correction.", "url": "https://github.com/nzy1997/TensorQEC.jl", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:pecos-packages--pecos", "kind": "repo", "label": "PECOS-packages/PECOS (56\u2605) \u2014 Software for exploring, developing, and evaluating quantum error-correction protocols.", "url": "https://github.com/PECOS-packages/PECOS", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:saashajoshi--quantum-computing", "kind": "repo", "label": "SaashaJoshi/quantum-computing (13\u2605) \u2014 Quantum Algorithms and Quantum Error Correction codes.", "url": "https://github.com/SaashaJoshi/quantum-computing", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:yuewuo--micro-blossom", "kind": "repo", "label": "yuewuo/micro-blossom (25\u2605) \u2014 Hardware Accelerated MWPM decoder for Quantum Error Correction", "url": "https://github.com/yuewuo/micro-blossom", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:deltakit--deltakit-textbook", "kind": "repo", "label": "Deltakit/deltakit-textbook (21\u2605) \u2014 Deltakit Textbook: A hands-on introduction to Quantum Error Correction concepts", "url": "https://github.com/Deltakit/deltakit-textbook", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:francois-marie--awesome-quantum-computing-experiments", "kind": "repo", "label": "francois-marie/awesome-quantum-computing-experiments (64\u2605) \u2014 A comprehensive database of notable quantum computing experiments, with emphasis on quantum error correction implementations", "url": "https://github.com/francois-marie/awesome-quantum-computing-experiments", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:chy-i--qecgpt", "kind": "repo", "label": "CHY-i/qecGPT (43\u2605) \u2014 Decoding Quantum Error Correction codes with Generative Pre-trained Transformers", "url": "https://github.com/CHY-i/qecGPT", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:abdullahkhalids--qecft", "kind": "repo", "label": "abdullahkhalids/qecft (20\u2605) \u2014 The book A Methods Focused Guide to Quantum Error Correction and Fault-Tolerant Quantum Computation", "url": "https://github.com/abdullahkhalids/qecft", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:sneakyweasel--genetic-quantum-correction", "kind": "repo", "label": "sneakyweasel/genetic-quantum-correction (8\u2605) \u2014 Solving the decodoku quantum error correction problem with genetic algorithm", "url": "https://github.com/sneakyweasel/genetic-quantum-correction", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:entropicalabs--el-loom", "kind": "repo", "label": "entropicalabs/el-loom (39\u2605) \u2014 Python library for the simplified setup of quantum error correction codes", "url": "https://github.com/entropicalabs/el-loom", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:yuewuo--qec-playground", "kind": "repo", "label": "yuewuo/QEC-Playground (27\u2605) \u2014 An educational tool to the introduction of Quantum Error Correction (QEC)", "url": "https://github.com/yuewuo/QEC-Playground", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:hongyehu--pyclifford", "kind": "repo", "label": "hongyehu/PyClifford (86\u2605) \u2014 An intuitive programming package for simulating and analyzing Clifford-dominated circuits, quantum measurement, and stabilizer states with applications to many-body localization, classical shadows, qu", "url": "https://github.com/hongyehu/PyClifford", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:xanaduai--flamingpy", "kind": "repo", "label": "XanaduAI/flamingpy (60\u2605) \u2014 FlamingPy is a cross-platform Python library with a variety of backends for efficient simulations of error correction in fault-tolerant quantum computers.", "url": "https://github.com/XanaduAI/flamingpy", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:samgodwood--quantum_error_correction", "kind": "repo", "label": "samgodwood/Quantum_Error_Correction (3\u2605)", "url": "https://github.com/samgodwood/Quantum_Error_Correction", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:yezhuoyang--scalerqec", "kind": "repo", "label": "yezhuoyang/ScaLERQEC (14\u2605) \u2014 Scalable testing and verification of logical error rate for all quantum error correction", "url": "https://github.com/yezhuoyang/ScaLERQEC", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:unarylab--syndrilla", "kind": "repo", "label": "UnaryLab/syndrilla (15\u2605) \u2014 A PyTorch-based numerical simulator for decoders in quantum error correction.", "url": "https://github.com/UnaryLab/syndrilla", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:chahak13--quantum-error-correction", "kind": "repo", "label": "chahak13/quantum-error-correction (2\u2605) \u2014 Quantum Error correction codes.", "url": "https://github.com/chahak13/quantum-error-correction", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:socathie--quantum-error-correction", "kind": "repo", "label": "socathie/Quantum-Error-Correction (4\u2605) \u2014 Simulation codes used for a final research project in Quantum Error Correction.", "url": "https://github.com/socathie/Quantum-Error-Correction", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:qec-codes--qec", "kind": "repo", "label": "qec-codes/qec (28\u2605) \u2014 Python Tools for Quantum Error Correction", "url": "https://github.com/qec-codes/qec", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:tahahassan92003--quantum_computing_tackle_noise_with_error_correction", "kind": "repo", "label": "Tahahassan92003/Quantum_Computing_Tackle_Noise_with_Error_Correction (7\u2605) \u2014 This project will explore quantum error correction using the repetition code from Qiskit's guide. We will encode information across multiple qubits to detect and correct bit-flip errors, implement the", "url": "https://github.com/Tahahassan92003/Quantum_Computing_Tackle_Noise_with_Error_Correction", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:the-singularity-research--error-correction", "kind": "repo", "label": "The-Singularity-Research/error-correction (1\u2605) \u2014 Quantum Error Correction", "url": "https://github.com/The-Singularity-Research/error-correction", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:nanleij--the-toric-code", "kind": "repo", "label": "nanleij/The-toric-code (22\u2605) \u2014 The Toric Code (surface code for quantum error correction) together with the MWPM decoder (need a package) and the union-find decoder programmed in python", "url": "https://github.com/nanleij/The-toric-code", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:stavan-jain--qeclean", "kind": "repo", "label": "Stavan-Jain/QECLean (36\u2605) \u2014 Formalization project on Quantum Error Correction in Lean", "url": "https://github.com/Stavan-Jain/QECLean", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:adelshb--graphqec", "kind": "repo", "label": "adelshb/graphqec (18\u2605) \u2014 A library for analyzing Quantum Error Correction Codes from their Tanner Graphs.", "url": "https://github.com/adelshb/graphqec", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:lewis-od--quantumerrorcorrection", "kind": "repo", "label": "lewis-od/QuantumErrorCorrection (9\u2605) \u2014 Implementations of various quantum error correction schemes using QuTiP", "url": "https://github.com/lewis-od/QuantumErrorCorrection", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:phionx--quantumnetworks", "kind": "repo", "label": "Phionx/quantumnetworks (15\u2605) \u2014 We present quantumnetworks as a numerical simulation tool with which to explore the time-dynamics of a driven, lossness, and nonlinear multi-mode quantum network using the Heisenberg-Langevin Equation", "url": "https://github.com/Phionx/quantumnetworks", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:deduckproject--tesseract-code-stim", "kind": "repo", "label": "DeDuckProject/tesseract-code-stim (5\u2605) \u2014 Tesseract quantum error correction code and Stim simulations", "url": "https://github.com/DeDuckProject/tesseract-code-stim", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:glanzz--quantum-error-correction", "kind": "repo", "label": "glanzz/quantum-error-correction (0\u2605) \u2014 Build error correction circuit using stim", "url": "https://github.com/glanzz/quantum-error-correction", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:nitchayanint--quantum-error-correction", "kind": "repo", "label": "NitchayaninT/quantum-error-correction (0\u2605) \u2014 quantum error correcting codes in stim, crumble and qiskit. ", "url": "https://github.com/NitchayaninT/quantum-error-correction", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:alexisdevpro--surfaces_codes_stim", "kind": "repo", "label": "Alexisdevpro/surfaces_codes_stim (0\u2605) \u2014 Surfaces Codes - Quantum Error Correction", "url": "https://github.com/Alexisdevpro/surfaces_codes_stim", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:haber7789--quantumfaultsim", "kind": "repo", "label": "HABER7789/QuantumFaultSim (0\u2605) \u2014 HPC assisted Surface Code threshold simulator powered by Stim, PyMatching, and Sinter for distributed quantum error correction research.", "url": "https://github.com/HABER7789/QuantumFaultSim", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:qvazarius648--repetition-qec-stim", "kind": "repo", "label": "qvazarius648/repetition-qec-stim (0\u2605) \u2014 Quantum Error Correction pipeline using Stim and PyMatching with threshold estimation for repetition code.", "url": "https://github.com/qvazarius648/repetition-qec-stim", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:pyhroff--qec-lab", "kind": "repo", "label": "Pyhroff/qec-lab (0\u2605) \u2014 Rotated surface code quantum error correction simulator: Stim + PyMatching threshold curve, D3 lattice animation, RSA-2048 qubit estimator", "url": "https://github.com/Pyhroff/qec-lab", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:mkatal--stim-learning", "kind": "repo", "label": "mKatal/Stim-Learning (0\u2605) \u2014 A long-term learning repository for Stim-based quantum error correction workflows, starting from minimal detector sampling and gradually moving toward decoder integration, visualization, and inspired ", "url": "https://github.com/mKatal/Stim-Learning", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:msubhia--intermediate-qec-symmetries", "kind": "repo", "label": "msubhia/intermediate-qec-symmetries (0\u2605) \u2014 Quantum error-correction research code exploring automorphism-based fault-tolerant logical gate constructions and intermediate code symmetries.", "url": "https://github.com/msubhia/intermediate-qec-symmetries", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:wseltd--waynestark-quantum-decoderops-workbench", "kind": "repo", "label": "wseltd/waynestark-quantum-decoderops-workbench (0\u2605) \u2014 Local-first, vendor-neutral Python workbench for benchmarking quantum error correction decoders \u2014 Stim, PyMatching, sinter, NVIDIA Ising-Decoding (Apache-2.0). FastAPI + Typer CLI, DuckDB/PostgreSQL p", "url": "https://github.com/wseltd/waynestark-quantum-decoderops-workbench", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:smitpatel228--surface-code-qec", "kind": "repo", "label": "smitpatel228/Surface-Code-QEC (0\u2605) \u2014 Surface Codes -  Quantum Error Correction. Manual Simulation of Unrotated Surface Code with Threshold and Bias Analysis of Rotated Surface Code using STIM and PyMatching", "url": "https://github.com/smitpatel228/Surface-Code-QEC", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:ridgeback1982--cameramediacodec", "kind": "repo", "label": "ridgeback1982/cameraMediaCodec (18\u2605) \u2014 On Android platform, use MediaCodec to encode camera preview data and decode it to surface after that.", "url": "https://github.com/ridgeback1982/cameraMediaCodec", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:emilbjornson--irs-relaying", "kind": "repo", "label": "emilbjornson/IRS-relaying (116\u2605) \u2014  Simulation code for \u201cIntelligent Reflecting Surface vs. Decode-and-Forward: How Large Surfaces Are Needed to Beat Relaying?,\u201d by Emil Bj\u00f6rnson, \u00d6zgecan \u00d6zdogan, Erik G. Larsson, IEEE Wireless Communi", "url": "https://github.com/emilbjornson/IRS-relaying", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:leye0--xamarinandroidmediacodecsurfacetosurface", "kind": "repo", "label": "leye0/XamarinAndroidMediaCodecSurfaceToSurface (6\u2605) \u2014 Xamarin Android MediaCodec Surface To Surface video decoding and encoding - CTS ported to Xamarin Android C#", "url": "https://github.com/leye0/XamarinAndroidMediaCodecSurfaceToSurface", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:usarica--fnal-qcdecodingtests", "kind": "repo", "label": "usarica/FNAL-QCDecodingTests (0\u2605) \u2014 Compact RCNN decoding of surface codes", "url": "https://github.com/usarica/FNAL-QCDecodingTests", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:r-sweke--gym-surfacecode", "kind": "repo", "label": "R-Sweke/gym-surfacecode (6\u2605) \u2014 A surface code environment for the development of decoding agents for fault tolerant quantum computing", "url": "https://github.com/R-Sweke/gym-surfacecode", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:mbecker12--surface-rl-decoder", "kind": "repo", "label": "mbecker12/surface-rl-decoder (7\u2605) \u2014 Implementation of different NN architectures & RL techniques for decoding of the quantum surface code", "url": "https://github.com/mbecker12/surface-rl-decoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:ypwk--decodervis", "kind": "repo", "label": "ypwk/DecoderVIS (3\u2605) \u2014 A visualizer for surface code decoding", "url": "https://github.com/ypwk/DecoderVIS", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:marcserraperalta--lomatching", "kind": "repo", "label": "MarcSerraPeralta/lomatching (7\u2605) \u2014 Decoder for (fold-)transversal logical gates in surface codes based on MWPM", "url": "https://github.com/MarcSerraPeralta/lomatching", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:tjivuraveng--mwpm-irmwpm-decoder-of-surface-codes", "kind": "repo", "label": "Tjivuraveng/MWPM-IRMWPM-decoder-of-surface-codes (2\u2605)", "url": "https://github.com/Tjivuraveng/MWPM-IRMWPM-decoder-of-surface-codes", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:dua-arpit--single_shot_decoding_fractal", "kind": "repo", "label": "dua-arpit/single_shot_decoding_fractal (3\u2605) \u2014 We adapt a cellular automaton decoder, sweep decoder, to the 3D surface code on a fractal lattice", "url": "https://github.com/dua-arpit/single_shot_decoding_fractal", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:ichirohasegawa07557--surface-code-decoder", "kind": "repo", "label": "ichirohasegawa07557/Surface-code-decoder (0\u2605) \u2014 surface-code decoder", "url": "https://github.com/ichirohasegawa07557/Surface-code-decoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:jazzych--bp-mwpm-xzzx-code", "kind": "repo", "label": "JazzyCH/BP-MWPM-XZZX-Code (2\u2605) \u2014 Work on the creation of a BP+MWPM decoder for the XZZX surface code.", "url": "https://github.com/JazzyCH/BP-MWPM-XZZX-Code", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:qvazarius648--surface-code-decoders", "kind": "repo", "label": "qvazarius648/surface-code-decoders (0\u2605) \u2014 Benchmarking quantum error correction decoders for the rotated surface code", "url": "https://github.com/qvazarius648/surface-code-decoders", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:adeelurehman--surface-code-decoder", "kind": "repo", "label": "adeelurehman/surface-code-decoder (0\u2605)", "url": "https://github.com/adeelurehman/surface-code-decoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:liziming18--surface-code-simulation", "kind": "repo", "label": "liziming18/surface-code-simulation (0\u2605) \u2014 a simulation of surface code and the maximum likelihood decoder", "url": "https://github.com/liziming18/surface-code-simulation", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:aknapen--pinball", "kind": "repo", "label": "aknapen/Pinball (7\u2605) \u2014 Source code for the Pinball predecoder, a cryogenic hardware predecoder for surface code quantum error correction decoding under circuit-level noise.", "url": "https://github.com/aknapen/Pinball", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:shraggy--xzzx-surface-code-decoder", "kind": "repo", "label": "shraggy/XZZX-Surface-Code-Decoder (0\u2605) \u2014 Deocoder for XZZX Surface Codes", "url": "https://github.com/shraggy/XZZX-Surface-Code-Decoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:timchan0--localuf", "kind": "repo", "label": "timchan0/localuf (6\u2605) \u2014 A Python package to simulate and visualise Union-Find-related decoders for the surface and repetition codes.", "url": "https://github.com/timchan0/localuf", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:pisush--surface-code", "kind": "repo", "label": "Pisush/surface-code (0\u2605) \u2014 Distance-d surface code with a union-find decoder and threshold Monte Carlo in Go", "url": "https://github.com/Pisush/surface-code", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:bryanzwu--transformer-surface-decoder", "kind": "repo", "label": "BryanZWu/transformer-surface-decoder (1\u2605) \u2014 191 project for a transformer based surface code decoder", "url": "https://github.com/BryanZWu/transformer-surface-decoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:33hariharann-ux--synop_decoding", "kind": "repo", "label": "33hariharann-ux/synop_decoding (0\u2605) \u2014 SYNOP FM-12 Surface Code Decoder", "url": "https://github.com/33hariharann-ux/synop_decoding", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:kechen666--decoding", "kind": "repo", "label": "kechen666/decoding (0\u2605) \u2014 decoding for surface code", "url": "https://github.com/kechen666/decoding", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:abenhemou--unimatch", "kind": "repo", "label": "abenhemou/unimatch (2\u2605) \u2014 Simulator of matching-based decoding on the color code and surface code", "url": "https://github.com/abenhemou/unimatch", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:bajwa4200--surface-code-qec", "kind": "repo", "label": "bajwa4200/surface-code-qec (0\u2605) \u2014 Surface code stabilizer lattice with noise injection and syndrome decode", "url": "https://github.com/bajwa4200/surface-code-qec", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:snpal--surface_code", "kind": "repo", "label": "snpal/surface_code (0\u2605) \u2014 Implementing a distance d surface code for quantum error correction. Decode using MWPM. ", "url": "https://github.com/snpal/surface_code", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:natashamp--quantum-error-correction-decoder", "kind": "repo", "label": "natashamp/Quantum-Error-Correction-Decoder (0\u2605) \u2014 Python Surface Code Quantum Error Correction Decoder", "url": "https://github.com/natashamp/Quantum-Error-Correction-Decoder", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:quicophy--mdopt", "kind": "repo", "label": "quicophy/mdopt (42\u2605) \u2014 Code-agnostic tensor-network (MPS-MPO) decoder for quantum error-correcting codes.", "url": "https://github.com/quicophy/mdopt", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:surdui--eva", "kind": "repo", "label": "Surdui/eva (0\u2605) \u2014 Quantum-inspired neural network for cross-load bearing fault diagnosis. Replaces Transformer with density matrix embedding, MPS tensor networks, collapse decoder, and no-cloning constraint.", "url": "https://github.com/Surdui/eva", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:108mk--tensor_network_codes", "kind": "repo", "label": "108mk/Tensor_Network_Codes (1\u2605) \u2014 As a part of Quantum error correction review project, we explored tensor network codes (TNC). TNC has diverse nad promising use in quantum error correcting codes. It is powerful tools to design larger", "url": "https://github.com/108mk/Tensor_Network_Codes", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:chubbc--ju2021", "kind": "repo", "label": "chubbc/JU2021 (1\u2605) \u2014 Talk on the paper 'General tensor network decoding of 2D Pauli codes' and package 'SweepContractor.jl' to the Quantum Resources Group (Jagiellonian University, Krakow, Poland).", "url": "https://github.com/chubbc/JU2021", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:mlco2--impact", "kind": "repo", "label": "mlco2/impact (266\u2605) \u2014 ML has an impact on the climate. But not all models are born equal. Compute your model's emissions with our calculator and add the results to your paper with our generated latex template", "url": "https://github.com/mlco2/impact", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:ml-energy--zeus", "kind": "repo", "label": "ml-energy/zeus (367\u2605) \u2014 Measure and optimize the energy consumption of your AI applications!", "url": "https://github.com/ml-energy/zeus", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:ml-energy--leaderboard", "kind": "repo", "label": "ml-energy/leaderboard (10\u2605) \u2014 How much time and energy do modern generative AI models consume?", "url": "https://github.com/ml-energy/leaderboard", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:responsibleproblemsolving--energy-usage", "kind": "repo", "label": "responsibleproblemsolving/energy-usage (154\u2605) \u2014 Provides a function to measure the energy usage of another function.", "url": "https://github.com/responsibleproblemsolving/energy-usage", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:green-software-foundation--carbon-aware-sdk", "kind": "repo", "label": "Green-Software-Foundation/carbon-aware-sdk (582\u2605) \u2014 Carbon-Aware SDK", "url": "https://github.com/Green-Software-Foundation/carbon-aware-sdk", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:green-software-foundation--if", "kind": "repo", "label": "Green-Software-Foundation/if (182\u2605) \u2014 Impact Framework", "url": "https://github.com/Green-Software-Foundation/if", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:powerapi-ng--powerapi", "kind": "repo", "label": "powerapi-ng/powerapi (248\u2605) \u2014 PowerAPI is a Python framework for building software-defined power meters.", "url": "https://github.com/powerapi-ng/powerapi", "source": "github", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:repo:quantumlib--stim", "kind": "repo", "label": "quantumlib/Stim (779\u2605) \u2014 A fast stabilizer circuit library.", "url": "https://github.com/quantumlib/Stim", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:oscarhiggott--pymatching", "kind": "repo", "label": "oscarhiggott/PyMatching (348\u2605) \u2014 PyMatching: A Python/C++ library for decoding quantum error correcting codes with minimum-weight perfect matching.", "url": "https://github.com/oscarhiggott/PyMatching", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:seokhyung-lee--color-code-stim", "kind": "repo", "label": "seokhyung-lee/color-code-stim (31\u2605) \u2014 Python package for simulating & decoding color code circuits.", "url": "https://github.com/seokhyung-lee/color-code-stim", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:gongaa--feedback-gnn", "kind": "repo", "label": "gongaa/Feedback-GNN (16\u2605) \u2014 Post-processing decoding of Quantum Low Density Parity Check Codes.", "url": "https://github.com/gongaa/Feedback-GNN", "source": "github", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:repo:dao-ailab--flash-attention", "kind": "repo", "label": "Dao-AILab/flash-attention (24375\u2605) \u2014 Fast and memory-efficient exact attention", "url": "https://github.com/Dao-AILab/flash-attention", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:zyphra--zamba2", "kind": "repo", "label": "Zyphra/Zamba2 (193\u2605) \u2014 PyTorch implementation of models from the Zamba2 series.", "url": "https://github.com/Zyphra/Zamba2", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:nvlabs--hymba", "kind": "repo", "label": "NVlabs/hymba (212\u2605)", "url": "https://github.com/NVlabs/hymba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:microsoft--samba", "kind": "repo", "label": "microsoft/Samba (964\u2605) \u2014 [ICLR 2025] Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling", "url": "https://github.com/microsoft/Samba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:state-spaces--mamba", "kind": "repo", "label": "state-spaces/mamba (18561\u2605) \u2014 Mamba SSM architecture", "url": "https://github.com/state-spaces/mamba", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:kyegomez--griffin", "kind": "repo", "label": "kyegomez/Griffin (57\u2605) \u2014 Implementation of Griffin from the paper: \"Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models\"", "url": "https://github.com/kyegomez/Griffin", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:proger--hippogriff", "kind": "repo", "label": "proger/hippogriff (89\u2605) \u2014 Griffin MQA + Hawk Linear RNN Hybrid", "url": "https://github.com/proger/hippogriff", "source": "github", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:repo:hkust-aerial-robotics--vins-fusion", "kind": "repo", "label": "HKUST-Aerial-Robotics/VINS-Fusion (4616\u2605) \u2014 An optimization-based multi-sensor state estimator", "url": "https://github.com/HKUST-Aerial-Robotics/VINS-Fusion", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:open-mmlab--mmdetection3d", "kind": "repo", "label": "open-mmlab/mmdetection3d (6472\u2605) \u2014 OpenMMLab's next-generation platform for general 3D object detection.", "url": "https://github.com/open-mmlab/mmdetection3d", "source": "github", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:repo:zhouyi1023--awesome-radar-perception", "kind": "repo", "label": "ZHOUYI1023/awesome-radar-perception (1865\u2605) \u2014  A curated list of radar datasets, detection, tracking and fusion", "url": "https://github.com/ZHOUYI1023/awesome-radar-perception", "source": "github", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:repo:significant-gravitas--autogpt", "kind": "repo", "label": "Significant-Gravitas/AutoGPT (185416\u2605) \u2014 AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.", "url": "https://github.com/Significant-Gravitas/AutoGPT", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:crewaiinc--crewai", "kind": "repo", "label": "crewAIInc/crewAI (55069\u2605) \u2014 Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together smoothly, tackling complex tasks.", "url": "https://github.com/crewAIInc/crewAI", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:stanfordnlp--dspy", "kind": "repo", "label": "stanfordnlp/dspy (35906\u2605) \u2014 DSPy: The framework for programming\u2014not prompting\u2014language models", "url": "https://github.com/stanfordnlp/dspy", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:mem0ai--mem0", "kind": "repo", "label": "mem0ai/mem0 (60294\u2605) \u2014 Universal memory layer for AI Agents", "url": "https://github.com/mem0ai/mem0", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:letta-ai--letta", "kind": "repo", "label": "letta-ai/letta (23692\u2605) \u2014 Platform for stateful agents: AI with advanced memory that can learn and self-improve over time.", "url": "https://github.com/letta-ai/letta", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:huggingface--smolagents", "kind": "repo", "label": "huggingface/smolagents (28231\u2605) \u2014 \ud83e\udd17 smolagents: a barebones library for agents that think in code.", "url": "https://github.com/huggingface/smolagents", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:swe-agent--swe-agent", "kind": "repo", "label": "SWE-agent/SWE-agent (19722\u2605) \u2014 SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024] ", "url": "https://github.com/SWE-agent/SWE-agent", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:openbmb--chatdev", "kind": "repo", "label": "OpenBMB/ChatDev (33682\u2605) \u2014 ChatDev 2.0: Dev All through LLM-powered Multi-Agent Collaboration", "url": "https://github.com/OpenBMB/ChatDev", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:yoheinakajima--babyagi", "kind": "repo", "label": "yoheinakajima/babyagi (22323\u2605)", "url": "https://github.com/yoheinakajima/babyagi", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:run-llama--llama_index", "kind": "repo", "label": "run-llama/llama_index (50705\u2605) \u2014 LlamaIndex is the widely-used document agent and OCR platform", "url": "https://github.com/run-llama/llama_index", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:repo:assafelovic--gpt-researcher", "kind": "repo", "label": "assafelovic/gpt-researcher (28129\u2605) \u2014 An autonomous agent that conducts deep research on any data using any LLM providers", "url": "https://github.com/assafelovic/gpt-researcher", "source": "github", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2504.00727", "kind": "paper", "label": "Personality-Driven Decision-Making in LLM-Based Autonomous Agents", "url": "https://arxiv.org/abs/2504.00727", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lewis-newsham", "kind": "person", "label": "Lewis Newsham", "url": "https://arxiv.org/abs/2504.00727", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daniel-prince", "kind": "person", "label": "Daniel Prince", "url": "https://arxiv.org/abs/2504.00727", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2308.11432", "kind": "paper", "label": "A Survey on Large Language Model based Autonomous Agents", "url": "https://arxiv.org/abs/2308.11432", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lei-wang", "kind": "person", "label": "Lei Wang", "url": "https://arxiv.org/abs/2308.11432", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chen-ma", "kind": "person", "label": "Chen Ma", "url": "https://arxiv.org/abs/2308.11432", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xueyang-feng", "kind": "person", "label": "Xueyang Feng", "url": "https://arxiv.org/abs/2308.11432", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zeyu-zhang", "kind": "person", "label": "Zeyu Zhang", "url": "https://arxiv.org/abs/2308.11432", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hao-yang", "kind": "person", "label": "Hao Yang", "url": "https://arxiv.org/abs/2308.11432", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingsen-zhang", "kind": "person", "label": "Jingsen Zhang", "url": "https://arxiv.org/abs/2308.11432", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhiyuan-chen", "kind": "person", "label": "Zhiyuan Chen", "url": "https://arxiv.org/abs/2308.11432", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiakai-tang", "kind": "person", "label": "Jiakai Tang", "url": "https://arxiv.org/abs/2308.11432", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2407.01603", "kind": "paper", "label": "A Review of Large Language Models and Autonomous Agents in Chemistry", "url": "https://arxiv.org/abs/2407.01603", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mayk-caldas-ramos", "kind": "person", "label": "Mayk Caldas Ramos", "url": "https://arxiv.org/abs/2407.01603", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:christopher-j-collison", "kind": "person", "label": "Christopher J. Collison", "url": "https://arxiv.org/abs/2407.01603", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:andrew-d-white", "kind": "person", "label": "Andrew D. White", "url": "https://arxiv.org/abs/2407.01603", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2404.04442", "kind": "paper", "label": "Exploring Autonomous Agents through the Lens of Large Language Models: A Review", "url": "https://arxiv.org/abs/2404.04442", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:saikat-barua", "kind": "person", "label": "Saikat Barua", "url": "https://arxiv.org/abs/2404.04442", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.17281", "kind": "paper", "label": "From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Users", "url": "https://arxiv.org/abs/2508.17281", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sadia-sultana-chowa", "kind": "person", "label": "Sadia Sultana Chowa", "url": "https://arxiv.org/abs/2508.17281", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:riasad-alvi", "kind": "person", "label": "Riasad Alvi", "url": "https://arxiv.org/abs/2508.17281", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:subhey-sadi-rahman", "kind": "person", "label": "Subhey Sadi Rahman", "url": "https://arxiv.org/abs/2508.17281", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:md-abdur-rahman", "kind": "person", "label": "Md Abdur Rahman", "url": "https://arxiv.org/abs/2508.17281", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mohaimenul-azam-khan-raiaan", "kind": "person", "label": "Mohaimenul Azam Khan Raiaan", "url": "https://arxiv.org/abs/2508.17281", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:md-rafiqul-islam", "kind": "person", "label": "Md Rafiqul Islam", "url": "https://arxiv.org/abs/2508.17281", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mukhtar-hussain", "kind": "person", "label": "Mukhtar Hussain", "url": "https://arxiv.org/abs/2508.17281", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sami-azam", "kind": "person", "label": "Sami Azam", "url": "https://arxiv.org/abs/2508.17281", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2310.16340", "kind": "paper", "label": "RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models", "url": "https://arxiv.org/abs/2310.16340", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zefan-wang", "kind": "person", "label": "Zefan Wang", "url": "https://arxiv.org/abs/2310.16340", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zichuan-liu", "kind": "person", "label": "Zichuan Liu", "url": "https://arxiv.org/abs/2310.16340", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yingying-zhang", "kind": "person", "label": "Yingying Zhang", "url": "https://arxiv.org/abs/2310.16340", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:aoxiao-zhong", "kind": "person", "label": "Aoxiao Zhong", "url": "https://arxiv.org/abs/2310.16340", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jihong-wang", "kind": "person", "label": "Jihong Wang", "url": "https://arxiv.org/abs/2310.16340", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fengbin-yin", "kind": "person", "label": "Fengbin Yin", "url": "https://arxiv.org/abs/2310.16340", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lunting-fan", "kind": "person", "label": "Lunting Fan", "url": "https://arxiv.org/abs/2310.16340", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lingfei-wu", "kind": "person", "label": "Lingfei Wu", "url": "https://arxiv.org/abs/2310.16340", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2412.16878", "kind": "paper", "label": "Online Preference-based Reinforcement Learning with Self-augmented Feedback from Large Language Model", "url": "https://arxiv.org/abs/2412.16878", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:songjun-tu", "kind": "person", "label": "Songjun Tu", "url": "https://arxiv.org/abs/2412.16878", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingbo-sun", "kind": "person", "label": "Jingbo Sun", "url": "https://arxiv.org/abs/2412.16878", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qichao-zhang", "kind": "person", "label": "Qichao Zhang", "url": "https://arxiv.org/abs/2412.16878", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiangyuan-lan", "kind": "person", "label": "Xiangyuan Lan", "url": "https://arxiv.org/abs/2412.16878", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dongbin-zhao", "kind": "person", "label": "Dongbin Zhao", "url": "https://arxiv.org/abs/2412.16878", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2408.11826", "kind": "paper", "label": "Generative Organizational Behavior Simulation using Large Language Model based Autonomous Agents: A Holacracy Perspective", "url": "https://arxiv.org/abs/2408.11826", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chen-zhu", "kind": "person", "label": "Chen Zhu", "url": "https://arxiv.org/abs/2408.11826", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yihang-cheng", "kind": "person", "label": "Yihang Cheng", "url": "https://arxiv.org/abs/2408.11826", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingshuai-zhang", "kind": "person", "label": "Jingshuai Zhang", "url": "https://arxiv.org/abs/2408.11826", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yusheng-qiu", "kind": "person", "label": "Yusheng Qiu", "url": "https://arxiv.org/abs/2408.11826", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sitao-xia", "kind": "person", "label": "Sitao Xia", "url": "https://arxiv.org/abs/2408.11826", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hengshu-zhu", "kind": "person", "label": "Hengshu Zhu", "url": "https://arxiv.org/abs/2408.11826", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2403.09567", "kind": "paper", "label": "Enhancing Trust in Autonomous Agents: An Architecture for Accountability and Explainability through Blockchain and Large Language Models", "url": "https://arxiv.org/abs/2403.09567", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:laura-fern-ndez-becerra", "kind": "person", "label": "Laura Fern\u00e1ndez-Becerra", "url": "https://arxiv.org/abs/2403.09567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:miguel-ngel-gonz-lez-santamarta", "kind": "person", "label": "Miguel \u00c1ngel Gonz\u00e1lez-Santamarta", "url": "https://arxiv.org/abs/2403.09567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ngel-manuel-guerrero-higueras", "kind": "person", "label": "\u00c1ngel Manuel Guerrero-Higueras", "url": "https://arxiv.org/abs/2403.09567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:francisco-javier-rodr-guez-lera", "kind": "person", "label": "Francisco Javier Rodr\u00edguez-Lera", "url": "https://arxiv.org/abs/2403.09567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:vicente-matell-n-olivera", "kind": "person", "label": "Vicente Matell\u00e1n Olivera", "url": "https://arxiv.org/abs/2403.09567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2308.10204", "kind": "paper", "label": "ChatEDA: A Large Language Model Powered Autonomous Agent for EDA", "url": "https://arxiv.org/abs/2308.10204", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhuolun-he", "kind": "person", "label": "Zhuolun He", "url": "https://arxiv.org/abs/2308.10204", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haoyuan-wu", "kind": "person", "label": "Haoyuan Wu", "url": "https://arxiv.org/abs/2308.10204", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinyun-zhang", "kind": "person", "label": "Xinyun Zhang", "url": "https://arxiv.org/abs/2308.10204", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xufeng-yao", "kind": "person", "label": "Xufeng Yao", "url": "https://arxiv.org/abs/2308.10204", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:su-zheng", "kind": "person", "label": "Su Zheng", "url": "https://arxiv.org/abs/2308.10204", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haisheng-zheng", "kind": "person", "label": "Haisheng Zheng", "url": "https://arxiv.org/abs/2308.10204", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bei-yu", "kind": "person", "label": "Bei Yu", "url": "https://arxiv.org/abs/2308.10204", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.03459", "kind": "paper", "label": "Unified Mind Model: Reimagining Autonomous Agents in the LLM Era", "url": "https://arxiv.org/abs/2503.03459", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:pengbo-hu", "kind": "person", "label": "Pengbo Hu", "url": "https://arxiv.org/abs/2503.03459", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiang-ying", "kind": "person", "label": "Xiang Ying", "url": "https://arxiv.org/abs/2503.03459", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2401.02851", "kind": "paper", "label": "Natural Language Programming in Medicine: Administering Evidence Based Clinical Workflows with Autonomous Agents Powered by Generative Large Language Models", "url": "https://arxiv.org/abs/2401.02851", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:akhil-vaid", "kind": "person", "label": "Akhil Vaid", "url": "https://arxiv.org/abs/2401.02851", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:joshua-lampert", "kind": "person", "label": "Joshua Lampert", "url": "https://arxiv.org/abs/2401.02851", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:juhee-lee", "kind": "person", "label": "Juhee Lee", "url": "https://arxiv.org/abs/2401.02851", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ashwin-sawant", "kind": "person", "label": "Ashwin Sawant", "url": "https://arxiv.org/abs/2401.02851", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:donald-apakama", "kind": "person", "label": "Donald Apakama", "url": "https://arxiv.org/abs/2401.02851", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ankit-sakhuja", "kind": "person", "label": "Ankit Sakhuja", "url": "https://arxiv.org/abs/2401.02851", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ali-soroush", "kind": "person", "label": "Ali Soroush", "url": "https://arxiv.org/abs/2401.02851", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sarah-bick", "kind": "person", "label": "Sarah Bick", "url": "https://arxiv.org/abs/2401.02851", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2410.11872", "kind": "paper", "label": "ClickAgent: Enhancing UI Location Capabilities of Autonomous Agents", "url": "https://arxiv.org/abs/2410.11872", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jakub-hoscilowicz", "kind": "person", "label": "Jakub Hoscilowicz", "url": "https://arxiv.org/abs/2410.11872", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bartosz-maj", "kind": "person", "label": "Bartosz Maj", "url": "https://arxiv.org/abs/2410.11872", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bartosz-kozakiewicz", "kind": "person", "label": "Bartosz Kozakiewicz", "url": "https://arxiv.org/abs/2410.11872", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:oleksii-tymoshchuk", "kind": "person", "label": "Oleksii Tymoshchuk", "url": "https://arxiv.org/abs/2410.11872", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:artur-janicki", "kind": "person", "label": "Artur Janicki", "url": "https://arxiv.org/abs/2410.11872", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2410.16197", "kind": "paper", "label": "LASER: Script Execution by Autonomous Agents for On-demand Traffic Simulation", "url": "https://arxiv.org/abs/2410.16197", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hao-gao", "kind": "person", "label": "Hao Gao", "url": "https://arxiv.org/abs/2410.16197", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingyue-wang", "kind": "person", "label": "Jingyue Wang", "url": "https://arxiv.org/abs/2410.16197", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenyang-fang", "kind": "person", "label": "Wenyang Fang", "url": "https://arxiv.org/abs/2410.16197", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingwei-xu", "kind": "person", "label": "Jingwei Xu", "url": "https://arxiv.org/abs/2410.16197", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yunpeng-huang", "kind": "person", "label": "Yunpeng Huang", "url": "https://arxiv.org/abs/2410.16197", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:taolue-chen", "kind": "person", "label": "Taolue Chen", "url": "https://arxiv.org/abs/2410.16197", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaoxing-ma", "kind": "person", "label": "Xiaoxing Ma", "url": "https://arxiv.org/abs/2410.16197", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2504.16855", "kind": "paper", "label": "Monte Carlo Planning with Large Language Model for Text-Based Game Agents", "url": "https://arxiv.org/abs/2504.16855", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zijing-shi", "kind": "person", "label": "Zijing Shi", "url": "https://arxiv.org/abs/2504.16855", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:meng-fang", "kind": "person", "label": "Meng Fang", "url": "https://arxiv.org/abs/2504.16855", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ling-chen", "kind": "person", "label": "Ling Chen", "url": "https://arxiv.org/abs/2504.16855", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2512.10971", "kind": "paper", "label": "AI-Trader: Benchmarking Autonomous Agents in Real-Time Financial Markets", "url": "https://arxiv.org/abs/2512.10971", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tianyu-fan", "kind": "person", "label": "Tianyu Fan", "url": "https://arxiv.org/abs/2512.10971", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuhao-yang", "kind": "person", "label": "Yuhao Yang", "url": "https://arxiv.org/abs/2512.10971", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yangqin-jiang", "kind": "person", "label": "Yangqin Jiang", "url": "https://arxiv.org/abs/2512.10971", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yifei-zhang", "kind": "person", "label": "Yifei Zhang", "url": "https://arxiv.org/abs/2512.10971", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuxuan-chen", "kind": "person", "label": "Yuxuan Chen", "url": "https://arxiv.org/abs/2512.10971", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chao-huang", "kind": "person", "label": "Chao Huang", "url": "https://arxiv.org/abs/2512.10971", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2601.13383", "kind": "paper", "label": "A Lightweight Modular Framework for Constructing Autonomous Agents Driven by Large Language Models: Design, Implementation, and Applications in AgentForge", "url": "https://arxiv.org/abs/2601.13383", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:akbar-anbar-jafari", "kind": "person", "label": "Akbar Anbar Jafari", "url": "https://arxiv.org/abs/2601.13383", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:cagri-ozcinar", "kind": "person", "label": "Cagri Ozcinar", "url": "https://arxiv.org/abs/2601.13383", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gholamreza-anbarjafari", "kind": "person", "label": "Gholamreza Anbarjafari", "url": "https://arxiv.org/abs/2601.13383", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2408.11021", "kind": "paper", "label": "Athena: Safe Autonomous Agents with Verbal Contrastive Learning", "url": "https://arxiv.org/abs/2408.11021", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tanmana-sadhu", "kind": "person", "label": "Tanmana Sadhu", "url": "https://arxiv.org/abs/2408.11021", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ali-pesaranghader", "kind": "person", "label": "Ali Pesaranghader", "url": "https://arxiv.org/abs/2408.11021", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yanan-chen", "kind": "person", "label": "Yanan Chen", "url": "https://arxiv.org/abs/2408.11021", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dong-hoon-yi", "kind": "person", "label": "Dong Hoon Yi", "url": "https://arxiv.org/abs/2408.11021", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.09990", "kind": "paper", "label": "Merlin: Deterministic Byte-Exact Deduplication for Lossless Context Optimization in Large Language Model Inference", "url": "https://arxiv.org/abs/2605.09990", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sietse-schelpe", "kind": "person", "label": "Sietse Schelpe", "url": "https://arxiv.org/abs/2605.09990", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2506.08136", "kind": "paper", "label": "EconWebArena: Benchmarking Autonomous Agents on Economic Tasks in Realistic Web Environments", "url": "https://arxiv.org/abs/2506.08136", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zefang-liu", "kind": "person", "label": "Zefang Liu", "url": "https://arxiv.org/abs/2506.08136", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yinzhu-quan", "kind": "person", "label": "Yinzhu Quan", "url": "https://arxiv.org/abs/2506.08136", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.12644", "kind": "paper", "label": "Uncovering Security Threats and Architecting Defenses in Autonomous Agents: A Case Study of OpenClaw", "url": "https://arxiv.org/abs/2603.12644", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zonghao-ying", "kind": "person", "label": "Zonghao Ying", "url": "https://arxiv.org/abs/2603.12644", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiao-yang", "kind": "person", "label": "Xiao Yang", "url": "https://arxiv.org/abs/2603.12644", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:siyang-wu", "kind": "person", "label": "Siyang Wu", "url": "https://arxiv.org/abs/2603.12644", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yumeng-song", "kind": "person", "label": "Yumeng Song", "url": "https://arxiv.org/abs/2603.12644", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yang-qu", "kind": "person", "label": "Yang Qu", "url": "https://arxiv.org/abs/2603.12644", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hainan-li", "kind": "person", "label": "Hainan Li", "url": "https://arxiv.org/abs/2603.12644", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tianlin-li", "kind": "person", "label": "Tianlin Li", "url": "https://arxiv.org/abs/2603.12644", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiakai-wang", "kind": "person", "label": "Jiakai Wang", "url": "https://arxiv.org/abs/2603.12644", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.13143", "kind": "paper", "label": "Exploring Autonomous Agents: A Closer Look at Why They Fail When Completing Tasks", "url": "https://arxiv.org/abs/2508.13143", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ruofan-lu", "kind": "person", "label": "Ruofan Lu", "url": "https://arxiv.org/abs/2508.13143", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yichen-li", "kind": "person", "label": "Yichen Li", "url": "https://arxiv.org/abs/2508.13143", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yintong-huo", "kind": "person", "label": "Yintong Huo", "url": "https://arxiv.org/abs/2508.13143", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2410.24024", "kind": "paper", "label": "AndroidLab: Training and Systematic Benchmarking of Android Autonomous Agents", "url": "https://arxiv.org/abs/2410.24024", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yifan-xu", "kind": "person", "label": "Yifan Xu", "url": "https://arxiv.org/abs/2410.24024", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiao-liu", "kind": "person", "label": "Xiao Liu", "url": "https://arxiv.org/abs/2410.24024", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xueqiao-sun", "kind": "person", "label": "Xueqiao Sun", "url": "https://arxiv.org/abs/2410.24024", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:siyi-cheng", "kind": "person", "label": "Siyi Cheng", "url": "https://arxiv.org/abs/2410.24024", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hao-yu", "kind": "person", "label": "Hao Yu", "url": "https://arxiv.org/abs/2410.24024", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hanyu-lai", "kind": "person", "label": "Hanyu Lai", "url": "https://arxiv.org/abs/2410.24024", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shudan-zhang", "kind": "person", "label": "Shudan Zhang", "url": "https://arxiv.org/abs/2410.24024", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dan-zhang", "kind": "person", "label": "Dan Zhang", "url": "https://arxiv.org/abs/2410.24024", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2308.05960", "kind": "paper", "label": "BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents", "url": "https://arxiv.org/abs/2308.05960", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhiwei-liu", "kind": "person", "label": "Zhiwei Liu", "url": "https://arxiv.org/abs/2308.05960", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:weiran-yao", "kind": "person", "label": "Weiran Yao", "url": "https://arxiv.org/abs/2308.05960", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jianguo-zhang", "kind": "person", "label": "Jianguo Zhang", "url": "https://arxiv.org/abs/2308.05960", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:le-xue", "kind": "person", "label": "Le Xue", "url": "https://arxiv.org/abs/2308.05960", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shelby-heinecke", "kind": "person", "label": "Shelby Heinecke", "url": "https://arxiv.org/abs/2308.05960", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rithesh-murthy", "kind": "person", "label": "Rithesh Murthy", "url": "https://arxiv.org/abs/2308.05960", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yihao-feng", "kind": "person", "label": "Yihao Feng", "url": "https://arxiv.org/abs/2308.05960", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zeyuan-chen", "kind": "person", "label": "Zeyuan Chen", "url": "https://arxiv.org/abs/2308.05960", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.03159", "kind": "paper", "label": "Learning Correct Behavior from Examples: Validating Sequential Execution in Autonomous Agents", "url": "https://arxiv.org/abs/2605.03159", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:reshabh-k-sharma", "kind": "person", "label": "Reshabh K Sharma", "url": "https://arxiv.org/abs/2605.03159", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gaurav-mittal", "kind": "person", "label": "Gaurav Mittal", "url": "https://arxiv.org/abs/2605.03159", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yu-hu", "kind": "person", "label": "Yu Hu", "url": "https://arxiv.org/abs/2605.03159", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.13820", "kind": "paper", "label": "Structured Agent Distillation for Large Language Model", "url": "https://arxiv.org/abs/2505.13820", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jun-liu", "kind": "person", "label": "Jun Liu", "url": "https://arxiv.org/abs/2505.13820", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhenglun-kong", "kind": "person", "label": "Zhenglun Kong", "url": "https://arxiv.org/abs/2505.13820", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:peiyan-dong", "kind": "person", "label": "Peiyan Dong", "url": "https://arxiv.org/abs/2505.13820", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:changdi-yang", "kind": "person", "label": "Changdi Yang", "url": "https://arxiv.org/abs/2505.13820", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tianqi-li", "kind": "person", "label": "Tianqi Li", "url": "https://arxiv.org/abs/2505.13820", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hao-tang", "kind": "person", "label": "Hao Tang", "url": "https://arxiv.org/abs/2505.13820", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:geng-yuan", "kind": "person", "label": "Geng Yuan", "url": "https://arxiv.org/abs/2505.13820", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wei-niu", "kind": "person", "label": "Wei Niu", "url": "https://arxiv.org/abs/2505.13820", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.23193", "kind": "paper", "label": "ESAA: Event Sourcing for Autonomous Agents in LLM-Based Software Engineering", "url": "https://arxiv.org/abs/2602.23193", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:elzo-brito-dos-santos-filho", "kind": "person", "label": "Elzo Brito dos Santos Filho", "url": "https://arxiv.org/abs/2602.23193", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.09901", "kind": "paper", "label": "Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics", "url": "https://arxiv.org/abs/2510.09901", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lianhao-zhou", "kind": "person", "label": "Lianhao Zhou", "url": "https://arxiv.org/abs/2510.09901", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hongyi-ling", "kind": "person", "label": "Hongyi Ling", "url": "https://arxiv.org/abs/2510.09901", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:cong-fu", "kind": "person", "label": "Cong Fu", "url": "https://arxiv.org/abs/2510.09901", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yepeng-huang", "kind": "person", "label": "Yepeng Huang", "url": "https://arxiv.org/abs/2510.09901", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:michael-sun", "kind": "person", "label": "Michael Sun", "url": "https://arxiv.org/abs/2510.09901", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wendi-yu", "kind": "person", "label": "Wendi Yu", "url": "https://arxiv.org/abs/2510.09901", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaoxuan-wang", "kind": "person", "label": "Xiaoxuan Wang", "url": "https://arxiv.org/abs/2510.09901", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiner-li", "kind": "person", "label": "Xiner Li", "url": "https://arxiv.org/abs/2510.09901", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2501.05171", "kind": "paper", "label": "Emergence of human-like polarization among large language model agents", "url": "https://arxiv.org/abs/2501.05171", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jinghua-piao", "kind": "person", "label": "Jinghua Piao", "url": "https://arxiv.org/abs/2501.05171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhihong-lu", "kind": "person", "label": "Zhihong Lu", "url": "https://arxiv.org/abs/2501.05171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chen-gao", "kind": "person", "label": "Chen Gao", "url": "https://arxiv.org/abs/2501.05171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fengli-xu", "kind": "person", "label": "Fengli Xu", "url": "https://arxiv.org/abs/2501.05171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qinghua-hu", "kind": "person", "label": "Qinghua Hu", "url": "https://arxiv.org/abs/2501.05171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fernando-p-santos", "kind": "person", "label": "Fernando P. Santos", "url": "https://arxiv.org/abs/2501.05171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yong-li", "kind": "person", "label": "Yong Li", "url": "https://arxiv.org/abs/2501.05171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:james-evans", "kind": "person", "label": "James Evans", "url": "https://arxiv.org/abs/2501.05171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2312.13382", "kind": "paper", "label": "DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines", "url": "https://arxiv.org/abs/2312.13382", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:arnav-singhvi", "kind": "person", "label": "Arnav Singhvi", "url": "https://arxiv.org/abs/2312.13382", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:manish-shetty", "kind": "person", "label": "Manish Shetty", "url": "https://arxiv.org/abs/2312.13382", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shangyin-tan", "kind": "person", "label": "Shangyin Tan", "url": "https://arxiv.org/abs/2312.13382", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:christopher-potts", "kind": "person", "label": "Christopher Potts", "url": "https://arxiv.org/abs/2312.13382", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:koushik-sen", "kind": "person", "label": "Koushik Sen", "url": "https://arxiv.org/abs/2312.13382", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:matei-zaharia", "kind": "person", "label": "Matei Zaharia", "url": "https://arxiv.org/abs/2312.13382", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:omar-khattab", "kind": "person", "label": "Omar Khattab", "url": "https://arxiv.org/abs/2312.13382", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.04869", "kind": "paper", "label": "Optimizing LLM Prompt Engineering with DSPy Based Declarative Learning", "url": "https://arxiv.org/abs/2604.04869", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shiek-ruksana", "kind": "person", "label": "Shiek Ruksana", "url": "https://arxiv.org/abs/2604.04869", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sailesh-kiran-kurra", "kind": "person", "label": "Sailesh Kiran Kurra", "url": "https://arxiv.org/abs/2604.04869", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:thipparthi-sanjay-baradwaj", "kind": "person", "label": "Thipparthi Sanjay Baradwaj", "url": "https://arxiv.org/abs/2604.04869", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2507.03620", "kind": "paper", "label": "Is It Time To Treat Prompts As Code? A Multi-Use Case Study For Prompt Optimization Using DSPy", "url": "https://arxiv.org/abs/2507.03620", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:francisca-lemos", "kind": "person", "label": "Francisca Lemos", "url": "https://arxiv.org/abs/2507.03620", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:victor-alves", "kind": "person", "label": "Victor Alves", "url": "https://arxiv.org/abs/2507.03620", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:filipa-ferraz", "kind": "person", "label": "Filipa Ferraz", "url": "https://arxiv.org/abs/2507.03620", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2412.15298", "kind": "paper", "label": "A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation", "url": "https://arxiv.org/abs/2412.15298", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bhaskarjit-sarmah", "kind": "person", "label": "Bhaskarjit Sarmah", "url": "https://arxiv.org/abs/2412.15298", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kriti-dutta", "kind": "person", "label": "Kriti Dutta", "url": "https://arxiv.org/abs/2412.15298", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:anna-grigoryan", "kind": "person", "label": "Anna Grigoryan", "url": "https://arxiv.org/abs/2412.15298", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sachin-tiwari", "kind": "person", "label": "Sachin Tiwari", "url": "https://arxiv.org/abs/2412.15298", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:stefano-pasquali", "kind": "person", "label": "Stefano Pasquali", "url": "https://arxiv.org/abs/2412.15298", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dhagash-mehta", "kind": "person", "label": "Dhagash Mehta", "url": "https://arxiv.org/abs/2412.15298", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2411.18564", "kind": "paper", "label": "Dspy-based Neural-Symbolic Pipeline to Enhance Spatial Reasoning in LLMs", "url": "https://arxiv.org/abs/2411.18564", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rong-wang", "kind": "person", "label": "Rong Wang", "url": "https://arxiv.org/abs/2411.18564", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kun-sun", "kind": "person", "label": "Kun Sun", "url": "https://arxiv.org/abs/2411.18564", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jonas-kuhn", "kind": "person", "label": "Jonas Kuhn", "url": "https://arxiv.org/abs/2411.18564", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.25169", "kind": "paper", "label": "To Write or to Automate Linguistic Prompts, That Is the Question", "url": "https://arxiv.org/abs/2603.25169", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:marina-s-nchez-torr-n", "kind": "person", "label": "Marina S\u00e1nchez-Torr\u00f3n", "url": "https://arxiv.org/abs/2603.25169", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daria-akselrod", "kind": "person", "label": "Daria Akselrod", "url": "https://arxiv.org/abs/2603.25169", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jason-rauchwerk", "kind": "person", "label": "Jason Rauchwerk", "url": "https://arxiv.org/abs/2603.25169", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.17937", "kind": "paper", "label": "Analyzing LLM Instruction Optimization for Tabular Fact Verification", "url": "https://arxiv.org/abs/2602.17937", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaotang-du", "kind": "person", "label": "Xiaotang Du", "url": "https://arxiv.org/abs/2602.17937", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:giwon-hong", "kind": "person", "label": "Giwon Hong", "url": "https://arxiv.org/abs/2602.17937", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wai-chung-kwan", "kind": "person", "label": "Wai-Chung Kwan", "url": "https://arxiv.org/abs/2602.17937", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rohit-saxena", "kind": "person", "label": "Rohit Saxena", "url": "https://arxiv.org/abs/2602.17937", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ivan-titov", "kind": "person", "label": "Ivan Titov", "url": "https://arxiv.org/abs/2602.17937", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:pasquale-minervini", "kind": "person", "label": "Pasquale Minervini", "url": "https://arxiv.org/abs/2602.17937", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:emily-allaway", "kind": "person", "label": "Emily Allaway", "url": "https://arxiv.org/abs/2602.17937", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.16827", "kind": "paper", "label": "Prompt Programming for Cultural Bias and Alignment of Large Language Models", "url": "https://arxiv.org/abs/2603.16827", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:maksim-eren", "kind": "person", "label": "Maksim Eren", "url": "https://arxiv.org/abs/2603.16827", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:eric-michalak", "kind": "person", "label": "Eric Michalak", "url": "https://arxiv.org/abs/2603.16827", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:brian-cook", "kind": "person", "label": "Brian Cook", "url": "https://arxiv.org/abs/2603.16827", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:johnny-seales", "kind": "person", "label": "Johnny Seales", "url": "https://arxiv.org/abs/2603.16827", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.22565", "kind": "paper", "label": "Retrieval-Augmented Guardrails for AI-Drafted Patient-Portal Messages: Error Taxonomy Construction and Large-Scale Evaluation", "url": "https://arxiv.org/abs/2509.22565", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenyuan-chen", "kind": "person", "label": "Wenyuan Chen", "url": "https://arxiv.org/abs/2509.22565", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fateme-nateghi-haredasht", "kind": "person", "label": "Fateme Nateghi Haredasht", "url": "https://arxiv.org/abs/2509.22565", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kameron-c-black", "kind": "person", "label": "Kameron C. Black", "url": "https://arxiv.org/abs/2509.22565", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:francois-grolleau", "kind": "person", "label": "Francois Grolleau", "url": "https://arxiv.org/abs/2509.22565", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:emily-alsentzer", "kind": "person", "label": "Emily Alsentzer", "url": "https://arxiv.org/abs/2509.22565", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jonathan-h-chen", "kind": "person", "label": "Jonathan H. Chen", "url": "https://arxiv.org/abs/2509.22565", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:stephen-p-ma", "kind": "person", "label": "Stephen P. Ma", "url": "https://arxiv.org/abs/2509.22565", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2511.20836", "kind": "paper", "label": "Structured Prompts Improve Evaluation of Language Models", "url": "https://arxiv.org/abs/2511.20836", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:asad-aali", "kind": "person", "label": "Asad Aali", "url": "https://arxiv.org/abs/2511.20836", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:muhammad-ahmed-mohsin", "kind": "person", "label": "Muhammad Ahmed Mohsin", "url": "https://arxiv.org/abs/2511.20836", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:vasiliki-bikia", "kind": "person", "label": "Vasiliki Bikia", "url": "https://arxiv.org/abs/2511.20836", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:richard-gaus", "kind": "person", "label": "Richard Gaus", "url": "https://arxiv.org/abs/2511.20836", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:suhana-bedi", "kind": "person", "label": "Suhana Bedi", "url": "https://arxiv.org/abs/2511.20836", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hejie-cui", "kind": "person", "label": "Hejie Cui", "url": "https://arxiv.org/abs/2511.20836", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:miguel-fuentes", "kind": "person", "label": "Miguel Fuentes", "url": "https://arxiv.org/abs/2511.20836", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.10673", "kind": "paper", "label": "ZeroSumEval: An Extensible Framework For Scaling LLM Evaluation with Inter-Model Competition", "url": "https://arxiv.org/abs/2503.10673", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hisham-a-alyahya", "kind": "person", "label": "Hisham A. Alyahya", "url": "https://arxiv.org/abs/2503.10673", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haidar-khan", "kind": "person", "label": "Haidar Khan", "url": "https://arxiv.org/abs/2503.10673", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yazeed-alnumay", "kind": "person", "label": "Yazeed Alnumay", "url": "https://arxiv.org/abs/2503.10673", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:m-saiful-bari", "kind": "person", "label": "M Saiful Bari", "url": "https://arxiv.org/abs/2503.10673", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:b-lent-yener", "kind": "person", "label": "B\u00fclent Yener", "url": "https://arxiv.org/abs/2503.10673", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.00410", "kind": "paper", "label": "Agent Capsules: Quality-Gated Granularity Control for Multi-Agent LLM Pipelines", "url": "https://arxiv.org/abs/2605.00410", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:aninda-ray", "kind": "person", "label": "Aninda Ray", "url": "https://arxiv.org/abs/2605.00410", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2506.11019", "kind": "paper", "label": "Mind the Metrics: Patterns for Telemetry-Aware In-IDE AI Application Development using the Model Context Protocol (MCP)", "url": "https://arxiv.org/abs/2506.11019", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:vincent-koc", "kind": "person", "label": "Vincent Koc", "url": "https://arxiv.org/abs/2506.11019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jacques-verre", "kind": "person", "label": "Jacques Verre", "url": "https://arxiv.org/abs/2506.11019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:douglas-blank", "kind": "person", "label": "Douglas Blank", "url": "https://arxiv.org/abs/2506.11019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:abigail-morgan", "kind": "person", "label": "Abigail Morgan", "url": "https://arxiv.org/abs/2506.11019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.26521", "kind": "paper", "label": "Testing Agentic Workflows with Structural Coverage Criteria", "url": "https://arxiv.org/abs/2605.26521", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:nafiseh-kahani", "kind": "person", "label": "Nafiseh Kahani", "url": "https://arxiv.org/abs/2605.26521", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mojtaba-bagherzadeh", "kind": "person", "label": "Mojtaba Bagherzadeh", "url": "https://arxiv.org/abs/2605.26521", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.04859", "kind": "paper", "label": "Codebook Reduction and Saturation: Novel observations on Inductive Thematic Saturation for Large Language Models and initial coding in Thematic Analysis", "url": "https://arxiv.org/abs/2503.04859", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:stefano-de-paoli", "kind": "person", "label": "Stefano De Paoli", "url": "https://arxiv.org/abs/2503.04859", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:walter-stan-mathis", "kind": "person", "label": "Walter Stan Mathis", "url": "https://arxiv.org/abs/2503.04859", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.18524", "kind": "paper", "label": "metaTextGrad: Automatically optimizing language model optimizers", "url": "https://arxiv.org/abs/2505.18524", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guowei-xu", "kind": "person", "label": "Guowei Xu", "url": "https://arxiv.org/abs/2505.18524", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mert-yuksekgonul", "kind": "person", "label": "Mert Yuksekgonul", "url": "https://arxiv.org/abs/2505.18524", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:carlos-guestrin", "kind": "person", "label": "Carlos Guestrin", "url": "https://arxiv.org/abs/2505.18524", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:james-zou", "kind": "person", "label": "James Zou", "url": "https://arxiv.org/abs/2505.18524", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.13930", "kind": "paper", "label": "InPars+: Supercharging Synthetic Data Generation for Information Retrieval Systems", "url": "https://arxiv.org/abs/2508.13930", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:matey-krastev", "kind": "person", "label": "Matey Krastev", "url": "https://arxiv.org/abs/2508.13930", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:miklos-hamar", "kind": "person", "label": "Miklos Hamar", "url": "https://arxiv.org/abs/2508.13930", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:danilo-toapanta", "kind": "person", "label": "Danilo Toapanta", "url": "https://arxiv.org/abs/2508.13930", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jesse-brouwers", "kind": "person", "label": "Jesse Brouwers", "url": "https://arxiv.org/abs/2508.13930", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yibin-lei", "kind": "person", "label": "Yibin Lei", "url": "https://arxiv.org/abs/2508.13930", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2507.11299", "kind": "paper", "label": "Dr.Copilot: A Multi-Agent Prompt Optimized Assistant for Improving Patient-Doctor Communication in Romanian", "url": "https://arxiv.org/abs/2507.11299", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:andrei-niculae", "kind": "person", "label": "Andrei Niculae", "url": "https://arxiv.org/abs/2507.11299", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:adrian-cosma", "kind": "person", "label": "Adrian Cosma", "url": "https://arxiv.org/abs/2507.11299", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:cosmin-dumitrache", "kind": "person", "label": "Cosmin Dumitrache", "url": "https://arxiv.org/abs/2507.11299", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:emilian-r-doi", "kind": "person", "label": "Emilian R\u01cedoi", "url": "https://arxiv.org/abs/2507.11299", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.14629", "kind": "paper", "label": "ResearchPilot: A Local-First Multi-Agent System for Literature Synthesis and Related Work Drafting", "url": "https://arxiv.org/abs/2603.14629", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:peng-zhang", "kind": "person", "label": "Peng Zhang", "url": "https://arxiv.org/abs/2603.14629", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.20491", "kind": "paper", "label": "In-context learning capabilities of Large Language Models to detect suicide risk among adolescents from speech transcripts", "url": "https://arxiv.org/abs/2505.20491", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:filomene-roquefort", "kind": "person", "label": "Filomene Roquefort", "url": "https://arxiv.org/abs/2505.20491", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alexandre-ducorroy", "kind": "person", "label": "Alexandre Ducorroy", "url": "https://arxiv.org/abs/2505.20491", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rachid-riad", "kind": "person", "label": "Rachid Riad", "url": "https://arxiv.org/abs/2505.20491", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.11118", "kind": "paper", "label": "UMB@PerAnsSumm 2025: Enhancing Perspective-Aware Summarization with Prompt Optimization and Supervised Fine-Tuning", "url": "https://arxiv.org/abs/2503.11118", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kristin-qi", "kind": "person", "label": "Kristin Qi", "url": "https://arxiv.org/abs/2503.11118", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:youxiang-zhu", "kind": "person", "label": "Youxiang Zhu", "url": "https://arxiv.org/abs/2503.11118", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaohui-liang", "kind": "person", "label": "Xiaohui Liang", "url": "https://arxiv.org/abs/2503.11118", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.13346", "kind": "paper", "label": "AgentSPEX: An Agent SPecification and EXecution Language", "url": "https://arxiv.org/abs/2604.13346", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:pengcheng-wang", "kind": "person", "label": "Pengcheng Wang", "url": "https://arxiv.org/abs/2604.13346", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jerry-huang", "kind": "person", "label": "Jerry Huang", "url": "https://arxiv.org/abs/2604.13346", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiarui-yao", "kind": "person", "label": "Jiarui Yao", "url": "https://arxiv.org/abs/2604.13346", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rui-pan", "kind": "person", "label": "Rui Pan", "url": "https://arxiv.org/abs/2604.13346", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:peizhi-niu", "kind": "person", "label": "Peizhi Niu", "url": "https://arxiv.org/abs/2604.13346", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yaowenqi-liu", "kind": "person", "label": "Yaowenqi Liu", "url": "https://arxiv.org/abs/2604.13346", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ruida-wang", "kind": "person", "label": "Ruida Wang", "url": "https://arxiv.org/abs/2604.13346", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:renhao-lu", "kind": "person", "label": "Renhao Lu", "url": "https://arxiv.org/abs/2604.13346", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.06937", "kind": "paper", "label": "A Reproducible Optimisation Protocol for Calibrating Prompt-Based Large Language Model Workflows in Evidence Synthesis", "url": "https://arxiv.org/abs/2605.06937", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:teo-susnjak", "kind": "person", "label": "Teo Susnjak", "url": "https://arxiv.org/abs/2605.06937", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2404.14544", "kind": "paper", "label": "WangLab at MEDIQA-CORR 2024: Optimized LLM-based Programs for Medical Error Detection and Correction", "url": "https://arxiv.org/abs/2404.14544", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:augustin-toma", "kind": "person", "label": "Augustin Toma", "url": "https://arxiv.org/abs/2404.14544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ronald-xie", "kind": "person", "label": "Ronald Xie", "url": "https://arxiv.org/abs/2404.14544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:steven-palayew", "kind": "person", "label": "Steven Palayew", "url": "https://arxiv.org/abs/2404.14544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:patrick-r-lawler", "kind": "person", "label": "Patrick R. Lawler", "url": "https://arxiv.org/abs/2404.14544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bo-wang", "kind": "person", "label": "Bo Wang", "url": "https://arxiv.org/abs/2404.14544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.21907", "kind": "paper", "label": "A Large-Scale Dataset and Citation Intent Classification in Turkish with LLMs", "url": "https://arxiv.org/abs/2509.21907", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kemal-sami-karaca", "kind": "person", "label": "Kemal Sami Karaca", "url": "https://arxiv.org/abs/2509.21907", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bahaeddin-eravc", "kind": "person", "label": "Bahaeddin Eravc\u0131", "url": "https://arxiv.org/abs/2509.21907", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2502.11267", "kind": "paper", "label": "Prompting in the Dark: Assessing Human Performance in Prompt Engineering for Data Labeling When Gold Labels Are Absent", "url": "https://arxiv.org/abs/2502.11267", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zeyu-he", "kind": "person", "label": "Zeyu He", "url": "https://arxiv.org/abs/2502.11267", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:saniya-naphade", "kind": "person", "label": "Saniya Naphade", "url": "https://arxiv.org/abs/2502.11267", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ting-hao-kenneth-huang", "kind": "person", "label": "Ting-Hao 'Kenneth' Huang", "url": "https://arxiv.org/abs/2502.11267", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2407.10930", "kind": "paper", "label": "Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together", "url": "https://arxiv.org/abs/2407.10930", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dilara-soylu", "kind": "person", "label": "Dilara Soylu", "url": "https://arxiv.org/abs/2407.10930", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2511.16544", "kind": "paper", "label": "WER is Unaware: Assessing How ASR Errors Distort Clinical Understanding in Patient Facing Dialogue", "url": "https://arxiv.org/abs/2511.16544", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zachary-ellis", "kind": "person", "label": "Zachary Ellis", "url": "https://arxiv.org/abs/2511.16544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jared-joselowitz", "kind": "person", "label": "Jared Joselowitz", "url": "https://arxiv.org/abs/2511.16544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yash-deo", "kind": "person", "label": "Yash Deo", "url": "https://arxiv.org/abs/2511.16544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yajie-he", "kind": "person", "label": "Yajie He", "url": "https://arxiv.org/abs/2511.16544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:anna-kalygina", "kind": "person", "label": "Anna Kalygina", "url": "https://arxiv.org/abs/2511.16544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:aisling-higham", "kind": "person", "label": "Aisling Higham", "url": "https://arxiv.org/abs/2511.16544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mana-rahimzadeh", "kind": "person", "label": "Mana Rahimzadeh", "url": "https://arxiv.org/abs/2511.16544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yan-jia", "kind": "person", "label": "Yan Jia", "url": "https://arxiv.org/abs/2511.16544", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.11051", "kind": "paper", "label": "OpenSanctions Pairs: Large-Scale Entity Matching with LLMs", "url": "https://arxiv.org/abs/2603.11051", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chandler-smith", "kind": "person", "label": "Chandler Smith", "url": "https://arxiv.org/abs/2603.11051", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:magnus-sesodia", "kind": "person", "label": "Magnus Sesodia", "url": "https://arxiv.org/abs/2603.11051", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:friedrich-lindenberg", "kind": "person", "label": "Friedrich Lindenberg", "url": "https://arxiv.org/abs/2603.11051", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:christian-schroeder-de-witt", "kind": "person", "label": "Christian Schroeder de Witt", "url": "https://arxiv.org/abs/2603.11051", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2402.07456", "kind": "paper", "label": "OS-Copilot: Towards Generalist Computer Agents with Self-Improvement", "url": "https://arxiv.org/abs/2402.07456", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhiyong-wu", "kind": "person", "label": "Zhiyong Wu", "url": "https://arxiv.org/abs/2402.07456", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chengcheng-han", "kind": "person", "label": "Chengcheng Han", "url": "https://arxiv.org/abs/2402.07456", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zichen-ding", "kind": "person", "label": "Zichen Ding", "url": "https://arxiv.org/abs/2402.07456", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhenmin-weng", "kind": "person", "label": "Zhenmin Weng", "url": "https://arxiv.org/abs/2402.07456", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhoumianze-liu", "kind": "person", "label": "Zhoumianze Liu", "url": "https://arxiv.org/abs/2402.07456", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shunyu-yao", "kind": "person", "label": "Shunyu Yao", "url": "https://arxiv.org/abs/2402.07456", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tao-yu", "kind": "person", "label": "Tao Yu", "url": "https://arxiv.org/abs/2402.07456", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lingpeng-kong", "kind": "person", "label": "Lingpeng Kong", "url": "https://arxiv.org/abs/2402.07456", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.05665", "kind": "paper", "label": "Graph-based Agent Memory: Taxonomy, Techniques, and Applications", "url": "https://arxiv.org/abs/2602.05665", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chang-yang", "kind": "person", "label": "Chang Yang", "url": "https://arxiv.org/abs/2602.05665", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chuang-zhou", "kind": "person", "label": "Chuang Zhou", "url": "https://arxiv.org/abs/2602.05665", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yilin-xiao", "kind": "person", "label": "Yilin Xiao", "url": "https://arxiv.org/abs/2602.05665", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:su-dong", "kind": "person", "label": "Su Dong", "url": "https://arxiv.org/abs/2602.05665", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:luyao-zhuang", "kind": "person", "label": "Luyao Zhuang", "url": "https://arxiv.org/abs/2602.05665", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yujing-zhang", "kind": "person", "label": "Yujing Zhang", "url": "https://arxiv.org/abs/2602.05665", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhu-wang", "kind": "person", "label": "Zhu Wang", "url": "https://arxiv.org/abs/2602.05665", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zijin-hong", "kind": "person", "label": "Zijin Hong", "url": "https://arxiv.org/abs/2602.05665", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.07798", "kind": "paper", "label": "Lightweight LLM Agent Memory with Small Language Models", "url": "https://arxiv.org/abs/2604.07798", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiaquan-zhang", "kind": "person", "label": "Jiaquan Zhang", "url": "https://arxiv.org/abs/2604.07798", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chaoning-zhang", "kind": "person", "label": "Chaoning Zhang", "url": "https://arxiv.org/abs/2604.07798", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shuxu-chen", "kind": "person", "label": "Shuxu Chen", "url": "https://arxiv.org/abs/2604.07798", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhenzhen-huang", "kind": "person", "label": "Zhenzhen Huang", "url": "https://arxiv.org/abs/2604.07798", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:pengcheng-zheng", "kind": "person", "label": "Pengcheng Zheng", "url": "https://arxiv.org/abs/2604.07798", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhicheng-wang", "kind": "person", "label": "Zhicheng Wang", "url": "https://arxiv.org/abs/2604.07798", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ping-guo", "kind": "person", "label": "Ping Guo", "url": "https://arxiv.org/abs/2604.07798", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fan-mo", "kind": "person", "label": "Fan Mo", "url": "https://arxiv.org/abs/2604.07798", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2601.20465", "kind": "paper", "label": "BMAM: Brain-inspired Multi-Agent Memory Framework", "url": "https://arxiv.org/abs/2601.20465", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yang-li", "kind": "person", "label": "Yang Li", "url": "https://arxiv.org/abs/2601.20465", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiaxiang-liu", "kind": "person", "label": "Jiaxiang Liu", "url": "https://arxiv.org/abs/2601.20465", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yusong-wang", "kind": "person", "label": "Yusong Wang", "url": "https://arxiv.org/abs/2601.20465", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yujie-wu", "kind": "person", "label": "Yujie Wu", "url": "https://arxiv.org/abs/2601.20465", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mingkun-xu", "kind": "person", "label": "Mingkun Xu", "url": "https://arxiv.org/abs/2601.20465", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2601.18642", "kind": "paper", "label": "FadeMem: Biologically-Inspired Forgetting for Efficient Agent Memory", "url": "https://arxiv.org/abs/2601.18642", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lei-wei", "kind": "person", "label": "Lei Wei", "url": "https://arxiv.org/abs/2601.18642", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiao-peng", "kind": "person", "label": "Xiao Peng", "url": "https://arxiv.org/abs/2601.18642", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xu-dong", "kind": "person", "label": "Xu Dong", "url": "https://arxiv.org/abs/2601.18642", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:niantao-xie", "kind": "person", "label": "Niantao Xie", "url": "https://arxiv.org/abs/2601.18642", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bin-wang", "kind": "person", "label": "Bin Wang", "url": "https://arxiv.org/abs/2601.18642", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2601.01885", "kind": "paper", "label": "Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents", "url": "https://arxiv.org/abs/2601.01885", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yi-yu", "kind": "person", "label": "Yi Yu", "url": "https://arxiv.org/abs/2601.01885", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:liuyi-yao", "kind": "person", "label": "Liuyi Yao", "url": "https://arxiv.org/abs/2601.01885", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuexiang-xie", "kind": "person", "label": "Yuexiang Xie", "url": "https://arxiv.org/abs/2601.01885", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qingquan-tan", "kind": "person", "label": "Qingquan Tan", "url": "https://arxiv.org/abs/2601.01885", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiaqi-feng", "kind": "person", "label": "Jiaqi Feng", "url": "https://arxiv.org/abs/2601.01885", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yaliang-li", "kind": "person", "label": "Yaliang Li", "url": "https://arxiv.org/abs/2601.01885", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:libing-wu", "kind": "person", "label": "Libing Wu", "url": "https://arxiv.org/abs/2601.01885", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.23195", "kind": "paper", "label": "Memory Contagion: Cross-Temporal Propagation of Evaluator Bias via Agent Memory", "url": "https://arxiv.org/abs/2606.23195", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zewen-liu", "kind": "person", "label": "Zewen Liu", "url": "https://arxiv.org/abs/2606.23195", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.15701", "kind": "paper", "label": "H-Mem: A Novel Memory Mechanism for Evolving and Retrieving Agent Memory via a Hybrid Structure", "url": "https://arxiv.org/abs/2605.15701", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiawei-yu", "kind": "person", "label": "Jiawei Yu", "url": "https://arxiv.org/abs/2605.15701", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yixiang-fang", "kind": "person", "label": "Yixiang Fang", "url": "https://arxiv.org/abs/2605.15701", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xilin-liu", "kind": "person", "label": "Xilin Liu", "url": "https://arxiv.org/abs/2605.15701", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuchi-ma", "kind": "person", "label": "Yuchi Ma", "url": "https://arxiv.org/abs/2605.15701", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.18421", "kind": "paper", "label": "EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective", "url": "https://arxiv.org/abs/2605.18421", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuyao-wang", "kind": "person", "label": "Yuyao Wang", "url": "https://arxiv.org/abs/2605.18421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhongjian-zhang", "kind": "person", "label": "Zhongjian Zhang", "url": "https://arxiv.org/abs/2605.18421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mo-chi", "kind": "person", "label": "Mo Chi", "url": "https://arxiv.org/abs/2605.18421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kaichi-yu", "kind": "person", "label": "Kaichi Yu", "url": "https://arxiv.org/abs/2605.18421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuhan-li", "kind": "person", "label": "Yuhan Li", "url": "https://arxiv.org/abs/2605.18421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:miao-peng", "kind": "person", "label": "Miao Peng", "url": "https://arxiv.org/abs/2605.18421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bing-tong", "kind": "person", "label": "Bing Tong", "url": "https://arxiv.org/abs/2605.18421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chen-zhang", "kind": "person", "label": "Chen Zhang", "url": "https://arxiv.org/abs/2605.18421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.02373", "kind": "paper", "label": "A-MemGuard: A Proactive Defense Framework for LLM-Based Agent Memory", "url": "https://arxiv.org/abs/2510.02373", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qianshan-wei", "kind": "person", "label": "Qianshan Wei", "url": "https://arxiv.org/abs/2510.02373", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tengchao-yang", "kind": "person", "label": "Tengchao Yang", "url": "https://arxiv.org/abs/2510.02373", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yaochen-wang", "kind": "person", "label": "Yaochen Wang", "url": "https://arxiv.org/abs/2510.02373", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinfeng-li", "kind": "person", "label": "Xinfeng Li", "url": "https://arxiv.org/abs/2510.02373", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lijun-li", "kind": "person", "label": "Lijun Li", "url": "https://arxiv.org/abs/2510.02373", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhenfei-yin", "kind": "person", "label": "Zhenfei Yin", "url": "https://arxiv.org/abs/2510.02373", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yi-zhan", "kind": "person", "label": "Yi Zhan", "url": "https://arxiv.org/abs/2510.02373", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:thorsten-holz", "kind": "person", "label": "Thorsten Holz", "url": "https://arxiv.org/abs/2510.02373", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.06025", "kind": "paper", "label": "Learning Query-Aware Budget-Tier Routing for Runtime Agent Memory", "url": "https://arxiv.org/abs/2602.06025", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haozhen-zhang", "kind": "person", "label": "Haozhen Zhang", "url": "https://arxiv.org/abs/2602.06025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haodong-yue", "kind": "person", "label": "Haodong Yue", "url": "https://arxiv.org/abs/2602.06025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tao-feng", "kind": "person", "label": "Tao Feng", "url": "https://arxiv.org/abs/2602.06025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:quanyu-long", "kind": "person", "label": "Quanyu Long", "url": "https://arxiv.org/abs/2602.06025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jianzhu-bao", "kind": "person", "label": "Jianzhu Bao", "url": "https://arxiv.org/abs/2602.06025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bowen-jin", "kind": "person", "label": "Bowen Jin", "url": "https://arxiv.org/abs/2602.06025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:weizhi-zhang", "kind": "person", "label": "Weizhi Zhang", "url": "https://arxiv.org/abs/2602.06025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiao-li", "kind": "person", "label": "Xiao Li", "url": "https://arxiv.org/abs/2602.06025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.14498", "kind": "paper", "label": "GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations", "url": "https://arxiv.org/abs/2605.14498", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingbo-yang", "kind": "person", "label": "Jingbo Yang", "url": "https://arxiv.org/abs/2605.14498", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kwei-herng-lai", "kind": "person", "label": "Kwei-Herng Lai", "url": "https://arxiv.org/abs/2605.14498", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaowen-wang", "kind": "person", "label": "Xiaowen Wang", "url": "https://arxiv.org/abs/2605.14498", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shiyu-chang", "kind": "person", "label": "Shiyu Chang", "url": "https://arxiv.org/abs/2605.14498", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yaar-harari", "kind": "person", "label": "Yaar Harari", "url": "https://arxiv.org/abs/2605.14498", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:evgeniy-gabrilovich", "kind": "person", "label": "Evgeniy Gabrilovich", "url": "https://arxiv.org/abs/2605.14498", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.29914", "kind": "paper", "label": "MemDelta: Controlled Baselines and Hidden Confounds in Agent Memory Evaluation", "url": "https://arxiv.org/abs/2606.29914", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kuan-wang", "kind": "person", "label": "Kuan Wang", "url": "https://arxiv.org/abs/2606.29914", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.06716", "kind": "paper", "label": "From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms", "url": "https://arxiv.org/abs/2605.06716", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jinghao-luo", "kind": "person", "label": "Jinghao Luo", "url": "https://arxiv.org/abs/2605.06716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuchen-tian", "kind": "person", "label": "Yuchen Tian", "url": "https://arxiv.org/abs/2605.06716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chuxue-cao", "kind": "person", "label": "Chuxue Cao", "url": "https://arxiv.org/abs/2605.06716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ziyang-luo", "kind": "person", "label": "Ziyang Luo", "url": "https://arxiv.org/abs/2605.06716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hongzhan-lin", "kind": "person", "label": "Hongzhan Lin", "url": "https://arxiv.org/abs/2605.06716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kaixin-li", "kind": "person", "label": "Kaixin Li", "url": "https://arxiv.org/abs/2605.06716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chuyi-kong", "kind": "person", "label": "Chuyi Kong", "url": "https://arxiv.org/abs/2605.06716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ruichao-yang", "kind": "person", "label": "Ruichao Yang", "url": "https://arxiv.org/abs/2605.06716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2512.21567", "kind": "paper", "label": "Beyond Heuristics: A Decision-Theoretic Framework for Agent Memory Management", "url": "https://arxiv.org/abs/2512.21567", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:changzhi-sun", "kind": "person", "label": "Changzhi Sun", "url": "https://arxiv.org/abs/2512.21567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiangyu-chen", "kind": "person", "label": "Xiangyu Chen", "url": "https://arxiv.org/abs/2512.21567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jixiang-luo", "kind": "person", "label": "Jixiang Luo", "url": "https://arxiv.org/abs/2512.21567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dell-zhang", "kind": "person", "label": "Dell Zhang", "url": "https://arxiv.org/abs/2512.21567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xuelong-li", "kind": "person", "label": "Xuelong Li", "url": "https://arxiv.org/abs/2512.21567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2601.10702", "kind": "paper", "label": "Grounding Agent Memory in Contextual Intent", "url": "https://arxiv.org/abs/2601.10702", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ruozhen-yang", "kind": "person", "label": "Ruozhen Yang", "url": "https://arxiv.org/abs/2601.10702", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yucheng-jiang", "kind": "person", "label": "Yucheng Jiang", "url": "https://arxiv.org/abs/2601.10702", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yueqi-jiang", "kind": "person", "label": "Yueqi Jiang", "url": "https://arxiv.org/abs/2601.10702", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:priyanka-kargupta", "kind": "person", "label": "Priyanka Kargupta", "url": "https://arxiv.org/abs/2601.10702", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yunyi-zhang", "kind": "person", "label": "Yunyi Zhang", "url": "https://arxiv.org/abs/2601.10702", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiawei-han", "kind": "person", "label": "Jiawei Han", "url": "https://arxiv.org/abs/2601.10702", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.14470", "kind": "paper", "label": "GitOfThoughts: Version-Controlled Reasoning and Agent Memory You Can Replay, Diff, and Merge", "url": "https://arxiv.org/abs/2606.14470", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:pavan-c-shekar", "kind": "person", "label": "Pavan C Shekar", "url": "https://arxiv.org/abs/2606.14470", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:abhishek-h-s", "kind": "person", "label": "Abhishek H S", "url": "https://arxiv.org/abs/2606.14470", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:aswanth-krishnan", "kind": "person", "label": "Aswanth Krishnan", "url": "https://arxiv.org/abs/2606.14470", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.29341", "kind": "paper", "label": "WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction", "url": "https://arxiv.org/abs/2605.29341", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chengzhi-liu", "kind": "person", "label": "Chengzhi Liu", "url": "https://arxiv.org/abs/2605.29341", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuzhe-yang", "kind": "person", "label": "Yuzhe Yang", "url": "https://arxiv.org/abs/2605.29341", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sophia-xiao-pu", "kind": "person", "label": "Sophia Xiao Pu", "url": "https://arxiv.org/abs/2605.29341", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yepeng-liu", "kind": "person", "label": "Yepeng Liu", "url": "https://arxiv.org/abs/2605.29341", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lin-long", "kind": "person", "label": "Lin Long", "url": "https://arxiv.org/abs/2605.29341", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yichen-guo", "kind": "person", "label": "Yichen Guo", "url": "https://arxiv.org/abs/2605.29341", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:nuo-chen", "kind": "person", "label": "Nuo Chen", "url": "https://arxiv.org/abs/2605.29341", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhaotian-weng", "kind": "person", "label": "Zhaotian Weng", "url": "https://arxiv.org/abs/2605.29341", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.20117", "kind": "paper", "label": "To Know is to Construct: Schema-Constrained Generation for Agent Memory", "url": "https://arxiv.org/abs/2604.20117", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lei-zheng", "kind": "person", "label": "Lei Zheng", "url": "https://arxiv.org/abs/2604.20117", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:weinan-song", "kind": "person", "label": "Weinan Song", "url": "https://arxiv.org/abs/2604.20117", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daili-li", "kind": "person", "label": "Daili Li", "url": "https://arxiv.org/abs/2604.20117", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yanming-yang", "kind": "person", "label": "Yanming Yang", "url": "https://arxiv.org/abs/2604.20117", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.19320", "kind": "paper", "label": "Anatomy of Agentic Memory: Taxonomy and Empirical Analysis of Evaluation and System Limitations", "url": "https://arxiv.org/abs/2602.19320", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dongming-jiang", "kind": "person", "label": "Dongming Jiang", "url": "https://arxiv.org/abs/2602.19320", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yi-li", "kind": "person", "label": "Yi Li", "url": "https://arxiv.org/abs/2602.19320", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:songtao-wei", "kind": "person", "label": "Songtao Wei", "url": "https://arxiv.org/abs/2602.19320", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jinxin-yang", "kind": "person", "label": "Jinxin Yang", "url": "https://arxiv.org/abs/2602.19320", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ayushi-kishore", "kind": "person", "label": "Ayushi Kishore", "url": "https://arxiv.org/abs/2602.19320", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alysa-zhao", "kind": "person", "label": "Alysa Zhao", "url": "https://arxiv.org/abs/2602.19320", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dingyi-kang", "kind": "person", "label": "Dingyi Kang", "url": "https://arxiv.org/abs/2602.19320", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xu-hu", "kind": "person", "label": "Xu Hu", "url": "https://arxiv.org/abs/2602.19320", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2512.12686", "kind": "paper", "label": "Memoria: A Scalable Agentic Memory Framework for Personalized Conversational AI", "url": "https://arxiv.org/abs/2512.12686", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:samarth-sarin", "kind": "person", "label": "Samarth Sarin", "url": "https://arxiv.org/abs/2512.12686", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lovepreet-singh", "kind": "person", "label": "Lovepreet Singh", "url": "https://arxiv.org/abs/2512.12686", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2502.12110", "kind": "paper", "label": "A-MEM: Agentic Memory for LLM Agents", "url": "https://arxiv.org/abs/2502.12110", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wujiang-xu", "kind": "person", "label": "Wujiang Xu", "url": "https://arxiv.org/abs/2502.12110", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zujie-liang", "kind": "person", "label": "Zujie Liang", "url": "https://arxiv.org/abs/2502.12110", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kai-mei", "kind": "person", "label": "Kai Mei", "url": "https://arxiv.org/abs/2502.12110", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hang-gao", "kind": "person", "label": "Hang Gao", "url": "https://arxiv.org/abs/2502.12110", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:juntao-tan", "kind": "person", "label": "Juntao Tan", "url": "https://arxiv.org/abs/2502.12110", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yongfeng-zhang", "kind": "person", "label": "Yongfeng Zhang", "url": "https://arxiv.org/abs/2502.12110", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.01528", "kind": "paper", "label": "Joint Agent Memory and Exploration Learning via Novelty Signals", "url": "https://arxiv.org/abs/2606.01528", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shizuo-tian", "kind": "person", "label": "Shizuo Tian", "url": "https://arxiv.org/abs/2606.01528", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaohong-weng", "kind": "person", "label": "Xiaohong Weng", "url": "https://arxiv.org/abs/2606.01528", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rui-kong", "kind": "person", "label": "Rui Kong", "url": "https://arxiv.org/abs/2606.01528", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guohong-liu", "kind": "person", "label": "Guohong Liu", "url": "https://arxiv.org/abs/2606.01528", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuebing-song", "kind": "person", "label": "Yuebing Song", "url": "https://arxiv.org/abs/2606.01528", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiacheng-liu", "kind": "person", "label": "Jiacheng Liu", "url": "https://arxiv.org/abs/2606.01528", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuchen-li", "kind": "person", "label": "Yuchen Li", "url": "https://arxiv.org/abs/2606.01528", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.09747", "kind": "paper", "label": "ADAM: A Systematic Data Extraction Attack on Agent Memory via Adaptive Querying", "url": "https://arxiv.org/abs/2604.09747", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xingyu-lyu", "kind": "person", "label": "Xingyu Lyu", "url": "https://arxiv.org/abs/2604.09747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jianfeng-he", "kind": "person", "label": "Jianfeng He", "url": "https://arxiv.org/abs/2604.09747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ning-wang", "kind": "person", "label": "Ning Wang", "url": "https://arxiv.org/abs/2604.09747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yidan-hu", "kind": "person", "label": "Yidan Hu", "url": "https://arxiv.org/abs/2604.09747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tao-li", "kind": "person", "label": "Tao Li", "url": "https://arxiv.org/abs/2604.09747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:danjue-chen", "kind": "person", "label": "Danjue Chen", "url": "https://arxiv.org/abs/2604.09747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shixiong-li", "kind": "person", "label": "Shixiong Li", "url": "https://arxiv.org/abs/2604.09747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yimin-chen", "kind": "person", "label": "Yimin Chen", "url": "https://arxiv.org/abs/2604.09747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.05520", "kind": "paper", "label": "CAM: A Constructivist View of Agentic Memory for LLM-Based Reading Comprehension", "url": "https://arxiv.org/abs/2510.05520", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rui-li", "kind": "person", "label": "Rui Li", "url": "https://arxiv.org/abs/2510.05520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaohe-bo", "kind": "person", "label": "Xiaohe Bo", "url": "https://arxiv.org/abs/2510.05520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zihang-tian", "kind": "person", "label": "Zihang Tian", "url": "https://arxiv.org/abs/2510.05520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xu-chen", "kind": "person", "label": "Xu Chen", "url": "https://arxiv.org/abs/2510.05520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:quanyu-dai", "kind": "person", "label": "Quanyu Dai", "url": "https://arxiv.org/abs/2510.05520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhenhua-dong", "kind": "person", "label": "Zhenhua Dong", "url": "https://arxiv.org/abs/2510.05520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ruiming-tang", "kind": "person", "label": "Ruiming Tang", "url": "https://arxiv.org/abs/2510.05520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2601.03236", "kind": "paper", "label": "MAGMA: A Multi-Graph based Agentic Memory Architecture for AI Agents", "url": "https://arxiv.org/abs/2601.03236", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guanpeng-li", "kind": "person", "label": "Guanpeng Li", "url": "https://arxiv.org/abs/2601.03236", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bingzhe-li", "kind": "person", "label": "Bingzhe Li", "url": "https://arxiv.org/abs/2601.03236", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.23723", "kind": "paper", "label": "MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection", "url": "https://arxiv.org/abs/2605.23723", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhewen-tan", "kind": "person", "label": "Zhewen Tan", "url": "https://arxiv.org/abs/2605.23723", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yilun-yao", "kind": "person", "label": "Yilun Yao", "url": "https://arxiv.org/abs/2605.23723", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:huiyan-jin", "kind": "person", "label": "Huiyan Jin", "url": "https://arxiv.org/abs/2605.23723", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenhan-yu", "kind": "person", "label": "Wenhan Yu", "url": "https://arxiv.org/abs/2605.23723", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guoan-wang", "kind": "person", "label": "Guoan Wang", "url": "https://arxiv.org/abs/2605.23723", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mengyuan-fan", "kind": "person", "label": "Mengyuan Fan", "url": "https://arxiv.org/abs/2605.23723", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:liang-lu", "kind": "person", "label": "liang lu", "url": "https://arxiv.org/abs/2605.23723", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:feng-liu", "kind": "person", "label": "Feng Liu", "url": "https://arxiv.org/abs/2605.23723", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2512.19537", "kind": "paper", "label": "Event Extraction in Large Language Model", "url": "https://arxiv.org/abs/2512.19537", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bobo-li", "kind": "person", "label": "Bobo Li", "url": "https://arxiv.org/abs/2512.19537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xudong-han", "kind": "person", "label": "Xudong Han", "url": "https://arxiv.org/abs/2512.19537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiang-liu", "kind": "person", "label": "Jiang Liu", "url": "https://arxiv.org/abs/2512.19537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuzhe-ding", "kind": "person", "label": "Yuzhe Ding", "url": "https://arxiv.org/abs/2512.19537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:liqiang-jing", "kind": "person", "label": "Liqiang Jing", "url": "https://arxiv.org/abs/2512.19537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhaoqi-zhang", "kind": "person", "label": "Zhaoqi Zhang", "url": "https://arxiv.org/abs/2512.19537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jinheng-li", "kind": "person", "label": "Jinheng Li", "url": "https://arxiv.org/abs/2512.19537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinya-du", "kind": "person", "label": "Xinya Du", "url": "https://arxiv.org/abs/2512.19537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.15421", "kind": "paper", "label": "CLAG: Adaptive Memory Organization via Agent-Driven Clustering for Small Language Model Agents", "url": "https://arxiv.org/abs/2603.15421", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:taeyun-roh", "kind": "person", "label": "Taeyun Roh", "url": "https://arxiv.org/abs/2603.15421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wonjune-jang", "kind": "person", "label": "Wonjune Jang", "url": "https://arxiv.org/abs/2603.15421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:junha-jung", "kind": "person", "label": "Junha Jung", "url": "https://arxiv.org/abs/2603.15421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jaewoo-kang", "kind": "person", "label": "Jaewoo Kang", "url": "https://arxiv.org/abs/2603.15421", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.12285", "kind": "paper", "label": "GAM: Hierarchical Graph-based Agentic Memory for LLM Agents", "url": "https://arxiv.org/abs/2604.12285", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhaofen-wu", "kind": "person", "label": "Zhaofen Wu", "url": "https://arxiv.org/abs/2604.12285", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hanrong-zhang", "kind": "person", "label": "Hanrong Zhang", "url": "https://arxiv.org/abs/2604.12285", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fulin-lin", "kind": "person", "label": "Fulin Lin", "url": "https://arxiv.org/abs/2604.12285", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinran-xu", "kind": "person", "label": "Xinran Xu", "url": "https://arxiv.org/abs/2604.12285", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yankai-chen", "kind": "person", "label": "Yankai Chen", "url": "https://arxiv.org/abs/2604.12285", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:henry-peng-zou", "kind": "person", "label": "Henry Peng Zou", "url": "https://arxiv.org/abs/2604.12285", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shaowen-chen", "kind": "person", "label": "Shaowen Chen", "url": "https://arxiv.org/abs/2604.12285", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.13189", "kind": "paper", "label": "LLM Constitutional Multi-Agent Governance", "url": "https://arxiv.org/abs/2603.13189", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:j-de-curt", "kind": "person", "label": "J. de Curt\u00f2", "url": "https://arxiv.org/abs/2603.13189", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:i-de-zarz", "kind": "person", "label": "I. de Zarz\u00e0", "url": "https://arxiv.org/abs/2603.13189", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2412.05449", "kind": "paper", "label": "Towards Effective GenAI Multi-Agent Collaboration: Design and Evaluation for Enterprise Applications", "url": "https://arxiv.org/abs/2412.05449", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:raphael-shu", "kind": "person", "label": "Raphael Shu", "url": "https://arxiv.org/abs/2412.05449", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:nilaksh-das", "kind": "person", "label": "Nilaksh Das", "url": "https://arxiv.org/abs/2412.05449", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:michelle-yuan", "kind": "person", "label": "Michelle Yuan", "url": "https://arxiv.org/abs/2412.05449", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:monica-sunkara", "kind": "person", "label": "Monica Sunkara", "url": "https://arxiv.org/abs/2412.05449", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yi-zhang", "kind": "person", "label": "Yi Zhang", "url": "https://arxiv.org/abs/2412.05449", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.26352", "kind": "paper", "label": "The Geometry of Dialogue: Graphing Language Models to Reveal Synergistic Teams for Multi-Agent Collaboration", "url": "https://arxiv.org/abs/2510.26352", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kotaro-furuya", "kind": "person", "label": "Kotaro Furuya", "url": "https://arxiv.org/abs/2510.26352", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuichi-kitagawa", "kind": "person", "label": "Yuichi Kitagawa", "url": "https://arxiv.org/abs/2510.26352", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.00131", "kind": "paper", "label": "Thought Virus: Viral Misalignment via Subliminal Prompting in Multi-Agent Systems", "url": "https://arxiv.org/abs/2603.00131", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:moritz-weckbecker", "kind": "person", "label": "Moritz Weckbecker", "url": "https://arxiv.org/abs/2603.00131", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jonas-m-ller", "kind": "person", "label": "Jonas M\u00fcller", "url": "https://arxiv.org/abs/2603.00131", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ben-hagag", "kind": "person", "label": "Ben Hagag", "url": "https://arxiv.org/abs/2603.00131", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:michael-mulet", "kind": "person", "label": "Michael Mulet", "url": "https://arxiv.org/abs/2603.00131", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.01295", "kind": "paper", "label": "The Social Laboratory: A Psychometric Framework for Multi-Agent LLM Evaluation", "url": "https://arxiv.org/abs/2510.01295", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zarreen-reza", "kind": "person", "label": "Zarreen Reza", "url": "https://arxiv.org/abs/2510.01295", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.05980", "kind": "paper", "label": "An Interactive Multi-Agent System for Evaluation of New Product Concepts", "url": "https://arxiv.org/abs/2603.05980", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bin-xuan", "kind": "person", "label": "Bin Xuan", "url": "https://arxiv.org/abs/2603.05980", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ruo-ai", "kind": "person", "label": "Ruo Ai", "url": "https://arxiv.org/abs/2603.05980", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hakyeon-lee", "kind": "person", "label": "Hakyeon Lee", "url": "https://arxiv.org/abs/2603.05980", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2512.15790", "kind": "paper", "label": "Bilevel Optimization for Covert Memory Tampering in Heterogeneous Multi-Agent Architectures (XAMT)", "url": "https://arxiv.org/abs/2512.15790", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:akhil-sharma", "kind": "person", "label": "Akhil Sharma", "url": "https://arxiv.org/abs/2512.15790", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shaikh-yaser-arafat", "kind": "person", "label": "Shaikh Yaser Arafat", "url": "https://arxiv.org/abs/2512.15790", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jai-kumar-sharma", "kind": "person", "label": "Jai Kumar Sharma", "url": "https://arxiv.org/abs/2512.15790", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ken-huang", "kind": "person", "label": "Ken Huang", "url": "https://arxiv.org/abs/2512.15790", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2407.06567", "kind": "paper", "label": "FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making", "url": "https://arxiv.org/abs/2407.06567", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yangyang-yu", "kind": "person", "label": "Yangyang Yu", "url": "https://arxiv.org/abs/2407.06567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhiyuan-yao", "kind": "person", "label": "Zhiyuan Yao", "url": "https://arxiv.org/abs/2407.06567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haohang-li", "kind": "person", "label": "Haohang Li", "url": "https://arxiv.org/abs/2407.06567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhiyang-deng", "kind": "person", "label": "Zhiyang Deng", "url": "https://arxiv.org/abs/2407.06567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yupeng-cao", "kind": "person", "label": "Yupeng Cao", "url": "https://arxiv.org/abs/2407.06567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhi-chen", "kind": "person", "label": "Zhi Chen", "url": "https://arxiv.org/abs/2407.06567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jordan-w-suchow", "kind": "person", "label": "Jordan W. Suchow", "url": "https://arxiv.org/abs/2407.06567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rong-liu", "kind": "person", "label": "Rong Liu", "url": "https://arxiv.org/abs/2407.06567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.15968", "kind": "paper", "label": "MAC: Multi-Agent Constitution Learning", "url": "https://arxiv.org/abs/2603.15968", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rushil-thareja", "kind": "person", "label": "Rushil Thareja", "url": "https://arxiv.org/abs/2603.15968", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gautam-gupta", "kind": "person", "label": "Gautam Gupta", "url": "https://arxiv.org/abs/2603.15968", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:francesco-pinto", "kind": "person", "label": "Francesco Pinto", "url": "https://arxiv.org/abs/2603.15968", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:nils-lukas", "kind": "person", "label": "Nils Lukas", "url": "https://arxiv.org/abs/2603.15968", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.04652", "kind": "paper", "label": "LLM Collaboration With Multi-Agent Reinforcement Learning", "url": "https://arxiv.org/abs/2508.04652", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shuo-liu", "kind": "person", "label": "Shuo Liu", "url": "https://arxiv.org/abs/2508.04652", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tianle-chen", "kind": "person", "label": "Tianle Chen", "url": "https://arxiv.org/abs/2508.04652", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zeyu-liang", "kind": "person", "label": "Zeyu Liang", "url": "https://arxiv.org/abs/2508.04652", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xueguang-lyu", "kind": "person", "label": "Xueguang Lyu", "url": "https://arxiv.org/abs/2508.04652", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:christopher-amato", "kind": "person", "label": "Christopher Amato", "url": "https://arxiv.org/abs/2508.04652", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.08501", "kind": "paper", "label": "Fanar-Sadiq: A Multi-Agent Architecture for Grounded Islamic QA", "url": "https://arxiv.org/abs/2603.08501", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ummar-abbas", "kind": "person", "label": "Ummar Abbas", "url": "https://arxiv.org/abs/2603.08501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mourad-ouzzani", "kind": "person", "label": "Mourad Ouzzani", "url": "https://arxiv.org/abs/2603.08501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mohamed-y-eltabakh", "kind": "person", "label": "Mohamed Y. Eltabakh", "url": "https://arxiv.org/abs/2603.08501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:omar-sinan", "kind": "person", "label": "Omar Sinan", "url": "https://arxiv.org/abs/2603.08501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gagan-bhatia", "kind": "person", "label": "Gagan Bhatia", "url": "https://arxiv.org/abs/2603.08501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hamdy-mubarak", "kind": "person", "label": "Hamdy Mubarak", "url": "https://arxiv.org/abs/2603.08501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:majd-hawasly", "kind": "person", "label": "Majd Hawasly", "url": "https://arxiv.org/abs/2603.08501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mohammed-qusay-hashim", "kind": "person", "label": "Mohammed Qusay Hashim", "url": "https://arxiv.org/abs/2603.08501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.27409", "kind": "paper", "label": "Delayed Verification Destabilizes Multi-Agent LLM Belief: Instability Thresholds and Optimal Corrector Placement", "url": "https://arxiv.org/abs/2606.27409", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:igor-itkin", "kind": "person", "label": "Igor Itkin", "url": "https://arxiv.org/abs/2606.27409", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2507.01019", "kind": "paper", "label": "MALIBU Benchmark: Multi-Agent LLM Implicit Bias Uncovered", "url": "https://arxiv.org/abs/2507.01019", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:imran-mirza", "kind": "person", "label": "Imran Mirza", "url": "https://arxiv.org/abs/2507.01019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:cole-huang", "kind": "person", "label": "Cole Huang", "url": "https://arxiv.org/abs/2507.01019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ishwara-vasista", "kind": "person", "label": "Ishwara Vasista", "url": "https://arxiv.org/abs/2507.01019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rohan-patil", "kind": "person", "label": "Rohan Patil", "url": "https://arxiv.org/abs/2507.01019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:asli-akalin", "kind": "person", "label": "Asli Akalin", "url": "https://arxiv.org/abs/2507.01019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sean-o-brien", "kind": "person", "label": "Sean O'Brien", "url": "https://arxiv.org/abs/2507.01019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kevin-zhu", "kind": "person", "label": "Kevin Zhu", "url": "https://arxiv.org/abs/2507.01019", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2511.05269", "kind": "paper", "label": "TAMAS: Benchmarking Adversarial Risks in Multi-Agent LLM Systems", "url": "https://arxiv.org/abs/2511.05269", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ishan-kavathekar", "kind": "person", "label": "Ishan Kavathekar", "url": "https://arxiv.org/abs/2511.05269", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hemang-jain", "kind": "person", "label": "Hemang Jain", "url": "https://arxiv.org/abs/2511.05269", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ameya-rathod", "kind": "person", "label": "Ameya Rathod", "url": "https://arxiv.org/abs/2511.05269", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ponnurangam-kumaraguru", "kind": "person", "label": "Ponnurangam Kumaraguru", "url": "https://arxiv.org/abs/2511.05269", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tanuja-ganu", "kind": "person", "label": "Tanuja Ganu", "url": "https://arxiv.org/abs/2511.05269", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.00132", "kind": "paper", "label": "CoComposer: LLM Multi-agent Collaborative Music Composition", "url": "https://arxiv.org/abs/2509.00132", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:peiwen-xing", "kind": "person", "label": "Peiwen Xing", "url": "https://arxiv.org/abs/2509.00132", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:aske-plaat", "kind": "person", "label": "Aske Plaat", "url": "https://arxiv.org/abs/2509.00132", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:niki-van-stein", "kind": "person", "label": "Niki van Stein", "url": "https://arxiv.org/abs/2509.00132", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2410.07283", "kind": "paper", "label": "Prompt Infection: LLM-to-LLM Prompt Injection within Multi-Agent Systems", "url": "https://arxiv.org/abs/2410.07283", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:donghyun-lee", "kind": "person", "label": "Donghyun Lee", "url": "https://arxiv.org/abs/2410.07283", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mo-tiwari", "kind": "person", "label": "Mo Tiwari", "url": "https://arxiv.org/abs/2410.07283", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.24239", "kind": "paper", "label": "An Adversary-Resistant Multi-Agent LLM System via Credibility Scoring", "url": "https://arxiv.org/abs/2505.24239", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sana-ebrahimi", "kind": "person", "label": "Sana Ebrahimi", "url": "https://arxiv.org/abs/2505.24239", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mohsen-dehghankar", "kind": "person", "label": "Mohsen Dehghankar", "url": "https://arxiv.org/abs/2505.24239", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:abolfazl-asudeh", "kind": "person", "label": "Abolfazl Asudeh", "url": "https://arxiv.org/abs/2505.24239", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2405.14314", "kind": "paper", "label": "Towards Efficient LLM Grounding for Embodied Multi-Agent Collaboration", "url": "https://arxiv.org/abs/2405.14314", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yang-zhang", "kind": "person", "label": "Yang Zhang", "url": "https://arxiv.org/abs/2405.14314", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shixin-yang", "kind": "person", "label": "Shixin Yang", "url": "https://arxiv.org/abs/2405.14314", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chenjia-bai", "kind": "person", "label": "Chenjia Bai", "url": "https://arxiv.org/abs/2405.14314", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fei-wu", "kind": "person", "label": "Fei Wu", "url": "https://arxiv.org/abs/2405.14314", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiu-li", "kind": "person", "label": "Xiu Li", "url": "https://arxiv.org/abs/2405.14314", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhen-wang", "kind": "person", "label": "Zhen Wang", "url": "https://arxiv.org/abs/2405.14314", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.25850", "kind": "paper", "label": "Debate2Create: Robot Co-design via Multi-Agent LLM Debate", "url": "https://arxiv.org/abs/2510.25850", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kevin-qiu", "kind": "person", "label": "Kevin Qiu", "url": "https://arxiv.org/abs/2510.25850", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:marek-cygan", "kind": "person", "label": "Marek Cygan", "url": "https://arxiv.org/abs/2510.25850", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2412.01928", "kind": "paper", "label": "MALT: Improving Reasoning with Multi-Agent LLM Training", "url": "https://arxiv.org/abs/2412.01928", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sumeet-ramesh-motwani", "kind": "person", "label": "Sumeet Ramesh Motwani", "url": "https://arxiv.org/abs/2412.01928", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rocktim-jyoti-das", "kind": "person", "label": "Rocktim Jyoti Das", "url": "https://arxiv.org/abs/2412.01928", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rafael-rafailov", "kind": "person", "label": "Rafael Rafailov", "url": "https://arxiv.org/abs/2412.01928", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ivan-laptev", "kind": "person", "label": "Ivan Laptev", "url": "https://arxiv.org/abs/2412.01928", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:philip-h-s-torr", "kind": "person", "label": "Philip H. S. Torr", "url": "https://arxiv.org/abs/2412.01928", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fabio-pizzati", "kind": "person", "label": "Fabio Pizzati", "url": "https://arxiv.org/abs/2412.01928", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ronald-clark", "kind": "person", "label": "Ronald Clark", "url": "https://arxiv.org/abs/2412.01928", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.08268", "kind": "paper", "label": "Insider Attacks in Multi-Agent LLM Consensus Systems", "url": "https://arxiv.org/abs/2605.08268", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaolin-sun", "kind": "person", "label": "Xiaolin Sun", "url": "https://arxiv.org/abs/2605.08268", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zixuan-liu", "kind": "person", "label": "Zixuan Liu", "url": "https://arxiv.org/abs/2605.08268", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yibin-hu", "kind": "person", "label": "Yibin Hu", "url": "https://arxiv.org/abs/2605.08268", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zizhan-zheng", "kind": "person", "label": "Zizhan Zheng", "url": "https://arxiv.org/abs/2605.08268", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2511.15755", "kind": "paper", "label": "Multi-Agent LLM Orchestration Achieves Deterministic, High-Quality Decision Support for Incident Response", "url": "https://arxiv.org/abs/2511.15755", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:philip-drammeh", "kind": "person", "label": "Philip Drammeh", "url": "https://arxiv.org/abs/2511.15755", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.13707", "kind": "paper", "label": "Orchestra-o1: Omnimodal Agent Orchestration", "url": "https://arxiv.org/abs/2606.13707", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fan-zhang", "kind": "person", "label": "Fan Zhang", "url": "https://arxiv.org/abs/2606.13707", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:vireo-zhang", "kind": "person", "label": "Vireo Zhang", "url": "https://arxiv.org/abs/2606.13707", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shengju-qian", "kind": "person", "label": "Shengju Qian", "url": "https://arxiv.org/abs/2606.13707", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haoxuan-li", "kind": "person", "label": "Haoxuan Li", "url": "https://arxiv.org/abs/2606.13707", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hao-wu", "kind": "person", "label": "Hao Wu", "url": "https://arxiv.org/abs/2606.13707", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jinyang-wu", "kind": "person", "label": "Jinyang Wu", "url": "https://arxiv.org/abs/2606.13707", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:donghao-zhou", "kind": "person", "label": "Donghao Zhou", "url": "https://arxiv.org/abs/2606.13707", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhihong-zhu", "kind": "person", "label": "Zhihong Zhu", "url": "https://arxiv.org/abs/2606.13707", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2512.09543", "kind": "paper", "label": "SWEnergy: An Empirical Study on Energy Efficiency in Agentic Issue Resolution Frameworks with SLMs", "url": "https://arxiv.org/abs/2512.09543", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:arihant-tripathy", "kind": "person", "label": "Arihant Tripathy", "url": "https://arxiv.org/abs/2512.09543", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ch-pavan-harshit", "kind": "person", "label": "Ch Pavan Harshit", "url": "https://arxiv.org/abs/2512.09543", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:karthik-vaidhyanathan", "kind": "person", "label": "Karthik Vaidhyanathan", "url": "https://arxiv.org/abs/2512.09543", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.03312", "kind": "paper", "label": "MemFlow: Intent-Driven Memory Orchestration for Small Language Model Agents", "url": "https://arxiv.org/abs/2605.03312", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiayi-chen", "kind": "person", "label": "Jiayi Chen", "url": "https://arxiv.org/abs/2605.03312", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yingcong-li", "kind": "person", "label": "Yingcong Li", "url": "https://arxiv.org/abs/2605.03312", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guiling-wang", "kind": "person", "label": "Guiling Wang", "url": "https://arxiv.org/abs/2605.03312", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.25746", "kind": "paper", "label": "Multi-Agent Coordination Adaptation via Structure-Guided Orchestration", "url": "https://arxiv.org/abs/2605.25746", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haoran-li", "kind": "person", "label": "Haoran Li", "url": "https://arxiv.org/abs/2605.25746", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shulun-chen", "kind": "person", "label": "Shulun Chen", "url": "https://arxiv.org/abs/2605.25746", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shaoyuan-sun", "kind": "person", "label": "Shaoyuan Sun", "url": "https://arxiv.org/abs/2605.25746", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hanchen-wang", "kind": "person", "label": "Hanchen Wang", "url": "https://arxiv.org/abs/2605.25746", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.13598", "kind": "paper", "label": "Reward Modeling for Multi-Agent Orchestration", "url": "https://arxiv.org/abs/2606.13598", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:king-yeung-tsang", "kind": "person", "label": "King Yeung Tsang", "url": "https://arxiv.org/abs/2606.13598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zihao-zhao", "kind": "person", "label": "Zihao Zhao", "url": "https://arxiv.org/abs/2606.13598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:vishal-venkataramani", "kind": "person", "label": "Vishal Venkataramani", "url": "https://arxiv.org/abs/2606.13598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haizhou-shi", "kind": "person", "label": "Haizhou Shi", "url": "https://arxiv.org/abs/2606.13598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zixuan-ke", "kind": "person", "label": "Zixuan Ke", "url": "https://arxiv.org/abs/2606.13598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:semih-yavuz", "kind": "person", "label": "Semih Yavuz", "url": "https://arxiv.org/abs/2606.13598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shafiq-joty", "kind": "person", "label": "Shafiq Joty", "url": "https://arxiv.org/abs/2606.13598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hao-wang", "kind": "person", "label": "Hao Wang", "url": "https://arxiv.org/abs/2606.13598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.22823", "kind": "paper", "label": "Empirical Comparison of Agent Communication Protocols for Task Orchestration", "url": "https://arxiv.org/abs/2603.22823", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ivan-dobrovolskyi", "kind": "person", "label": "Ivan Dobrovolskyi", "url": "https://arxiv.org/abs/2603.22823", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.00326", "kind": "paper", "label": "Reasoning-Aware Prompt Orchestration: A Foundation Model for Multi-Agent Language Model Coordination", "url": "https://arxiv.org/abs/2510.00326", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hassen-dhrif", "kind": "person", "label": "Hassen Dhrif", "url": "https://arxiv.org/abs/2510.00326", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.19896", "kind": "paper", "label": "Utility-Guided Agent Orchestration for Efficient LLM Tool Use", "url": "https://arxiv.org/abs/2603.19896", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:boyan-liu", "kind": "person", "label": "Boyan Liu", "url": "https://arxiv.org/abs/2603.19896", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gongming-zhao", "kind": "person", "label": "Gongming Zhao", "url": "https://arxiv.org/abs/2603.19896", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hongli-xu", "kind": "person", "label": "Hongli Xu", "url": "https://arxiv.org/abs/2603.19896", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.02801", "kind": "paper", "label": "Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces", "url": "https://arxiv.org/abs/2605.02801", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chenchen-zhang", "kind": "person", "label": "Chenchen Zhang", "url": "https://arxiv.org/abs/2605.02801", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.01416", "kind": "paper", "label": "Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems", "url": "https://arxiv.org/abs/2606.01416", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rahul-suresh-babu", "kind": "person", "label": "Rahul Suresh Babu", "url": "https://arxiv.org/abs/2606.01416", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:adarsh-agrawal", "kind": "person", "label": "Adarsh Agrawal", "url": "https://arxiv.org/abs/2606.01416", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2601.21822", "kind": "paper", "label": "CORE:Toward Ubiquitous 6G Intelligence Through Collaborative Orchestration of Large Language Model Agents Over Hierarchical Edge", "url": "https://arxiv.org/abs/2601.21822", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zitong-yu", "kind": "person", "label": "Zitong Yu", "url": "https://arxiv.org/abs/2601.21822", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:boquan-sun", "kind": "person", "label": "Boquan Sun", "url": "https://arxiv.org/abs/2601.21822", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zheyan-qu", "kind": "person", "label": "Zheyan Qu", "url": "https://arxiv.org/abs/2601.21822", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xing-zhang", "kind": "person", "label": "Xing Zhang", "url": "https://arxiv.org/abs/2601.21822", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2412.17964", "kind": "paper", "label": "Dynamic Multi-Agent Orchestration and Retrieval for Multi-Source Question-Answer Systems using Large Language Models", "url": "https://arxiv.org/abs/2412.17964", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:antony-seabra", "kind": "person", "label": "Antony Seabra", "url": "https://arxiv.org/abs/2412.17964", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:claudio-cavalcante", "kind": "person", "label": "Claudio Cavalcante", "url": "https://arxiv.org/abs/2412.17964", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:joao-nepomuceno", "kind": "person", "label": "Joao Nepomuceno", "url": "https://arxiv.org/abs/2412.17964", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lucas-lago", "kind": "person", "label": "Lucas Lago", "url": "https://arxiv.org/abs/2412.17964", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:nicolaas-ruberg", "kind": "person", "label": "Nicolaas Ruberg", "url": "https://arxiv.org/abs/2412.17964", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sergio-lifschitz", "kind": "person", "label": "Sergio Lifschitz", "url": "https://arxiv.org/abs/2412.17964", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.14483", "kind": "paper", "label": "LEMON: Learning Executable Multi-Agent Orchestration via Counterfactual Reinforcement Learning", "url": "https://arxiv.org/abs/2605.14483", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xudong-chen", "kind": "person", "label": "Xudong Chen", "url": "https://arxiv.org/abs/2605.14483", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yixin-liu", "kind": "person", "label": "Yixin Liu", "url": "https://arxiv.org/abs/2605.14483", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hua-wei", "kind": "person", "label": "Hua Wei", "url": "https://arxiv.org/abs/2605.14483", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kaize-ding", "kind": "person", "label": "Kaize Ding", "url": "https://arxiv.org/abs/2605.14483", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.16873", "kind": "paper", "label": "AdaptOrch: Task-Adaptive Multi-Agent Orchestration in the Era of LLM Performance Convergence", "url": "https://arxiv.org/abs/2602.16873", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:geunbin-yu", "kind": "person", "label": "Geunbin Yu", "url": "https://arxiv.org/abs/2602.16873", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.19591", "kind": "paper", "label": "Multi-Agent Collaboration via Evolving Orchestration", "url": "https://arxiv.org/abs/2505.19591", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yufan-dang", "kind": "person", "label": "Yufan Dang", "url": "https://arxiv.org/abs/2505.19591", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chen-qian", "kind": "person", "label": "Chen Qian", "url": "https://arxiv.org/abs/2505.19591", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xueheng-luo", "kind": "person", "label": "Xueheng Luo", "url": "https://arxiv.org/abs/2505.19591", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingru-fan", "kind": "person", "label": "Jingru Fan", "url": "https://arxiv.org/abs/2505.19591", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zihao-xie", "kind": "person", "label": "Zihao Xie", "url": "https://arxiv.org/abs/2505.19591", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ruijie-shi", "kind": "person", "label": "Ruijie Shi", "url": "https://arxiv.org/abs/2505.19591", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:weize-chen", "kind": "person", "label": "Weize Chen", "url": "https://arxiv.org/abs/2505.19591", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:cheng-yang", "kind": "person", "label": "Cheng Yang", "url": "https://arxiv.org/abs/2505.19591", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.31174", "kind": "paper", "label": "ClawArena-Team: Benchmarking Subagent Orchestration and Dynamic Workflows in Language-Model Agents", "url": "https://arxiv.org/abs/2606.31174", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kaiwen-xiong", "kind": "person", "label": "Kaiwen Xiong", "url": "https://arxiv.org/abs/2606.31174", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haonian-ji", "kind": "person", "label": "Haonian Ji", "url": "https://arxiv.org/abs/2606.31174", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shi-qiu", "kind": "person", "label": "Shi Qiu", "url": "https://arxiv.org/abs/2606.31174", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zeyu-zheng", "kind": "person", "label": "Zeyu Zheng", "url": "https://arxiv.org/abs/2606.31174", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:cihang-xie", "kind": "person", "label": "Cihang Xie", "url": "https://arxiv.org/abs/2606.31174", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinyu-ye", "kind": "person", "label": "Xinyu Ye", "url": "https://arxiv.org/abs/2606.31174", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:huaxiu-yao", "kind": "person", "label": "Huaxiu Yao", "url": "https://arxiv.org/abs/2606.31174", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.24354", "kind": "paper", "label": "Unifying Language Agent Algorithms with Graph-based Orchestration Engine for Reproducible Agent Research", "url": "https://arxiv.org/abs/2505.24354", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qianqian-zhang", "kind": "person", "label": "Qianqian Zhang", "url": "https://arxiv.org/abs/2505.24354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiajia-liao", "kind": "person", "label": "Jiajia Liao", "url": "https://arxiv.org/abs/2505.24354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:heting-ying", "kind": "person", "label": "Heting Ying", "url": "https://arxiv.org/abs/2505.24354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yibo-ma", "kind": "person", "label": "Yibo Ma", "url": "https://arxiv.org/abs/2505.24354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haozhan-shen", "kind": "person", "label": "Haozhan Shen", "url": "https://arxiv.org/abs/2505.24354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingcheng-li", "kind": "person", "label": "Jingcheng Li", "url": "https://arxiv.org/abs/2505.24354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:peng-liu", "kind": "person", "label": "Peng Liu", "url": "https://arxiv.org/abs/2505.24354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lu-zhang", "kind": "person", "label": "Lu Zhang", "url": "https://arxiv.org/abs/2505.24354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.21255", "kind": "paper", "label": "A General Equilibrium Theory of Orchestrated AI Agent Systems", "url": "https://arxiv.org/abs/2602.21255", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jean-philippe-garnier", "kind": "person", "label": "Jean-Philippe Garnier", "url": "https://arxiv.org/abs/2602.21255", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.23537", "kind": "paper", "label": "Beyond the Strongest LLM: Multi-Turn Multi-Agent Orchestration vs. Single LLMs on Benchmarks", "url": "https://arxiv.org/abs/2509.23537", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:aaron-xuxiang-tian", "kind": "person", "label": "Aaron Xuxiang Tian", "url": "https://arxiv.org/abs/2509.23537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ruofan-zhang", "kind": "person", "label": "Ruofan Zhang", "url": "https://arxiv.org/abs/2509.23537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiayao-tang", "kind": "person", "label": "Jiayao Tang", "url": "https://arxiv.org/abs/2509.23537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:young-min-cho", "kind": "person", "label": "Young Min Cho", "url": "https://arxiv.org/abs/2509.23537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xueqian-li", "kind": "person", "label": "Xueqian Li", "url": "https://arxiv.org/abs/2509.23537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qiang-yi", "kind": "person", "label": "Qiang Yi", "url": "https://arxiv.org/abs/2509.23537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ji-wang", "kind": "person", "label": "Ji Wang", "url": "https://arxiv.org/abs/2509.23537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhunping-zhang", "kind": "person", "label": "Zhunping Zhang", "url": "https://arxiv.org/abs/2509.23537", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2403.13721", "kind": "paper", "label": "Large Language Models meet Network Slicing Management and Orchestration", "url": "https://arxiv.org/abs/2403.13721", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:abdulhalim-dandoush", "kind": "person", "label": "Abdulhalim Dandoush", "url": "https://arxiv.org/abs/2403.13721", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:viswanath-kumarskandpriya", "kind": "person", "label": "Viswanath Kumarskandpriya", "url": "https://arxiv.org/abs/2403.13721", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mueen-uddin", "kind": "person", "label": "Mueen Uddin", "url": "https://arxiv.org/abs/2403.13721", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:usman-khalil", "kind": "person", "label": "Usman Khalil", "url": "https://arxiv.org/abs/2403.13721", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.12129", "kind": "paper", "label": "Aethon: A Reference-Based Replication Primitive for Constant-Time Instantiation of Stateful AI Agents", "url": "https://arxiv.org/abs/2604.12129", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:swanand-rao", "kind": "person", "label": "Swanand Rao", "url": "https://arxiv.org/abs/2604.12129", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kiran-kashalkar", "kind": "person", "label": "Kiran Kashalkar", "url": "https://arxiv.org/abs/2604.12129", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:parvathi-somashekar", "kind": "person", "label": "Parvathi Somashekar", "url": "https://arxiv.org/abs/2604.12129", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:priya-krishnan", "kind": "person", "label": "Priya Krishnan", "url": "https://arxiv.org/abs/2604.12129", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.15055", "kind": "paper", "label": "Beyond Context Sharing: A Unified Agent Communication Protocol (ACP) for Secure, Federated, and Autonomous Agent-to-Agent (A2A) Orchestration", "url": "https://arxiv.org/abs/2602.15055", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:naveen-kumar-krishnan", "kind": "person", "label": "Naveen Kumar Krishnan", "url": "https://arxiv.org/abs/2602.15055", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2406.08979", "kind": "paper", "label": "Multi-Agent Collaboration via Cross-Team Orchestration", "url": "https://arxiv.org/abs/2406.08979", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhuoyun-du", "kind": "person", "label": "Zhuoyun Du", "url": "https://arxiv.org/abs/2406.08979", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wei-liu", "kind": "person", "label": "Wei Liu", "url": "https://arxiv.org/abs/2406.08979", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yifei-wang", "kind": "person", "label": "YiFei Wang", "url": "https://arxiv.org/abs/2406.08979", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rennai-qiu", "kind": "person", "label": "Rennai Qiu", "url": "https://arxiv.org/abs/2406.08979", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.13227", "kind": "paper", "label": "An Agentic AI Control Plane for 6G Network Slice Orchestration, Monitoring, and Trading", "url": "https://arxiv.org/abs/2602.13227", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:eranga-bandara", "kind": "person", "label": "Eranga Bandara", "url": "https://arxiv.org/abs/2602.13227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ross-gore", "kind": "person", "label": "Ross Gore", "url": "https://arxiv.org/abs/2602.13227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sachin-shetty", "kind": "person", "label": "Sachin Shetty", "url": "https://arxiv.org/abs/2602.13227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ravi-mukkamala", "kind": "person", "label": "Ravi Mukkamala", "url": "https://arxiv.org/abs/2602.13227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tharaka-hewa", "kind": "person", "label": "Tharaka Hewa", "url": "https://arxiv.org/abs/2602.13227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:abdul-rahman", "kind": "person", "label": "Abdul Rahman", "url": "https://arxiv.org/abs/2602.13227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xueping-liang", "kind": "person", "label": "Xueping Liang", "url": "https://arxiv.org/abs/2602.13227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:safdar-h-bouk", "kind": "person", "label": "Safdar H. Bouk", "url": "https://arxiv.org/abs/2602.13227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2507.01599", "kind": "paper", "label": "Data Agent: A Holistic Architecture for Orchestrating Data+AI Ecosystems", "url": "https://arxiv.org/abs/2507.01599", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhaoyan-sun", "kind": "person", "label": "Zhaoyan Sun", "url": "https://arxiv.org/abs/2507.01599", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiayi-wang", "kind": "person", "label": "Jiayi Wang", "url": "https://arxiv.org/abs/2507.01599", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinyang-zhao", "kind": "person", "label": "Xinyang Zhao", "url": "https://arxiv.org/abs/2507.01599", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiachi-wang", "kind": "person", "label": "Jiachi Wang", "url": "https://arxiv.org/abs/2507.01599", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guoliang-li", "kind": "person", "label": "Guoliang Li", "url": "https://arxiv.org/abs/2507.01599", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.03005", "kind": "paper", "label": "OrchMAS: Orchestrated Reasoning with Multi Collaborative Heterogeneous Scientific Expert Structured Agents", "url": "https://arxiv.org/abs/2603.03005", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yichao-feng", "kind": "person", "label": "Yichao Feng", "url": "https://arxiv.org/abs/2603.03005", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haoran-luo", "kind": "person", "label": "Haoran Luo", "url": "https://arxiv.org/abs/2603.03005", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhenghong-lin", "kind": "person", "label": "Zhenghong Lin", "url": "https://arxiv.org/abs/2603.03005", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yiqun-sun", "kind": "person", "label": "Yiqun Sun", "url": "https://arxiv.org/abs/2603.03005", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:pengfei-wei", "kind": "person", "label": "Pengfei Wei", "url": "https://arxiv.org/abs/2603.03005", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lawrence-b-hsieh", "kind": "person", "label": "Lawrence B. Hsieh", "url": "https://arxiv.org/abs/2603.03005", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:anh-tuan-luu", "kind": "person", "label": "Anh Tuan Luu", "url": "https://arxiv.org/abs/2603.03005", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2410.21784", "kind": "paper", "label": "MARCO: Multi-Agent Real-time Chat Orchestration", "url": "https://arxiv.org/abs/2410.21784", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:anubhav-shrimal", "kind": "person", "label": "Anubhav Shrimal", "url": "https://arxiv.org/abs/2410.21784", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:stanley-kanagaraj", "kind": "person", "label": "Stanley Kanagaraj", "url": "https://arxiv.org/abs/2410.21784", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kriti-biswas", "kind": "person", "label": "Kriti Biswas", "url": "https://arxiv.org/abs/2410.21784", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:swarnalatha-raghuraman", "kind": "person", "label": "Swarnalatha Raghuraman", "url": "https://arxiv.org/abs/2410.21784", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:anish-nediyanchath", "kind": "person", "label": "Anish Nediyanchath", "url": "https://arxiv.org/abs/2410.21784", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:promod-yenigalla", "kind": "person", "label": "Promod Yenigalla", "url": "https://arxiv.org/abs/2410.21784", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.00922", "kind": "paper", "label": "A Machine-to-Machine Knowledge-Guided LLM Agent for Generalizable Radiotherapy Treatment Planning", "url": "https://arxiv.org/abs/2606.00922", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:md-mainul-abrar", "kind": "person", "label": "Md Mainul Abrar", "url": "https://arxiv.org/abs/2606.00922", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xun-jia", "kind": "person", "label": "Xun Jia", "url": "https://arxiv.org/abs/2606.00922", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yujie-chi", "kind": "person", "label": "Yujie Chi", "url": "https://arxiv.org/abs/2606.00922", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2402.02716", "kind": "paper", "label": "Understanding the planning of LLM agents: A survey", "url": "https://arxiv.org/abs/2402.02716", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xu-huang", "kind": "person", "label": "Xu Huang", "url": "https://arxiv.org/abs/2402.02716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:weiwen-liu", "kind": "person", "label": "Weiwen Liu", "url": "https://arxiv.org/abs/2402.02716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaolong-chen", "kind": "person", "label": "Xiaolong Chen", "url": "https://arxiv.org/abs/2402.02716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xingmei-wang", "kind": "person", "label": "Xingmei Wang", "url": "https://arxiv.org/abs/2402.02716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:defu-lian", "kind": "person", "label": "Defu Lian", "url": "https://arxiv.org/abs/2402.02716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yasheng-wang", "kind": "person", "label": "Yasheng Wang", "url": "https://arxiv.org/abs/2402.02716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.12740", "kind": "paper", "label": "ToolTree: Efficient LLM Agent Tool Planning via Dual-Feedback Monte Carlo Tree Search and Bidirectional Pruning", "url": "https://arxiv.org/abs/2603.12740", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shuo-yang", "kind": "person", "label": "Shuo Yang", "url": "https://arxiv.org/abs/2603.12740", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:soyeon-caren-han", "kind": "person", "label": "Soyeon Caren Han", "url": "https://arxiv.org/abs/2603.12740", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yihao-ding", "kind": "person", "label": "Yihao Ding", "url": "https://arxiv.org/abs/2603.12740", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shuhe-wang", "kind": "person", "label": "Shuhe Wang", "url": "https://arxiv.org/abs/2603.12740", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:eduard-hoy", "kind": "person", "label": "Eduard Hoy", "url": "https://arxiv.org/abs/2603.12740", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.12501", "kind": "paper", "label": "ALAS: A Stateful Multi-LLM Agent Framework for Disruption-Aware Planning", "url": "https://arxiv.org/abs/2505.12501", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:edward-y-chang", "kind": "person", "label": "Edward Y. Chang", "url": "https://arxiv.org/abs/2505.12501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:longling-geng", "kind": "person", "label": "Longling Geng", "url": "https://arxiv.org/abs/2505.12501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2502.05227", "kind": "paper", "label": "Robotouille: An Asynchronous Planning Benchmark for LLM Agents", "url": "https://arxiv.org/abs/2502.05227", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gonzalo-gonzalez-pumariega", "kind": "person", "label": "Gonzalo Gonzalez-Pumariega", "url": "https://arxiv.org/abs/2502.05227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:leong-su-yean", "kind": "person", "label": "Leong Su Yean", "url": "https://arxiv.org/abs/2502.05227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:neha-sunkara", "kind": "person", "label": "Neha Sunkara", "url": "https://arxiv.org/abs/2502.05227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sanjiban-choudhury", "kind": "person", "label": "Sanjiban Choudhury", "url": "https://arxiv.org/abs/2502.05227", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.10507", "kind": "paper", "label": "HIPIF: Hierarchical Planning and Information Folding for Long-Horizon LLM Agent Learning", "url": "https://arxiv.org/abs/2606.10507", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:juncheng-diao", "kind": "person", "label": "Juncheng Diao", "url": "https://arxiv.org/abs/2606.10507", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhicong-lu", "kind": "person", "label": "Zhicong Lu", "url": "https://arxiv.org/abs/2606.10507", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:peiguang-li", "kind": "person", "label": "Peiguang Li", "url": "https://arxiv.org/abs/2606.10507", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yongwei-zhou", "kind": "person", "label": "Yongwei Zhou", "url": "https://arxiv.org/abs/2606.10507", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:changyuan-tian", "kind": "person", "label": "Changyuan Tian", "url": "https://arxiv.org/abs/2606.10507", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qingbin-li", "kind": "person", "label": "Qingbin Li", "url": "https://arxiv.org/abs/2606.10507", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rongxiang-weng", "kind": "person", "label": "Rongxiang Weng", "url": "https://arxiv.org/abs/2606.10507", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingang-wang", "kind": "person", "label": "Jingang Wang", "url": "https://arxiv.org/abs/2606.10507", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.09474", "kind": "paper", "label": "Surgical AI Copilot: Energy-Based Fourier Gradient Low-Rank Adaptation for Surgical LLM Agent Reasoning and Planning", "url": "https://arxiv.org/abs/2503.09474", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiayuan-huang", "kind": "person", "label": "Jiayuan Huang", "url": "https://arxiv.org/abs/2503.09474", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:runlong-he", "kind": "person", "label": "Runlong He", "url": "https://arxiv.org/abs/2503.09474", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:danyal-zaman-khan", "kind": "person", "label": "Danyal Zaman Khan", "url": "https://arxiv.org/abs/2503.09474", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:evangelos-b-mazomenos", "kind": "person", "label": "Evangelos B. Mazomenos", "url": "https://arxiv.org/abs/2503.09474", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:danail-stoyanov", "kind": "person", "label": "Danail Stoyanov", "url": "https://arxiv.org/abs/2503.09474", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hani-marcus", "kind": "person", "label": "Hani Marcus", "url": "https://arxiv.org/abs/2503.09474", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:linzhe-jiang", "kind": "person", "label": "Linzhe Jiang", "url": "https://arxiv.org/abs/2503.09474", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:matthew-j-clarkson", "kind": "person", "label": "Matthew J Clarkson", "url": "https://arxiv.org/abs/2503.09474", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2502.01390", "kind": "paper", "label": "Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistant", "url": "https://arxiv.org/abs/2502.01390", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gaole-he", "kind": "person", "label": "Gaole He", "url": "https://arxiv.org/abs/2502.01390", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gianluca-demartini", "kind": "person", "label": "Gianluca Demartini", "url": "https://arxiv.org/abs/2502.01390", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ujwal-gadiraju", "kind": "person", "label": "Ujwal Gadiraju", "url": "https://arxiv.org/abs/2502.01390", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2404.17833", "kind": "paper", "label": "Testing and Understanding Erroneous Planning in LLM Agents through Synthesized User Inputs", "url": "https://arxiv.org/abs/2404.17833", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhenlan-ji", "kind": "person", "label": "Zhenlan Ji", "url": "https://arxiv.org/abs/2404.17833", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daoyuan-wu", "kind": "person", "label": "Daoyuan Wu", "url": "https://arxiv.org/abs/2404.17833", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:pingchuan-ma", "kind": "person", "label": "Pingchuan Ma", "url": "https://arxiv.org/abs/2404.17833", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zongjie-li", "kind": "person", "label": "Zongjie Li", "url": "https://arxiv.org/abs/2404.17833", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shuai-wang", "kind": "person", "label": "Shuai Wang", "url": "https://arxiv.org/abs/2404.17833", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.30639", "kind": "paper", "label": "Self-Evolving World Models for LLM Agent Planning", "url": "https://arxiv.org/abs/2606.30639", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xuan-zhang", "kind": "person", "label": "Xuan Zhang", "url": "https://arxiv.org/abs/2606.30639", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenxuan-zhang", "kind": "person", "label": "Wenxuan Zhang", "url": "https://arxiv.org/abs/2606.30639", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:see-kiong-ng", "kind": "person", "label": "See-Kiong Ng", "url": "https://arxiv.org/abs/2606.30639", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yang-deng", "kind": "person", "label": "Yang Deng", "url": "https://arxiv.org/abs/2606.30639", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.19598", "kind": "paper", "label": "Encouraging Good Processes Without the Need for Good Answers: Reinforcement Learning for LLM Agent Planning", "url": "https://arxiv.org/abs/2508.19598", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhiwei-li", "kind": "person", "label": "Zhiwei Li", "url": "https://arxiv.org/abs/2508.19598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yong-hu", "kind": "person", "label": "Yong Hu", "url": "https://arxiv.org/abs/2508.19598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenqing-wang", "kind": "person", "label": "Wenqing Wang", "url": "https://arxiv.org/abs/2508.19598", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2511.02424", "kind": "paper", "label": "ReAcTree: Hierarchical LLM Agent Trees with Control Flow for Long-Horizon Task Planning", "url": "https://arxiv.org/abs/2511.02424", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jae-woo-choi", "kind": "person", "label": "Jae-Woo Choi", "url": "https://arxiv.org/abs/2511.02424", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hyungmin-kim", "kind": "person", "label": "Hyungmin Kim", "url": "https://arxiv.org/abs/2511.02424", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hyobin-ong", "kind": "person", "label": "Hyobin Ong", "url": "https://arxiv.org/abs/2511.02424", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:youngwoo-yoon", "kind": "person", "label": "Youngwoo Yoon", "url": "https://arxiv.org/abs/2511.02424", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:minsu-jang", "kind": "person", "label": "Minsu Jang", "url": "https://arxiv.org/abs/2511.02424", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dohyung-kim", "kind": "person", "label": "Dohyung Kim", "url": "https://arxiv.org/abs/2511.02424", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jaehong-kim", "kind": "person", "label": "Jaehong Kim", "url": "https://arxiv.org/abs/2511.02424", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.22718", "kind": "paper", "label": "LLM-ABM for Transportation: Assessing the Potential of LLM Agents in System Analysis", "url": "https://arxiv.org/abs/2503.22718", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tianming-liu", "kind": "person", "label": "Tianming Liu", "url": "https://arxiv.org/abs/2503.22718", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jirong-yang", "kind": "person", "label": "Jirong Yang", "url": "https://arxiv.org/abs/2503.22718", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yafeng-yin", "kind": "person", "label": "Yafeng Yin", "url": "https://arxiv.org/abs/2503.22718", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.04874", "kind": "paper", "label": "Agent Planning Benchmark: A Diagnostic Framework for Planning Capabilities in LLM Agents", "url": "https://arxiv.org/abs/2606.04874", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haoyu-sun", "kind": "person", "label": "Haoyu Sun", "url": "https://arxiv.org/abs/2606.04874", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenxuan-wang", "kind": "person", "label": "Wenxuan Wang", "url": "https://arxiv.org/abs/2606.04874", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mingyang-song", "kind": "person", "label": "Mingyang Song", "url": "https://arxiv.org/abs/2606.04874", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jujie-he", "kind": "person", "label": "Jujie He", "url": "https://arxiv.org/abs/2606.04874", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:weinan-zhang", "kind": "person", "label": "Weinan Zhang", "url": "https://arxiv.org/abs/2606.04874", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yang-liu", "kind": "person", "label": "Yang Liu", "url": "https://arxiv.org/abs/2606.04874", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yang-yang", "kind": "person", "label": "Yang Yang", "url": "https://arxiv.org/abs/2606.04874", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yu-cheng", "kind": "person", "label": "Yu Cheng", "url": "https://arxiv.org/abs/2606.04874", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2512.11143", "kind": "paper", "label": "Automated Penetration Testing with LLM Agents and Classical Planning", "url": "https://arxiv.org/abs/2512.11143", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lingzhi-wang", "kind": "person", "label": "Lingzhi Wang", "url": "https://arxiv.org/abs/2512.11143", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinyi-shi", "kind": "person", "label": "Xinyi Shi", "url": "https://arxiv.org/abs/2512.11143", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ziyu-li", "kind": "person", "label": "Ziyu Li", "url": "https://arxiv.org/abs/2512.11143", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yi-jiang", "kind": "person", "label": "Yi Jiang", "url": "https://arxiv.org/abs/2512.11143", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shiyu-tan", "kind": "person", "label": "Shiyu Tan", "url": "https://arxiv.org/abs/2512.11143", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuhao-jiang", "kind": "person", "label": "Yuhao Jiang", "url": "https://arxiv.org/abs/2512.11143", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:junjie-cheng", "kind": "person", "label": "Junjie Cheng", "url": "https://arxiv.org/abs/2512.11143", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2405.13050", "kind": "paper", "label": "Human-Centered LLM-Agent User Interface: A Position Paper", "url": "https://arxiv.org/abs/2405.13050", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daniel-chin", "kind": "person", "label": "Daniel Chin", "url": "https://arxiv.org/abs/2405.13050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuxuan-wang", "kind": "person", "label": "Yuxuan Wang", "url": "https://arxiv.org/abs/2405.13050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gus-xia", "kind": "person", "label": "Gus Xia", "url": "https://arxiv.org/abs/2405.13050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2408.04168", "kind": "paper", "label": "Perceive, Reflect, and Plan: Designing LLM Agent for Goal-Directed City Navigation without Instructions", "url": "https://arxiv.org/abs/2408.04168", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qingbin-zeng", "kind": "person", "label": "Qingbin Zeng", "url": "https://arxiv.org/abs/2408.04168", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qinglong-yang", "kind": "person", "label": "Qinglong Yang", "url": "https://arxiv.org/abs/2408.04168", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shunan-dong", "kind": "person", "label": "Shunan Dong", "url": "https://arxiv.org/abs/2408.04168", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:heming-du", "kind": "person", "label": "Heming Du", "url": "https://arxiv.org/abs/2408.04168", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:liang-zheng", "kind": "person", "label": "Liang Zheng", "url": "https://arxiv.org/abs/2408.04168", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2402.03610", "kind": "paper", "label": "RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents", "url": "https://arxiv.org/abs/2402.03610", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tomoyuki-kagaya", "kind": "person", "label": "Tomoyuki Kagaya", "url": "https://arxiv.org/abs/2402.03610", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:thong-jing-yuan", "kind": "person", "label": "Thong Jing Yuan", "url": "https://arxiv.org/abs/2402.03610", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuxuan-lou", "kind": "person", "label": "Yuxuan Lou", "url": "https://arxiv.org/abs/2402.03610", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jayashree-karlekar", "kind": "person", "label": "Jayashree Karlekar", "url": "https://arxiv.org/abs/2402.03610", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sugiri-pranata", "kind": "person", "label": "Sugiri Pranata", "url": "https://arxiv.org/abs/2402.03610", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:akira-kinose", "kind": "person", "label": "Akira Kinose", "url": "https://arxiv.org/abs/2402.03610", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:koki-oguri", "kind": "person", "label": "Koki Oguri", "url": "https://arxiv.org/abs/2402.03610", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:felix-wick", "kind": "person", "label": "Felix Wick", "url": "https://arxiv.org/abs/2402.03610", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2506.09171", "kind": "paper", "label": "Fact-Augmented Lookahead Planning for LLM Agents", "url": "https://arxiv.org/abs/2506.09171", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:samuel-holt", "kind": "person", "label": "Samuel Holt", "url": "https://arxiv.org/abs/2506.09171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:max-ruiz-luyten", "kind": "person", "label": "Max Ruiz Luyten", "url": "https://arxiv.org/abs/2506.09171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:thomas-pouplin", "kind": "person", "label": "Thomas Pouplin", "url": "https://arxiv.org/abs/2506.09171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mihaela-van-der-schaar", "kind": "person", "label": "Mihaela van der Schaar", "url": "https://arxiv.org/abs/2506.09171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2412.21033", "kind": "paper", "label": "Plancraft: an evaluation dataset for planning with LLM agents", "url": "https://arxiv.org/abs/2412.21033", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gautier-dagan", "kind": "person", "label": "Gautier Dagan", "url": "https://arxiv.org/abs/2412.21033", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:frank-keller", "kind": "person", "label": "Frank Keller", "url": "https://arxiv.org/abs/2412.21033", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alex-lascarides", "kind": "person", "label": "Alex Lascarides", "url": "https://arxiv.org/abs/2412.21033", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.03581", "kind": "paper", "label": "Learning When to Plan: Efficiently Allocating Test-Time Compute for LLM Agents", "url": "https://arxiv.org/abs/2509.03581", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:davide-paglieri", "kind": "person", "label": "Davide Paglieri", "url": "https://arxiv.org/abs/2509.03581", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bart-omiej-cupia", "kind": "person", "label": "Bart\u0142omiej Cupia\u0142", "url": "https://arxiv.org/abs/2509.03581", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jonathan-cook", "kind": "person", "label": "Jonathan Cook", "url": "https://arxiv.org/abs/2509.03581", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ulyana-piterbarg", "kind": "person", "label": "Ulyana Piterbarg", "url": "https://arxiv.org/abs/2509.03581", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jens-tuyls", "kind": "person", "label": "Jens Tuyls", "url": "https://arxiv.org/abs/2509.03581", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:edward-grefenstette", "kind": "person", "label": "Edward Grefenstette", "url": "https://arxiv.org/abs/2509.03581", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jakob-nicolaus-foerster", "kind": "person", "label": "Jakob Nicolaus Foerster", "url": "https://arxiv.org/abs/2509.03581", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jack-parker-holder", "kind": "person", "label": "Jack Parker-Holder", "url": "https://arxiv.org/abs/2509.03581", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2410.06153", "kind": "paper", "label": "AgentSquare: Automatic LLM Agent Search in Modular Design Space", "url": "https://arxiv.org/abs/2410.06153", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yu-shang", "kind": "person", "label": "Yu Shang", "url": "https://arxiv.org/abs/2410.06153", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yu-li", "kind": "person", "label": "Yu Li", "url": "https://arxiv.org/abs/2410.06153", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:keyu-zhao", "kind": "person", "label": "Keyu Zhao", "url": "https://arxiv.org/abs/2410.06153", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:likai-ma", "kind": "person", "label": "Likai Ma", "url": "https://arxiv.org/abs/2410.06153", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiahe-liu", "kind": "person", "label": "Jiahe Liu", "url": "https://arxiv.org/abs/2410.06153", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2411.05651", "kind": "paper", "label": "LightVA: Lightweight Visual Analytics with LLM Agent-Based Task Planning and Execution", "url": "https://arxiv.org/abs/2411.05651", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuheng-zhao", "kind": "person", "label": "Yuheng Zhao", "url": "https://arxiv.org/abs/2411.05651", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:junjie-wang", "kind": "person", "label": "Junjie Wang", "url": "https://arxiv.org/abs/2411.05651", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:linbin-xiang", "kind": "person", "label": "Linbin Xiang", "url": "https://arxiv.org/abs/2411.05651", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaowen-zhang", "kind": "person", "label": "Xiaowen Zhang", "url": "https://arxiv.org/abs/2411.05651", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zifei-guo", "kind": "person", "label": "Zifei Guo", "url": "https://arxiv.org/abs/2411.05651", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:cagatay-turkay", "kind": "person", "label": "Cagatay Turkay", "url": "https://arxiv.org/abs/2411.05651", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yu-zhang", "kind": "person", "label": "Yu Zhang", "url": "https://arxiv.org/abs/2411.05651", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:siming-chen", "kind": "person", "label": "Siming Chen", "url": "https://arxiv.org/abs/2411.05651", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.21868", "kind": "paper", "label": "What Makes LLM Agent Simulations Useful for Policy Practice? An Iterative Design Study in Emergency Preparedness", "url": "https://arxiv.org/abs/2509.21868", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuxuan-li", "kind": "person", "label": "Yuxuan Li", "url": "https://arxiv.org/abs/2509.21868", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sauvik-das", "kind": "person", "label": "Sauvik Das", "url": "https://arxiv.org/abs/2509.21868", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hirokazu-shirado", "kind": "person", "label": "Hirokazu Shirado", "url": "https://arxiv.org/abs/2509.21868", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.14635", "kind": "paper", "label": "Can LLM Agents Solve Collaborative Tasks? A Study on Urgency-Aware Planning and Coordination", "url": "https://arxiv.org/abs/2508.14635", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jo-o-vitor-de-carvalho-silva", "kind": "person", "label": "Jo\u00e3o Vitor de Carvalho Silva", "url": "https://arxiv.org/abs/2508.14635", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:douglas-g-macharet", "kind": "person", "label": "Douglas G. Macharet", "url": "https://arxiv.org/abs/2508.14635", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2408.06318", "kind": "paper", "label": "Can We Rely on LLM Agents to Draft Long-Horizon Plans? Let's Take TravelPlanner as an Example", "url": "https://arxiv.org/abs/2408.06318", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.06957", "kind": "paper", "label": "Learning and Reusing Policy Decompositions for Hierarchical Generalized Planning with LLM Agents", "url": "https://arxiv.org/abs/2605.06957", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shirin-sohrabi", "kind": "person", "label": "Shirin Sohrabi", "url": "https://arxiv.org/abs/2605.06957", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haritha-ananthakrishnan", "kind": "person", "label": "Haritha Ananthakrishnan", "url": "https://arxiv.org/abs/2605.06957", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:harsha-kokel", "kind": "person", "label": "Harsha Kokel", "url": "https://arxiv.org/abs/2605.06957", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kavitha-srinivas", "kind": "person", "label": "Kavitha Srinivas", "url": "https://arxiv.org/abs/2605.06957", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:michael-katz", "kind": "person", "label": "Michael Katz", "url": "https://arxiv.org/abs/2605.06957", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.17767", "kind": "paper", "label": "Position: The Real Barrier to LLM Agent Usability is Agentic ROI", "url": "https://arxiv.org/abs/2505.17767", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiarui-qin", "kind": "person", "label": "Jiarui Qin", "url": "https://arxiv.org/abs/2505.17767", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xingshan-zeng", "kind": "person", "label": "Xingshan Zeng", "url": "https://arxiv.org/abs/2505.17767", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yunjia-xi", "kind": "person", "label": "Yunjia Xi", "url": "https://arxiv.org/abs/2505.17767", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jianghao-lin", "kind": "person", "label": "Jianghao Lin", "url": "https://arxiv.org/abs/2505.17767", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chuhan-wu", "kind": "person", "label": "Chuhan Wu", "url": "https://arxiv.org/abs/2505.17767", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2504.03111", "kind": "paper", "label": "Les Dissonances: Cross-Tool Harvesting and Polluting in Pool-of-Tools Empowered LLM Agents", "url": "https://arxiv.org/abs/2504.03111", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zichuan-li", "kind": "person", "label": "Zichuan Li", "url": "https://arxiv.org/abs/2504.03111", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jian-cui", "kind": "person", "label": "Jian Cui", "url": "https://arxiv.org/abs/2504.03111", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaojing-liao", "kind": "person", "label": "Xiaojing Liao", "url": "https://arxiv.org/abs/2504.03111", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:luyi-xing", "kind": "person", "label": "Luyi Xing", "url": "https://arxiv.org/abs/2504.03111", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.09970", "kind": "paper", "label": "Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents", "url": "https://arxiv.org/abs/2505.09970", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mrinal-rawat", "kind": "person", "label": "Mrinal Rawat", "url": "https://arxiv.org/abs/2505.09970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ambuje-gupta", "kind": "person", "label": "Ambuje Gupta", "url": "https://arxiv.org/abs/2505.09970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rushil-goomer", "kind": "person", "label": "Rushil Goomer", "url": "https://arxiv.org/abs/2505.09970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alessandro-di-bari", "kind": "person", "label": "Alessandro Di Bari", "url": "https://arxiv.org/abs/2505.09970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:neha-gupta", "kind": "person", "label": "Neha Gupta", "url": "https://arxiv.org/abs/2505.09970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:roberto-pieraccini", "kind": "person", "label": "Roberto Pieraccini", "url": "https://arxiv.org/abs/2505.09970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.23590", "kind": "paper", "label": "Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents", "url": "https://arxiv.org/abs/2605.23590", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiazheng-kang", "kind": "person", "label": "Jiazheng Kang", "url": "https://arxiv.org/abs/2605.23590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bowen-zhang", "kind": "person", "label": "Bowen Zhang", "url": "https://arxiv.org/abs/2605.23590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zixin-song", "kind": "person", "label": "Zixin Song", "url": "https://arxiv.org/abs/2605.23590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiangwang-chen", "kind": "person", "label": "Jiangwang Chen", "url": "https://arxiv.org/abs/2605.23590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:da-zhu", "kind": "person", "label": "Da Zhu", "url": "https://arxiv.org/abs/2605.23590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guanjun-jiang", "kind": "person", "label": "Guanjun Jiang", "url": "https://arxiv.org/abs/2605.23590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2412.01262", "kind": "paper", "label": "Exploring ReAct Prompting for Task-Oriented Dialogue: Insights and Shortcomings", "url": "https://arxiv.org/abs/2412.01262", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:michelle-elizabeth", "kind": "person", "label": "Michelle Elizabeth", "url": "https://arxiv.org/abs/2412.01262", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:morgan-veyret", "kind": "person", "label": "Morgan Veyret", "url": "https://arxiv.org/abs/2412.01262", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:miguel-couceiro", "kind": "person", "label": "Miguel Couceiro", "url": "https://arxiv.org/abs/2412.01262", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ondrej-dusek", "kind": "person", "label": "Ondrej Dusek", "url": "https://arxiv.org/abs/2412.01262", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lina-m-rojas-barahona", "kind": "person", "label": "Lina M. Rojas-Barahona", "url": "https://arxiv.org/abs/2412.01262", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2312.10003", "kind": "paper", "label": "ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent", "url": "https://arxiv.org/abs/2312.10003", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:renat-aksitov", "kind": "person", "label": "Renat Aksitov", "url": "https://arxiv.org/abs/2312.10003", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sobhan-miryoosefi", "kind": "person", "label": "Sobhan Miryoosefi", "url": "https://arxiv.org/abs/2312.10003", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zonglin-li", "kind": "person", "label": "Zonglin Li", "url": "https://arxiv.org/abs/2312.10003", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daliang-li", "kind": "person", "label": "Daliang Li", "url": "https://arxiv.org/abs/2312.10003", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sheila-babayan", "kind": "person", "label": "Sheila Babayan", "url": "https://arxiv.org/abs/2312.10003", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kavya-kopparapu", "kind": "person", "label": "Kavya Kopparapu", "url": "https://arxiv.org/abs/2312.10003", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zachary-fisher", "kind": "person", "label": "Zachary Fisher", "url": "https://arxiv.org/abs/2312.10003", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ruiqi-guo", "kind": "person", "label": "Ruiqi Guo", "url": "https://arxiv.org/abs/2312.10003", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.07236", "kind": "paper", "label": "UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning", "url": "https://arxiv.org/abs/2505.07236", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:oleg-sautenkov", "kind": "person", "label": "Oleg Sautenkov", "url": "https://arxiv.org/abs/2505.07236", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yasheerah-yaqoot", "kind": "person", "label": "Yasheerah Yaqoot", "url": "https://arxiv.org/abs/2505.07236", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:muhammad-ahsan-mustafa", "kind": "person", "label": "Muhammad Ahsan Mustafa", "url": "https://arxiv.org/abs/2505.07236", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:faryal-batool", "kind": "person", "label": "Faryal Batool", "url": "https://arxiv.org/abs/2505.07236", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jeffrin-sam", "kind": "person", "label": "Jeffrin Sam", "url": "https://arxiv.org/abs/2505.07236", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:artem-lykov", "kind": "person", "label": "Artem Lykov", "url": "https://arxiv.org/abs/2505.07236", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chih-yung-wen", "kind": "person", "label": "Chih-Yung Wen", "url": "https://arxiv.org/abs/2505.07236", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dzmitry-tsetserukou", "kind": "person", "label": "Dzmitry Tsetserukou", "url": "https://arxiv.org/abs/2505.07236", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.18000", "kind": "paper", "label": "A T-API-Compliant ReAct Agentic Loop for Optical Networks: Generic vs. Domain-Specific Tool Abstractions", "url": "https://arxiv.org/abs/2606.18000", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:seyed-morteza-ahmadian", "kind": "person", "label": "Seyed Morteza Ahmadian", "url": "https://arxiv.org/abs/2606.18000", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:paolo-monti", "kind": "person", "label": "Paolo Monti", "url": "https://arxiv.org/abs/2606.18000", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:carlos-natalino", "kind": "person", "label": "Carlos Natalino", "url": "https://arxiv.org/abs/2606.18000", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.11068", "kind": "paper", "label": "From Phase Prediction to Phase Design: A ReAct Agent Framework for High-Entropy Alloy Discovery", "url": "https://arxiv.org/abs/2603.11068", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:iman-peivaste", "kind": "person", "label": "Iman Peivaste", "url": "https://arxiv.org/abs/2603.11068", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:salim-belouettar", "kind": "person", "label": "Salim Belouettar", "url": "https://arxiv.org/abs/2603.11068", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:1906.11932", "kind": "paper", "label": "To Act or React: Investigating Proactive Strategies For Online Community Moderation", "url": "https://arxiv.org/abs/1906.11932", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hussam-habib", "kind": "person", "label": "Hussam Habib", "url": "https://arxiv.org/abs/1906.11932", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:maaz-bin-musa", "kind": "person", "label": "Maaz Bin Musa", "url": "https://arxiv.org/abs/1906.11932", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fareed-zaffar", "kind": "person", "label": "Fareed Zaffar", "url": "https://arxiv.org/abs/1906.11932", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rishab-nithyanand", "kind": "person", "label": "Rishab Nithyanand", "url": "https://arxiv.org/abs/1906.11932", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.01413", "kind": "paper", "label": "Adaptive Stopping for Multi-Turn LLM Reasoning", "url": "https://arxiv.org/abs/2604.01413", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaofan-zhou", "kind": "person", "label": "Xiaofan Zhou", "url": "https://arxiv.org/abs/2604.01413", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:huy-nguyen", "kind": "person", "label": "Huy Nguyen", "url": "https://arxiv.org/abs/2604.01413", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bo-yu", "kind": "person", "label": "Bo Yu", "url": "https://arxiv.org/abs/2604.01413", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chenxi-liu", "kind": "person", "label": "Chenxi Liu", "url": "https://arxiv.org/abs/2604.01413", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lu-cheng", "kind": "person", "label": "Lu Cheng", "url": "https://arxiv.org/abs/2604.01413", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2411.00927", "kind": "paper", "label": "ReSpAct: Harmonizing Reasoning, Speaking, and Acting Towards Building Large Language Model-Based Conversational AI Agents", "url": "https://arxiv.org/abs/2411.00927", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:vardhan-dongre", "kind": "person", "label": "Vardhan Dongre", "url": "https://arxiv.org/abs/2411.00927", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaocheng-yang", "kind": "person", "label": "Xiaocheng Yang", "url": "https://arxiv.org/abs/2411.00927", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:emre-can-acikgoz", "kind": "person", "label": "Emre Can Acikgoz", "url": "https://arxiv.org/abs/2411.00927", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:suvodip-dey", "kind": "person", "label": "Suvodip Dey", "url": "https://arxiv.org/abs/2411.00927", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gokhan-tur", "kind": "person", "label": "Gokhan Tur", "url": "https://arxiv.org/abs/2411.00927", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dilek-hakkani-t-r", "kind": "person", "label": "Dilek Hakkani-T\u00fcr", "url": "https://arxiv.org/abs/2411.00927", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2408.12036", "kind": "paper", "label": "Reasoning and Tools for Human-Level Forecasting", "url": "https://arxiv.org/abs/2408.12036", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:elvis-hsieh", "kind": "person", "label": "Elvis Hsieh", "url": "https://arxiv.org/abs/2408.12036", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:preston-fu", "kind": "person", "label": "Preston Fu", "url": "https://arxiv.org/abs/2408.12036", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jonathan-chen", "kind": "person", "label": "Jonathan Chen", "url": "https://arxiv.org/abs/2408.12036", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.07773", "kind": "paper", "label": "SRR-Judge: Step-Level Rating and Refinement for Enhancing Search-Integrated Reasoning in Search Agents", "url": "https://arxiv.org/abs/2602.07773", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kuicai-dong", "kind": "person", "label": "Kuicai Dong", "url": "https://arxiv.org/abs/2602.07773", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dexun-li", "kind": "person", "label": "Dexun Li", "url": "https://arxiv.org/abs/2602.07773", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenjun-li", "kind": "person", "label": "Wenjun Li", "url": "https://arxiv.org/abs/2602.07773", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qu-yang", "kind": "person", "label": "Qu Yang", "url": "https://arxiv.org/abs/2602.07773", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wei-han", "kind": "person", "label": "Wei Han", "url": "https://arxiv.org/abs/2602.07773", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yong-liu", "kind": "person", "label": "Yong Liu", "url": "https://arxiv.org/abs/2602.07773", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.17794", "kind": "paper", "label": "Bridging the Reasoning Gap in Vietnamese with Small Language Models via Test-Time Scaling", "url": "https://arxiv.org/abs/2604.17794", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bui-the-trung", "kind": "person", "label": "Bui The Trung", "url": "https://arxiv.org/abs/2604.17794", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:do-minh-duc", "kind": "person", "label": "Do Minh Duc", "url": "https://arxiv.org/abs/2604.17794", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:nguyen-van-vinh", "kind": "person", "label": "Nguyen Van Vinh", "url": "https://arxiv.org/abs/2604.17794", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bui-nguyen-quoc-trinh", "kind": "person", "label": "Bui Nguyen Quoc Trinh", "url": "https://arxiv.org/abs/2604.17794", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.13382", "kind": "paper", "label": "Datarus-R1: An Adaptive Multi-Step Reasoning LLM for Automated Data Analysis", "url": "https://arxiv.org/abs/2508.13382", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ayoub-ben-chaliah", "kind": "person", "label": "Ayoub Ben Chaliah", "url": "https://arxiv.org/abs/2508.13382", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hela-dellagi", "kind": "person", "label": "Hela Dellagi", "url": "https://arxiv.org/abs/2508.13382", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2506.02025", "kind": "paper", "label": "Evaluating the Efficacy of LLM-Based Reasoning for Multiobjective HPC Job Scheduling", "url": "https://arxiv.org/abs/2506.02025", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:prachi-jadhav", "kind": "person", "label": "Prachi Jadhav", "url": "https://arxiv.org/abs/2506.02025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hongwei-jin", "kind": "person", "label": "Hongwei Jin", "url": "https://arxiv.org/abs/2506.02025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ewa-deelman", "kind": "person", "label": "Ewa Deelman", "url": "https://arxiv.org/abs/2506.02025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:prasanna-balaprakash", "kind": "person", "label": "Prasanna Balaprakash", "url": "https://arxiv.org/abs/2506.02025", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2312.07671", "kind": "paper", "label": "Reacting like Humans: Incorporating Intrinsic Human Behaviors into NAO through Sound-Based Reactions to Fearful and Shocking Events for Enhanced Sociability", "url": "https://arxiv.org/abs/2312.07671", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ali-ghadami", "kind": "person", "label": "Ali Ghadami", "url": "https://arxiv.org/abs/2312.07671", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mohammadreza-taghimohammadi", "kind": "person", "label": "Mohammadreza Taghimohammadi", "url": "https://arxiv.org/abs/2312.07671", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mohammad-mohammadzadeh", "kind": "person", "label": "Mohammad Mohammadzadeh", "url": "https://arxiv.org/abs/2312.07671", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mohammad-hosseinipour", "kind": "person", "label": "Mohammad Hosseinipour", "url": "https://arxiv.org/abs/2312.07671", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alireza-taheri", "kind": "person", "label": "Alireza Taheri", "url": "https://arxiv.org/abs/2312.07671", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.10658", "kind": "paper", "label": "Governed Reasoning for Institutional AI", "url": "https://arxiv.org/abs/2604.10658", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mamadou-seck", "kind": "person", "label": "Mamadou Seck", "url": "https://arxiv.org/abs/2604.10658", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.07035", "kind": "paper", "label": "DLLM-Searcher: Adapting Diffusion Large Language Model for Search Agents", "url": "https://arxiv.org/abs/2602.07035", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiahao-zhao", "kind": "person", "label": "Jiahao Zhao", "url": "https://arxiv.org/abs/2602.07035", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shaoxuan-xu", "kind": "person", "label": "Shaoxuan Xu", "url": "https://arxiv.org/abs/2602.07035", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhongxiang-sun", "kind": "person", "label": "Zhongxiang Sun", "url": "https://arxiv.org/abs/2602.07035", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fengqi-zhu", "kind": "person", "label": "Fengqi Zhu", "url": "https://arxiv.org/abs/2602.07035", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingyang-ou", "kind": "person", "label": "Jingyang Ou", "url": "https://arxiv.org/abs/2602.07035", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuling-shi", "kind": "person", "label": "Yuling Shi", "url": "https://arxiv.org/abs/2602.07035", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiao-zhang", "kind": "person", "label": "Xiao Zhang", "url": "https://arxiv.org/abs/2602.07035", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.23415", "kind": "paper", "label": "An Analysis of Decoding Methods for LLM-based Agents for Faithful Multi-Hop Question Answering", "url": "https://arxiv.org/abs/2503.23415", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alexander-murphy", "kind": "person", "label": "Alexander Murphy", "url": "https://arxiv.org/abs/2503.23415", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mohd-sanad-zaki-rizvi", "kind": "person", "label": "Mohd Sanad Zaki Rizvi", "url": "https://arxiv.org/abs/2503.23415", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:aden-haussmann", "kind": "person", "label": "Aden Haussmann", "url": "https://arxiv.org/abs/2503.23415", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ping-nie", "kind": "person", "label": "Ping Nie", "url": "https://arxiv.org/abs/2503.23415", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guifu-liu", "kind": "person", "label": "Guifu Liu", "url": "https://arxiv.org/abs/2503.23415", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:aryo-pradipta-gema", "kind": "person", "label": "Aryo Pradipta Gema", "url": "https://arxiv.org/abs/2503.23415", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2402.11534", "kind": "paper", "label": "PreAct: Prediction Enhances Agent's Planning Ability", "url": "https://arxiv.org/abs/2402.11534", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dayuan-fu", "kind": "person", "label": "Dayuan Fu", "url": "https://arxiv.org/abs/2402.11534", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jianzhao-huang", "kind": "person", "label": "Jianzhao Huang", "url": "https://arxiv.org/abs/2402.11534", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:siyuan-lu", "kind": "person", "label": "Siyuan Lu", "url": "https://arxiv.org/abs/2402.11534", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guanting-dong", "kind": "person", "label": "Guanting Dong", "url": "https://arxiv.org/abs/2402.11534", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yejie-wang", "kind": "person", "label": "Yejie Wang", "url": "https://arxiv.org/abs/2402.11534", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:keqing-he", "kind": "person", "label": "Keqing He", "url": "https://arxiv.org/abs/2402.11534", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:weiran-xu", "kind": "person", "label": "Weiran Xu", "url": "https://arxiv.org/abs/2402.11534", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2511.08098", "kind": "paper", "label": "PerspAct: Enhancing LLM Situated Collaboration Skills through Perspective Taking and Active Vision", "url": "https://arxiv.org/abs/2511.08098", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sabrina-patania", "kind": "person", "label": "Sabrina Patania", "url": "https://arxiv.org/abs/2511.08098", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:luca-annese", "kind": "person", "label": "Luca Annese", "url": "https://arxiv.org/abs/2511.08098", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:anita-pellegrini", "kind": "person", "label": "Anita Pellegrini", "url": "https://arxiv.org/abs/2511.08098", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:silvia-serino", "kind": "person", "label": "Silvia Serino", "url": "https://arxiv.org/abs/2511.08098", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:anna-lambiase", "kind": "person", "label": "Anna Lambiase", "url": "https://arxiv.org/abs/2511.08098", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:luca-pallonetto", "kind": "person", "label": "Luca Pallonetto", "url": "https://arxiv.org/abs/2511.08098", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:silvia-rossi", "kind": "person", "label": "Silvia Rossi", "url": "https://arxiv.org/abs/2511.08098", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:simone-colombani", "kind": "person", "label": "Simone Colombani", "url": "https://arxiv.org/abs/2511.08098", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.06825", "kind": "paper", "label": "Adaptive Tool Generation with Models as Tools and Reinforcement Learning", "url": "https://arxiv.org/abs/2510.06825", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chenpeng-wang", "kind": "person", "label": "Chenpeng Wang", "url": "https://arxiv.org/abs/2510.06825", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaojie-cheng", "kind": "person", "label": "Xiaojie Cheng", "url": "https://arxiv.org/abs/2510.06825", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chunye-wang", "kind": "person", "label": "Chunye Wang", "url": "https://arxiv.org/abs/2510.06825", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:linfeng-yang", "kind": "person", "label": "Linfeng Yang", "url": "https://arxiv.org/abs/2510.06825", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lei-zhang", "kind": "person", "label": "Lei Zhang", "url": "https://arxiv.org/abs/2510.06825", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.01171", "kind": "paper", "label": "ASP-Bench: From Natural Language to Logic Programs", "url": "https://arxiv.org/abs/2602.01171", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:stefan-szeider", "kind": "person", "label": "Stefan Szeider", "url": "https://arxiv.org/abs/2602.01171", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2312.04511", "kind": "paper", "label": "An LLM Compiler for Parallel Function Calling", "url": "https://arxiv.org/abs/2312.04511", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sehoon-kim", "kind": "person", "label": "Sehoon Kim", "url": "https://arxiv.org/abs/2312.04511", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:suhong-moon", "kind": "person", "label": "Suhong Moon", "url": "https://arxiv.org/abs/2312.04511", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ryan-tabrizi", "kind": "person", "label": "Ryan Tabrizi", "url": "https://arxiv.org/abs/2312.04511", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:nicholas-lee", "kind": "person", "label": "Nicholas Lee", "url": "https://arxiv.org/abs/2312.04511", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:michael-w-mahoney", "kind": "person", "label": "Michael W. Mahoney", "url": "https://arxiv.org/abs/2312.04511", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kurt-keutzer", "kind": "person", "label": "Kurt Keutzer", "url": "https://arxiv.org/abs/2312.04511", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:amir-gholami", "kind": "person", "label": "Amir Gholami", "url": "https://arxiv.org/abs/2312.04511", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2401.02777", "kind": "paper", "label": "From LLM to Conversational Agent: A Memory Enhanced Architecture with Fine-Tuning of Large Language Models", "url": "https://arxiv.org/abs/2401.02777", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:na-liu", "kind": "person", "label": "Na Liu", "url": "https://arxiv.org/abs/2401.02777", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:liangyu-chen", "kind": "person", "label": "Liangyu Chen", "url": "https://arxiv.org/abs/2401.02777", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaoyu-tian", "kind": "person", "label": "Xiaoyu Tian", "url": "https://arxiv.org/abs/2401.02777", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wei-zou", "kind": "person", "label": "Wei Zou", "url": "https://arxiv.org/abs/2401.02777", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kaijiang-chen", "kind": "person", "label": "Kaijiang Chen", "url": "https://arxiv.org/abs/2401.02777", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ming-cui", "kind": "person", "label": "Ming Cui", "url": "https://arxiv.org/abs/2401.02777", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.23422", "kind": "paper", "label": "From Knowledge to Noise: CTIM-Rover and the Pitfalls of Episodic Memory in Software Engineering Agents", "url": "https://arxiv.org/abs/2505.23422", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tobias-lindenbauer", "kind": "person", "label": "Tobias Lindenbauer", "url": "https://arxiv.org/abs/2505.23422", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:georg-groh", "kind": "person", "label": "Georg Groh", "url": "https://arxiv.org/abs/2505.23422", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hinrich-sch-tze", "kind": "person", "label": "Hinrich Sch\u00fctze", "url": "https://arxiv.org/abs/2505.23422", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.17734", "kind": "paper", "label": "Harnessing LLM Agents with Skill Programs", "url": "https://arxiv.org/abs/2605.17734", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hongjun-liu", "kind": "person", "label": "Hongjun Liu", "url": "https://arxiv.org/abs/2605.17734", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yifei-ming", "kind": "person", "label": "Yifei Ming", "url": "https://arxiv.org/abs/2605.17734", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chen-zhao", "kind": "person", "label": "Chen Zhao", "url": "https://arxiv.org/abs/2605.17734", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2502.11211", "kind": "paper", "label": "A Survey of LLM-based Agents in Medicine: How far are we from Baymax?", "url": "https://arxiv.org/abs/2502.11211", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zizhan-ma", "kind": "person", "label": "Zizhan Ma", "url": "https://arxiv.org/abs/2502.11211", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zheng-wang", "kind": "person", "label": "Zheng Wang", "url": "https://arxiv.org/abs/2502.11211", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chenghan-wu", "kind": "person", "label": "Chenghan Wu", "url": "https://arxiv.org/abs/2502.11211", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiaming-ji", "kind": "person", "label": "Jiaming Ji", "url": "https://arxiv.org/abs/2502.11211", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenting-chen", "kind": "person", "label": "Wenting Chen", "url": "https://arxiv.org/abs/2502.11211", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiang-li", "kind": "person", "label": "Xiang Li", "url": "https://arxiv.org/abs/2502.11211", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yixuan-yuan", "kind": "person", "label": "Yixuan Yuan", "url": "https://arxiv.org/abs/2502.11211", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.18970", "kind": "paper", "label": "LLM-based Agents Suffer from Hallucinations: A Survey of Taxonomy, Methods, and Directions", "url": "https://arxiv.org/abs/2509.18970", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xixun-lin", "kind": "person", "label": "Xixun Lin", "url": "https://arxiv.org/abs/2509.18970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yucheng-ning", "kind": "person", "label": "Yucheng Ning", "url": "https://arxiv.org/abs/2509.18970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingwen-zhang", "kind": "person", "label": "Jingwen Zhang", "url": "https://arxiv.org/abs/2509.18970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yan-dong", "kind": "person", "label": "Yan Dong", "url": "https://arxiv.org/abs/2509.18970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yilong-liu", "kind": "person", "label": "Yilong Liu", "url": "https://arxiv.org/abs/2509.18970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yongxuan-wu", "kind": "person", "label": "Yongxuan Wu", "url": "https://arxiv.org/abs/2509.18970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaohua-qi", "kind": "person", "label": "Xiaohua Qi", "url": "https://arxiv.org/abs/2509.18970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:nan-sun", "kind": "person", "label": "Nan Sun", "url": "https://arxiv.org/abs/2509.18970", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2408.02479", "kind": "paper", "label": "From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future", "url": "https://arxiv.org/abs/2408.02479", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haolin-jin", "kind": "person", "label": "Haolin Jin", "url": "https://arxiv.org/abs/2408.02479", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:linghan-huang", "kind": "person", "label": "Linghan Huang", "url": "https://arxiv.org/abs/2408.02479", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haipeng-cai", "kind": "person", "label": "Haipeng Cai", "url": "https://arxiv.org/abs/2408.02479", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jun-yan", "kind": "person", "label": "Jun Yan", "url": "https://arxiv.org/abs/2408.02479", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bo-li", "kind": "person", "label": "Bo Li", "url": "https://arxiv.org/abs/2408.02479", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:huaming-chen", "kind": "person", "label": "Huaming Chen", "url": "https://arxiv.org/abs/2408.02479", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.16416", "kind": "paper", "label": "Survey on Evaluation of LLM-based Agents", "url": "https://arxiv.org/abs/2503.16416", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:asaf-yehudai", "kind": "person", "label": "Asaf Yehudai", "url": "https://arxiv.org/abs/2503.16416", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lilach-eden", "kind": "person", "label": "Lilach Eden", "url": "https://arxiv.org/abs/2503.16416", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alan-li", "kind": "person", "label": "Alan Li", "url": "https://arxiv.org/abs/2503.16416", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guy-uziel", "kind": "person", "label": "Guy Uziel", "url": "https://arxiv.org/abs/2503.16416", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yilun-zhao", "kind": "person", "label": "Yilun Zhao", "url": "https://arxiv.org/abs/2503.16416", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:roy-bar-haim", "kind": "person", "label": "Roy Bar-Haim", "url": "https://arxiv.org/abs/2503.16416", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:arman-cohan", "kind": "person", "label": "Arman Cohan", "url": "https://arxiv.org/abs/2503.16416", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:michal-shmueli-scheuer", "kind": "person", "label": "Michal Shmueli-Scheuer", "url": "https://arxiv.org/abs/2503.16416", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.22458", "kind": "paper", "label": "Evaluating LLM-based Agents for Multi-Turn Conversations: A Survey", "url": "https://arxiv.org/abs/2503.22458", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shengyue-guan", "kind": "person", "label": "Shengyue Guan", "url": "https://arxiv.org/abs/2503.22458", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jindong-wang", "kind": "person", "label": "Jindong Wang", "url": "https://arxiv.org/abs/2503.22458", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiang-bian", "kind": "person", "label": "Jiang Bian", "url": "https://arxiv.org/abs/2503.22458", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bin-zhu", "kind": "person", "label": "Bin Zhu", "url": "https://arxiv.org/abs/2503.22458", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jian-guang-lou", "kind": "person", "label": "Jian-guang Lou", "url": "https://arxiv.org/abs/2503.22458", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haoyi-xiong", "kind": "person", "label": "Haoyi Xiong", "url": "https://arxiv.org/abs/2503.22458", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.00083", "kind": "paper", "label": "A Survey on Code Generation with LLM-based Agents", "url": "https://arxiv.org/abs/2508.00083", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yihong-dong", "kind": "person", "label": "Yihong Dong", "url": "https://arxiv.org/abs/2508.00083", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xue-jiang", "kind": "person", "label": "Xue Jiang", "url": "https://arxiv.org/abs/2508.00083", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiaru-qian", "kind": "person", "label": "Jiaru Qian", "url": "https://arxiv.org/abs/2508.00083", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tian-wang", "kind": "person", "label": "Tian Wang", "url": "https://arxiv.org/abs/2508.00083", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kechi-zhang", "kind": "person", "label": "Kechi Zhang", "url": "https://arxiv.org/abs/2508.00083", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhi-jin", "kind": "person", "label": "Zhi Jin", "url": "https://arxiv.org/abs/2508.00083", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ge-li", "kind": "person", "label": "Ge Li", "url": "https://arxiv.org/abs/2508.00083", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2411.09523", "kind": "paper", "label": "Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents", "url": "https://arxiv.org/abs/2411.09523", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuyou-gan", "kind": "person", "label": "Yuyou Gan", "url": "https://arxiv.org/abs/2411.09523", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yong-yang", "kind": "person", "label": "Yong Yang", "url": "https://arxiv.org/abs/2411.09523", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhe-ma", "kind": "person", "label": "Zhe Ma", "url": "https://arxiv.org/abs/2411.09523", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ping-he", "kind": "person", "label": "Ping He", "url": "https://arxiv.org/abs/2411.09523", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rui-zeng", "kind": "person", "label": "Rui Zeng", "url": "https://arxiv.org/abs/2411.09523", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yiming-wang", "kind": "person", "label": "Yiming Wang", "url": "https://arxiv.org/abs/2411.09523", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qingming-li", "kind": "person", "label": "Qingming Li", "url": "https://arxiv.org/abs/2411.09523", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chunyi-zhou", "kind": "person", "label": "Chunyi Zhou", "url": "https://arxiv.org/abs/2411.09523", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.00675", "kind": "paper", "label": "Rethinking Memory in LLM based Agents: Representations, Operations, and Emerging Topics", "url": "https://arxiv.org/abs/2505.00675", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yiming-du", "kind": "person", "label": "Yiming Du", "url": "https://arxiv.org/abs/2505.00675", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenyu-huang", "kind": "person", "label": "Wenyu Huang", "url": "https://arxiv.org/abs/2505.00675", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:danna-zheng", "kind": "person", "label": "Danna Zheng", "url": "https://arxiv.org/abs/2505.00675", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhaowei-wang", "kind": "person", "label": "Zhaowei Wang", "url": "https://arxiv.org/abs/2505.00675", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sebastien-montella", "kind": "person", "label": "Sebastien Montella", "url": "https://arxiv.org/abs/2505.00675", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mirella-lapata", "kind": "person", "label": "Mirella Lapata", "url": "https://arxiv.org/abs/2505.00675", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kam-fai-wong", "kind": "person", "label": "Kam-Fai Wong", "url": "https://arxiv.org/abs/2505.00675", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jeff-z-pan", "kind": "person", "label": "Jeff Z. Pan", "url": "https://arxiv.org/abs/2505.00675", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2511.13305", "kind": "paper", "label": "SAINT: Service-level Integration Test Generation with Program Analysis and LLM-based Agents", "url": "https://arxiv.org/abs/2511.13305", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rangeet-pan", "kind": "person", "label": "Rangeet Pan", "url": "https://arxiv.org/abs/2511.13305", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:raju-pavuluri", "kind": "person", "label": "Raju Pavuluri", "url": "https://arxiv.org/abs/2511.13305", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ruikai-huang", "kind": "person", "label": "Ruikai Huang", "url": "https://arxiv.org/abs/2511.13305", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rahul-krishna", "kind": "person", "label": "Rahul Krishna", "url": "https://arxiv.org/abs/2511.13305", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tyler-stennett", "kind": "person", "label": "Tyler Stennett", "url": "https://arxiv.org/abs/2511.13305", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alessandro-orso", "kind": "person", "label": "Alessandro Orso", "url": "https://arxiv.org/abs/2511.13305", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:saurabh-sinha", "kind": "person", "label": "Saurabh SInha", "url": "https://arxiv.org/abs/2511.13305", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.17692", "kind": "paper", "label": "LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios", "url": "https://arxiv.org/abs/2508.17692", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bingxi-zhao", "kind": "person", "label": "Bingxi Zhao", "url": "https://arxiv.org/abs/2508.17692", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lin-geng-foo", "kind": "person", "label": "Lin Geng Foo", "url": "https://arxiv.org/abs/2508.17692", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ping-hu", "kind": "person", "label": "Ping Hu", "url": "https://arxiv.org/abs/2508.17692", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:christian-theobalt", "kind": "person", "label": "Christian Theobalt", "url": "https://arxiv.org/abs/2508.17692", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hossein-rahmani", "kind": "person", "label": "Hossein Rahmani", "url": "https://arxiv.org/abs/2508.17692", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2406.17232", "kind": "paper", "label": "Beyond Demographics: Aligning Role-playing LLM-based Agents Using Human Belief Networks", "url": "https://arxiv.org/abs/2406.17232", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yun-shiuan-chuang", "kind": "person", "label": "Yun-Shiuan Chuang", "url": "https://arxiv.org/abs/2406.17232", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:krirk-nirunwiroj", "kind": "person", "label": "Krirk Nirunwiroj", "url": "https://arxiv.org/abs/2406.17232", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zach-studdiford", "kind": "person", "label": "Zach Studdiford", "url": "https://arxiv.org/abs/2406.17232", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:agam-goyal", "kind": "person", "label": "Agam Goyal", "url": "https://arxiv.org/abs/2406.17232", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:vincent-v-frigo", "kind": "person", "label": "Vincent V. Frigo", "url": "https://arxiv.org/abs/2406.17232", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sijia-yang", "kind": "person", "label": "Sijia Yang", "url": "https://arxiv.org/abs/2406.17232", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dhavan-shah", "kind": "person", "label": "Dhavan Shah", "url": "https://arxiv.org/abs/2406.17232", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:junjie-hu", "kind": "person", "label": "Junjie Hu", "url": "https://arxiv.org/abs/2406.17232", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2511.03758", "kind": "paper", "label": "Leveraging LLM-based agents for social science research: insights from citation network simulations", "url": "https://arxiv.org/abs/2511.03758", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiarui-ji", "kind": "person", "label": "Jiarui Ji", "url": "https://arxiv.org/abs/2511.03758", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:runlin-lei", "kind": "person", "label": "Runlin Lei", "url": "https://arxiv.org/abs/2511.03758", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xuchen-pan", "kind": "person", "label": "Xuchen Pan", "url": "https://arxiv.org/abs/2511.03758", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhewei-wei", "kind": "person", "label": "Zhewei Wei", "url": "https://arxiv.org/abs/2511.03758", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hao-sun", "kind": "person", "label": "Hao Sun", "url": "https://arxiv.org/abs/2511.03758", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yankai-lin", "kind": "person", "label": "Yankai Lin", "url": "https://arxiv.org/abs/2511.03758", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yongzheng-yang", "kind": "person", "label": "Yongzheng Yang", "url": "https://arxiv.org/abs/2511.03758", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2409.02977", "kind": "paper", "label": "Large Language Model-Based Agents for Software Engineering: A Survey", "url": "https://arxiv.org/abs/2409.02977", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:junwei-liu", "kind": "person", "label": "Junwei Liu", "url": "https://arxiv.org/abs/2409.02977", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kaixin-wang", "kind": "person", "label": "Kaixin Wang", "url": "https://arxiv.org/abs/2409.02977", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yixuan-chen", "kind": "person", "label": "Yixuan Chen", "url": "https://arxiv.org/abs/2409.02977", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xin-peng", "kind": "person", "label": "Xin Peng", "url": "https://arxiv.org/abs/2409.02977", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhenpeng-chen", "kind": "person", "label": "Zhenpeng Chen", "url": "https://arxiv.org/abs/2409.02977", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lingming-zhang", "kind": "person", "label": "Lingming Zhang", "url": "https://arxiv.org/abs/2409.02977", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yiling-lou", "kind": "person", "label": "Yiling Lou", "url": "https://arxiv.org/abs/2409.02977", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.04813", "kind": "paper", "label": "Agentic AI in Healthcare & Medicine: A Seven-Dimensional Taxonomy for Empirical Evaluation of LLM-based Agents", "url": "https://arxiv.org/abs/2602.04813", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shubham-vatsal", "kind": "person", "label": "Shubham Vatsal", "url": "https://arxiv.org/abs/2602.04813", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:harsh-dubey", "kind": "person", "label": "Harsh Dubey", "url": "https://arxiv.org/abs/2602.04813", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:aditi-singh", "kind": "person", "label": "Aditi Singh", "url": "https://arxiv.org/abs/2602.04813", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2406.05804", "kind": "paper", "label": "A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning", "url": "https://arxiv.org/abs/2406.05804", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinzhe-li", "kind": "person", "label": "Xinzhe Li", "url": "https://arxiv.org/abs/2406.05804", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2409.09030", "kind": "paper", "label": "Agents in Software Engineering: Survey, Landscape, and Vision", "url": "https://arxiv.org/abs/2409.09030", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yanlin-wang", "kind": "person", "label": "Yanlin Wang", "url": "https://arxiv.org/abs/2409.09030", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wanjun-zhong", "kind": "person", "label": "Wanjun Zhong", "url": "https://arxiv.org/abs/2409.09030", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yanxian-huang", "kind": "person", "label": "Yanxian Huang", "url": "https://arxiv.org/abs/2409.09030", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ensheng-shi", "kind": "person", "label": "Ensheng Shi", "url": "https://arxiv.org/abs/2409.09030", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:min-yang", "kind": "person", "label": "Min Yang", "url": "https://arxiv.org/abs/2409.09030", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiachi-chen", "kind": "person", "label": "Jiachi Chen", "url": "https://arxiv.org/abs/2409.09030", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hui-li", "kind": "person", "label": "Hui Li", "url": "https://arxiv.org/abs/2409.09030", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.02744", "kind": "paper", "label": "Large Language Model-based Data Science Agent: A Survey", "url": "https://arxiv.org/abs/2508.02744", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ke-chen", "kind": "person", "label": "Ke Chen", "url": "https://arxiv.org/abs/2508.02744", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:peiran-wang", "kind": "person", "label": "Peiran Wang", "url": "https://arxiv.org/abs/2508.02744", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yaoning-yu", "kind": "person", "label": "Yaoning Yu", "url": "https://arxiv.org/abs/2508.02744", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xianyang-zhan", "kind": "person", "label": "Xianyang Zhan", "url": "https://arxiv.org/abs/2508.02744", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haohan-wang", "kind": "person", "label": "Haohan Wang", "url": "https://arxiv.org/abs/2508.02744", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.16330", "kind": "paper", "label": "Generalizability of Large Language Model-Based Agents: A Comprehensive Survey", "url": "https://arxiv.org/abs/2509.16330", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:minxing-zhang", "kind": "person", "label": "Minxing Zhang", "url": "https://arxiv.org/abs/2509.16330", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yi-yang", "kind": "person", "label": "Yi Yang", "url": "https://arxiv.org/abs/2509.16330", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:roy-xie", "kind": "person", "label": "Roy Xie", "url": "https://arxiv.org/abs/2509.16330", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bhuwan-dhingra", "kind": "person", "label": "Bhuwan Dhingra", "url": "https://arxiv.org/abs/2509.16330", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shuyan-zhou", "kind": "person", "label": "Shuyan Zhou", "url": "https://arxiv.org/abs/2509.16330", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jian-pei", "kind": "person", "label": "Jian Pei", "url": "https://arxiv.org/abs/2509.16330", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.12786", "kind": "paper", "label": "Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks", "url": "https://arxiv.org/abs/2505.12786", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:minrui-xu", "kind": "person", "label": "Minrui Xu", "url": "https://arxiv.org/abs/2505.12786", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiani-fan", "kind": "person", "label": "Jiani Fan", "url": "https://arxiv.org/abs/2505.12786", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinyu-huang", "kind": "person", "label": "Xinyu Huang", "url": "https://arxiv.org/abs/2505.12786", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:conghao-zhou", "kind": "person", "label": "Conghao Zhou", "url": "https://arxiv.org/abs/2505.12786", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiawen-kang", "kind": "person", "label": "Jiawen Kang", "url": "https://arxiv.org/abs/2505.12786", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dusit-niyato", "kind": "person", "label": "Dusit Niyato", "url": "https://arxiv.org/abs/2505.12786", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shiwen-mao", "kind": "person", "label": "Shiwen Mao", "url": "https://arxiv.org/abs/2505.12786", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhu-han", "kind": "person", "label": "Zhu Han", "url": "https://arxiv.org/abs/2505.12786", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2404.00629", "kind": "paper", "label": "Against The Achilles' Heel: A Survey on Red Teaming for Generative Models", "url": "https://arxiv.org/abs/2404.00629", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lizhi-lin", "kind": "person", "label": "Lizhi Lin", "url": "https://arxiv.org/abs/2404.00629", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:honglin-mu", "kind": "person", "label": "Honglin Mu", "url": "https://arxiv.org/abs/2404.00629", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zenan-zhai", "kind": "person", "label": "Zenan Zhai", "url": "https://arxiv.org/abs/2404.00629", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:minghan-wang", "kind": "person", "label": "Minghan Wang", "url": "https://arxiv.org/abs/2404.00629", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuxia-wang", "kind": "person", "label": "Yuxia Wang", "url": "https://arxiv.org/abs/2404.00629", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:renxi-wang", "kind": "person", "label": "Renxi Wang", "url": "https://arxiv.org/abs/2404.00629", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:junjie-gao", "kind": "person", "label": "Junjie Gao", "url": "https://arxiv.org/abs/2404.00629", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yixuan-zhang", "kind": "person", "label": "Yixuan Zhang", "url": "https://arxiv.org/abs/2404.00629", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.12567", "kind": "paper", "label": "A Survey of Attacks on Large Language Models", "url": "https://arxiv.org/abs/2505.12567", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenrui-xu", "kind": "person", "label": "Wenrui Xu", "url": "https://arxiv.org/abs/2505.12567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:keshab-k-parhi", "kind": "person", "label": "Keshab K. Parhi", "url": "https://arxiv.org/abs/2505.12567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2404.13501", "kind": "paper", "label": "A Survey on the Memory Mechanism of Large Language Model based Agents", "url": "https://arxiv.org/abs/2404.13501", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jieming-zhu", "kind": "person", "label": "Jieming Zhu", "url": "https://arxiv.org/abs/2404.13501", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.20683", "kind": "paper", "label": "From Question Answering to Task Completion: A Survey on Agent System and Harness Design", "url": "https://arxiv.org/abs/2606.20683", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jianyuan-guo", "kind": "person", "label": "Jianyuan Guo", "url": "https://arxiv.org/abs/2606.20683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhiwei-hao", "kind": "person", "label": "Zhiwei Hao", "url": "https://arxiv.org/abs/2606.20683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chengcheng-wang", "kind": "person", "label": "Chengcheng Wang", "url": "https://arxiv.org/abs/2606.20683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:cheng-fan", "kind": "person", "label": "Cheng Fan", "url": "https://arxiv.org/abs/2606.20683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tingzhang-luo", "kind": "person", "label": "Tingzhang Luo", "url": "https://arxiv.org/abs/2606.20683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hongguang-li", "kind": "person", "label": "Hongguang Li", "url": "https://arxiv.org/abs/2606.20683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ying-gao", "kind": "person", "label": "Ying Gao", "url": "https://arxiv.org/abs/2606.20683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hefei-mei", "kind": "person", "label": "Hefei Mei", "url": "https://arxiv.org/abs/2606.20683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.12434", "kind": "paper", "label": "A Survey on the Optimization of Large Language Model-based Agents", "url": "https://arxiv.org/abs/2503.12434", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shangheng-du", "kind": "person", "label": "Shangheng Du", "url": "https://arxiv.org/abs/2503.12434", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiabao-zhao", "kind": "person", "label": "Jiabao Zhao", "url": "https://arxiv.org/abs/2503.12434", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jinxin-shi", "kind": "person", "label": "Jinxin Shi", "url": "https://arxiv.org/abs/2503.12434", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhentao-xie", "kind": "person", "label": "Zhentao Xie", "url": "https://arxiv.org/abs/2503.12434", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xin-jiang", "kind": "person", "label": "Xin Jiang", "url": "https://arxiv.org/abs/2503.12434", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yanhong-bai", "kind": "person", "label": "Yanhong Bai", "url": "https://arxiv.org/abs/2503.12434", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:liang-he", "kind": "person", "label": "Liang He", "url": "https://arxiv.org/abs/2503.12434", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.19213", "kind": "paper", "label": "A Survey of Large Language Model Agents for Question Answering", "url": "https://arxiv.org/abs/2503.19213", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:murong-yue", "kind": "person", "label": "Murong Yue", "url": "https://arxiv.org/abs/2503.19213", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2312.17601", "kind": "paper", "label": "The Tyranny of Possibilities in the Design of Task-Oriented LLM Systems: A Scoping Survey", "url": "https://arxiv.org/abs/2312.17601", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dhruv-dhamani", "kind": "person", "label": "Dhruv Dhamani", "url": "https://arxiv.org/abs/2312.17601", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mary-lou-maher", "kind": "person", "label": "Mary Lou Maher", "url": "https://arxiv.org/abs/2312.17601", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2309.07864", "kind": "paper", "label": "The Rise and Potential of Large Language Model Based Agents: A Survey", "url": "https://arxiv.org/abs/2309.07864", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhiheng-xi", "kind": "person", "label": "Zhiheng Xi", "url": "https://arxiv.org/abs/2309.07864", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenxiang-chen", "kind": "person", "label": "Wenxiang Chen", "url": "https://arxiv.org/abs/2309.07864", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xin-guo", "kind": "person", "label": "Xin Guo", "url": "https://arxiv.org/abs/2309.07864", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wei-he", "kind": "person", "label": "Wei He", "url": "https://arxiv.org/abs/2309.07864", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yiwen-ding", "kind": "person", "label": "Yiwen Ding", "url": "https://arxiv.org/abs/2309.07864", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:boyang-hong", "kind": "person", "label": "Boyang Hong", "url": "https://arxiv.org/abs/2309.07864", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ming-zhang", "kind": "person", "label": "Ming Zhang", "url": "https://arxiv.org/abs/2309.07864", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:junzhe-wang", "kind": "person", "label": "Junzhe Wang", "url": "https://arxiv.org/abs/2309.07864", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.00753", "kind": "paper", "label": "LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey", "url": "https://arxiv.org/abs/2505.00753", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wei-chieh-huang", "kind": "person", "label": "Wei-Chieh Huang", "url": "https://arxiv.org/abs/2505.00753", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yaozu-wu", "kind": "person", "label": "Yaozu Wu", "url": "https://arxiv.org/abs/2505.00753", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jizhou-guo", "kind": "person", "label": "Jizhou Guo", "url": "https://arxiv.org/abs/2505.00753", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chunyu-miao", "kind": "person", "label": "Chunyu Miao", "url": "https://arxiv.org/abs/2505.00753", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hoang-nguyen", "kind": "person", "label": "Hoang Nguyen", "url": "https://arxiv.org/abs/2505.00753", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yue-zhou", "kind": "person", "label": "Yue Zhou", "url": "https://arxiv.org/abs/2505.00753", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2507.21504", "kind": "paper", "label": "Evaluation and Benchmarking of LLM Agents: A Survey", "url": "https://arxiv.org/abs/2507.21504", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mahmoud-mohammadi", "kind": "person", "label": "Mahmoud Mohammadi", "url": "https://arxiv.org/abs/2507.21504", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yipeng-li", "kind": "person", "label": "Yipeng Li", "url": "https://arxiv.org/abs/2507.21504", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jane-lo", "kind": "person", "label": "Jane Lo", "url": "https://arxiv.org/abs/2507.21504", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wendy-yip", "kind": "person", "label": "Wendy Yip", "url": "https://arxiv.org/abs/2507.21504", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2505.23419", "kind": "paper", "label": "SWE-bench Goes Live!", "url": "https://arxiv.org/abs/2505.23419", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:linghao-zhang", "kind": "person", "label": "Linghao Zhang", "url": "https://arxiv.org/abs/2505.23419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shilin-he", "kind": "person", "label": "Shilin He", "url": "https://arxiv.org/abs/2505.23419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chaoyun-zhang", "kind": "person", "label": "Chaoyun Zhang", "url": "https://arxiv.org/abs/2505.23419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yu-kang", "kind": "person", "label": "Yu Kang", "url": "https://arxiv.org/abs/2505.23419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bowen-li", "kind": "person", "label": "Bowen Li", "url": "https://arxiv.org/abs/2505.23419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chengxing-xie", "kind": "person", "label": "Chengxing Xie", "url": "https://arxiv.org/abs/2505.23419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:junhao-wang", "kind": "person", "label": "Junhao Wang", "url": "https://arxiv.org/abs/2505.23419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:maoquan-wang", "kind": "person", "label": "Maoquan Wang", "url": "https://arxiv.org/abs/2505.23419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.08996", "kind": "paper", "label": "Saving SWE-Bench: A Benchmark Mutation Approach for Realistic Agent Evaluation", "url": "https://arxiv.org/abs/2510.08996", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:spandan-garg", "kind": "person", "label": "Spandan Garg", "url": "https://arxiv.org/abs/2510.08996", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:benjamin-steenhoek", "kind": "person", "label": "Benjamin Steenhoek", "url": "https://arxiv.org/abs/2510.08996", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yufan-huang", "kind": "person", "label": "Yufan Huang", "url": "https://arxiv.org/abs/2510.08996", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2410.06992", "kind": "paper", "label": "SWE-Bench+: Enhanced Coding Benchmark for LLMs", "url": "https://arxiv.org/abs/2410.06992", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:reem-aleithan", "kind": "person", "label": "Reem Aleithan", "url": "https://arxiv.org/abs/2410.06992", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haoran-xue", "kind": "person", "label": "Haoran Xue", "url": "https://arxiv.org/abs/2410.06992", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mohammad-mahdi-mohajer", "kind": "person", "label": "Mohammad Mahdi Mohajer", "url": "https://arxiv.org/abs/2410.06992", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:elijah-nnorom", "kind": "person", "label": "Elijah Nnorom", "url": "https://arxiv.org/abs/2410.06992", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gias-uddin", "kind": "person", "label": "Gias Uddin", "url": "https://arxiv.org/abs/2410.06992", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:song-wang", "kind": "person", "label": "Song Wang", "url": "https://arxiv.org/abs/2410.06992", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.16941", "kind": "paper", "label": "SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?", "url": "https://arxiv.org/abs/2509.16941", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiang-deng", "kind": "person", "label": "Xiang Deng", "url": "https://arxiv.org/abs/2509.16941", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jeff-da", "kind": "person", "label": "Jeff Da", "url": "https://arxiv.org/abs/2509.16941", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:edwin-pan", "kind": "person", "label": "Edwin Pan", "url": "https://arxiv.org/abs/2509.16941", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yannis-yiming-he", "kind": "person", "label": "Yannis Yiming He", "url": "https://arxiv.org/abs/2509.16941", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:charles-ide", "kind": "person", "label": "Charles Ide", "url": "https://arxiv.org/abs/2509.16941", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kanak-garg", "kind": "person", "label": "Kanak Garg", "url": "https://arxiv.org/abs/2509.16941", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:niklas-lauffer", "kind": "person", "label": "Niklas Lauffer", "url": "https://arxiv.org/abs/2509.16941", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:andrew-park", "kind": "person", "label": "Andrew Park", "url": "https://arxiv.org/abs/2509.16941", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2410.03859", "kind": "paper", "label": "SWE-bench Multimodal: Do AI Systems Generalize to Visual Software Domains?", "url": "https://arxiv.org/abs/2410.03859", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:john-yang", "kind": "person", "label": "John Yang", "url": "https://arxiv.org/abs/2410.03859", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:carlos-e-jimenez", "kind": "person", "label": "Carlos E. Jimenez", "url": "https://arxiv.org/abs/2410.03859", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alex-l-zhang", "kind": "person", "label": "Alex L. Zhang", "url": "https://arxiv.org/abs/2410.03859", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kilian-lieret", "kind": "person", "label": "Kilian Lieret", "url": "https://arxiv.org/abs/2410.03859", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:joyce-yang", "kind": "person", "label": "Joyce Yang", "url": "https://arxiv.org/abs/2410.03859", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xindi-wu", "kind": "person", "label": "Xindi Wu", "url": "https://arxiv.org/abs/2410.03859", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ori-press", "kind": "person", "label": "Ori Press", "url": "https://arxiv.org/abs/2410.03859", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:niklas-muennighoff", "kind": "person", "label": "Niklas Muennighoff", "url": "https://arxiv.org/abs/2410.03859", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2506.14683", "kind": "paper", "label": "Unified Software Engineering Agent as AI Software Engineer", "url": "https://arxiv.org/abs/2506.14683", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:leonhard-applis", "kind": "person", "label": "Leonhard Applis", "url": "https://arxiv.org/abs/2506.14683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuntong-zhang", "kind": "person", "label": "Yuntong Zhang", "url": "https://arxiv.org/abs/2506.14683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shanchao-liang", "kind": "person", "label": "Shanchao Liang", "url": "https://arxiv.org/abs/2506.14683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:nan-jiang", "kind": "person", "label": "Nan Jiang", "url": "https://arxiv.org/abs/2506.14683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lin-tan", "kind": "person", "label": "Lin Tan", "url": "https://arxiv.org/abs/2506.14683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:abhik-roychoudhury", "kind": "person", "label": "Abhik Roychoudhury", "url": "https://arxiv.org/abs/2506.14683", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2504.08696", "kind": "paper", "label": "SeaView: Software Engineering Agent Visual Interface for Enhanced Workflow", "url": "https://arxiv.org/abs/2504.08696", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:timothy-bula", "kind": "person", "label": "Timothy Bula", "url": "https://arxiv.org/abs/2504.08696", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:saurabh-pujar", "kind": "person", "label": "Saurabh Pujar", "url": "https://arxiv.org/abs/2504.08696", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:luca-buratti", "kind": "person", "label": "Luca Buratti", "url": "https://arxiv.org/abs/2504.08696", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mihaela-bornea", "kind": "person", "label": "Mihaela Bornea", "url": "https://arxiv.org/abs/2504.08696", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:avirup-sil", "kind": "person", "label": "Avirup Sil", "url": "https://arxiv.org/abs/2504.08696", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2506.09289", "kind": "paper", "label": "UTBoost: Rigorous Evaluation of Coding Agents on SWE-Bench", "url": "https://arxiv.org/abs/2506.09289", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:boxi-yu", "kind": "person", "label": "Boxi Yu", "url": "https://arxiv.org/abs/2506.09289", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuxuan-zhu", "kind": "person", "label": "Yuxuan Zhu", "url": "https://arxiv.org/abs/2506.09289", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:pinjia-he", "kind": "person", "label": "Pinjia He", "url": "https://arxiv.org/abs/2506.09289", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daniel-kang", "kind": "person", "label": "Daniel Kang", "url": "https://arxiv.org/abs/2506.09289", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2506.12286", "kind": "paper", "label": "The SWE-Bench Illusion: When High-performing LLMs Remember Instead of Reason", "url": "https://arxiv.org/abs/2506.12286", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:roshanak-zilouchian-moghaddam", "kind": "person", "label": "Roshanak Zilouchian Moghaddam", "url": "https://arxiv.org/abs/2506.12286", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2410.04485", "kind": "paper", "label": "Exploring the Potential of Conversational Test Suite Based Program Repair on SWE-bench", "url": "https://arxiv.org/abs/2410.04485", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:anton-cheshkov", "kind": "person", "label": "Anton Cheshkov", "url": "https://arxiv.org/abs/2410.04485", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:pavel-zadorozhny", "kind": "person", "label": "Pavel Zadorozhny", "url": "https://arxiv.org/abs/2410.04485", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rodion-levichev", "kind": "person", "label": "Rodion Levichev", "url": "https://arxiv.org/abs/2410.04485", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:evgeny-maslov", "kind": "person", "label": "Evgeny Maslov", "url": "https://arxiv.org/abs/2410.04485", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ronaldo-franco-jaldin", "kind": "person", "label": "Ronaldo Franco Jaldin", "url": "https://arxiv.org/abs/2410.04485", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.15223", "kind": "paper", "label": "Are \"Solved Issues\" in SWE-bench Really Solved Correctly? An Empirical Study", "url": "https://arxiv.org/abs/2503.15223", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:you-wang", "kind": "person", "label": "You Wang", "url": "https://arxiv.org/abs/2503.15223", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:michael-pradel", "kind": "person", "label": "Michael Pradel", "url": "https://arxiv.org/abs/2503.15223", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhongxin-liu", "kind": "person", "label": "Zhongxin Liu", "url": "https://arxiv.org/abs/2503.15223", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2310.06770", "kind": "paper", "label": "SWE-bench: Can Language Models Resolve Real-World GitHub Issues?", "url": "https://arxiv.org/abs/2310.06770", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alexander-wettig", "kind": "person", "label": "Alexander Wettig", "url": "https://arxiv.org/abs/2310.06770", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kexin-pei", "kind": "person", "label": "Kexin Pei", "url": "https://arxiv.org/abs/2310.06770", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ofir-press", "kind": "person", "label": "Ofir Press", "url": "https://arxiv.org/abs/2310.06770", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:karthik-narasimhan", "kind": "person", "label": "Karthik Narasimhan", "url": "https://arxiv.org/abs/2310.06770", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2408.14354", "kind": "paper", "label": "SWE-bench-java: A GitHub Issue Resolving Benchmark for Java", "url": "https://arxiv.org/abs/2408.14354", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daoguang-zan", "kind": "person", "label": "Daoguang Zan", "url": "https://arxiv.org/abs/2408.14354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhirong-huang", "kind": "person", "label": "Zhirong Huang", "url": "https://arxiv.org/abs/2408.14354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ailun-yu", "kind": "person", "label": "Ailun Yu", "url": "https://arxiv.org/abs/2408.14354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shaoxin-lin", "kind": "person", "label": "Shaoxin Lin", "url": "https://arxiv.org/abs/2408.14354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yifan-shi", "kind": "person", "label": "Yifan Shi", "url": "https://arxiv.org/abs/2408.14354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dong-chen", "kind": "person", "label": "Dong Chen", "url": "https://arxiv.org/abs/2408.14354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zongshuai-qi", "kind": "person", "label": "Zongshuai Qi", "url": "https://arxiv.org/abs/2408.14354", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2506.17208", "kind": "paper", "label": "Dissecting the SWE-Bench Leaderboards: Profiling Submitters and Architectures of LLM- and Agent-Based Repair Systems", "url": "https://arxiv.org/abs/2506.17208", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:matias-martinez", "kind": "person", "label": "Matias Martinez", "url": "https://arxiv.org/abs/2506.17208", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xavier-franch", "kind": "person", "label": "Xavier Franch", "url": "https://arxiv.org/abs/2506.17208", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.04449", "kind": "paper", "label": "What's in a Benchmark? The Case of SWE-Bench in Automated Program Repair", "url": "https://arxiv.org/abs/2602.04449", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.03411", "kind": "paper", "label": "SWE-Master: Unleashing the Potential of Software Engineering Agents via Post-Training", "url": "https://arxiv.org/abs/2602.03411", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:huatong-song", "kind": "person", "label": "Huatong Song", "url": "https://arxiv.org/abs/2602.03411", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lisheng-huang", "kind": "person", "label": "Lisheng Huang", "url": "https://arxiv.org/abs/2602.03411", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shuang-sun", "kind": "person", "label": "Shuang Sun", "url": "https://arxiv.org/abs/2602.03411", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jinhao-jiang", "kind": "person", "label": "Jinhao Jiang", "url": "https://arxiv.org/abs/2602.03411", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ran-le", "kind": "person", "label": "Ran Le", "url": "https://arxiv.org/abs/2602.03411", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daixuan-cheng", "kind": "person", "label": "Daixuan Cheng", "url": "https://arxiv.org/abs/2602.03411", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guoxin-chen", "kind": "person", "label": "Guoxin Chen", "url": "https://arxiv.org/abs/2602.03411", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yiwen-hu", "kind": "person", "label": "Yiwen Hu", "url": "https://arxiv.org/abs/2602.03411", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2601.22129", "kind": "paper", "label": "SWE-Replay: Efficient Test-Time Scaling for Software Engineering Agents", "url": "https://arxiv.org/abs/2601.22129", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yifeng-ding", "kind": "person", "label": "Yifeng Ding", "url": "https://arxiv.org/abs/2601.22129", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.00520", "kind": "paper", "label": "SWE-ABS: Adversarial Benchmark Strengthening Exposes Inflated Success Rates on Test-based Benchmark", "url": "https://arxiv.org/abs/2603.00520", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yang-cao", "kind": "person", "label": "Yang Cao", "url": "https://arxiv.org/abs/2603.00520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuzhong-zhang", "kind": "person", "label": "Yuzhong Zhang", "url": "https://arxiv.org/abs/2603.00520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:liting-lin", "kind": "person", "label": "Liting Lin", "url": "https://arxiv.org/abs/2603.00520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:junjielong-xu", "kind": "person", "label": "Junjielong Xu", "url": "https://arxiv.org/abs/2603.00520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhiqing-zhong", "kind": "person", "label": "Zhiqing Zhong", "url": "https://arxiv.org/abs/2603.00520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qinghua-xu", "kind": "person", "label": "Qinghua Xu", "url": "https://arxiv.org/abs/2603.00520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guancheng-wang", "kind": "person", "label": "Guancheng Wang", "url": "https://arxiv.org/abs/2603.00520", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.03419", "kind": "paper", "label": "SWE-World: Building Software Engineering Agents in Docker-Free Environments", "url": "https://arxiv.org/abs/2602.03419", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhihao-lv", "kind": "person", "label": "Zhihao Lv", "url": "https://arxiv.org/abs/2602.03419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zongchao-chen", "kind": "person", "label": "Zongchao Chen", "url": "https://arxiv.org/abs/2602.03419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2512.17419", "kind": "paper", "label": "SWE-Bench++: A Framework for the Scalable Generation of Software Engineering Benchmarks from Open-Source Repositories", "url": "https://arxiv.org/abs/2512.17419", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lilin-wang", "kind": "person", "label": "Lilin Wang", "url": "https://arxiv.org/abs/2512.17419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lucas-ramalho", "kind": "person", "label": "Lucas Ramalho", "url": "https://arxiv.org/abs/2512.17419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:alan-celestino", "kind": "person", "label": "Alan Celestino", "url": "https://arxiv.org/abs/2512.17419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:phuc-anthony-pham", "kind": "person", "label": "Phuc Anthony Pham", "url": "https://arxiv.org/abs/2512.17419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yu-liu", "kind": "person", "label": "Yu Liu", "url": "https://arxiv.org/abs/2512.17419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:umang-kumar-sinha", "kind": "person", "label": "Umang Kumar Sinha", "url": "https://arxiv.org/abs/2512.17419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:andres-portillo", "kind": "person", "label": "Andres Portillo", "url": "https://arxiv.org/abs/2512.17419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:onassis-osunwa", "kind": "person", "label": "Onassis Osunwa", "url": "https://arxiv.org/abs/2512.17419", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2507.00014", "kind": "paper", "label": "SWE-Bench-CL: Continual Learning for Coding Agents", "url": "https://arxiv.org/abs/2507.00014", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:thomas-joshi", "kind": "person", "label": "Thomas Joshi", "url": "https://arxiv.org/abs/2507.00014", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shayan-chowdhury", "kind": "person", "label": "Shayan Chowdhury", "url": "https://arxiv.org/abs/2507.00014", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fatih-uysal", "kind": "person", "label": "Fatih Uysal", "url": "https://arxiv.org/abs/2507.00014", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2504.02605", "kind": "paper", "label": "Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving", "url": "https://arxiv.org/abs/2504.02605", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hanwu-chen", "kind": "person", "label": "Hanwu Chen", "url": "https://arxiv.org/abs/2504.02605", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:linhao-zhang", "kind": "person", "label": "Linhao Zhang", "url": "https://arxiv.org/abs/2504.02605", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shulin-xin", "kind": "person", "label": "Shulin Xin", "url": "https://arxiv.org/abs/2504.02605", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lu-chen", "kind": "person", "label": "Lu Chen", "url": "https://arxiv.org/abs/2504.02605", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qi-liu", "kind": "person", "label": "Qi Liu", "url": "https://arxiv.org/abs/2504.02605", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2507.09108", "kind": "paper", "label": "SPICE: An Automated SWE-Bench Labeling Pipeline for Issue Clarity, Test Coverage, and Effort Estimation", "url": "https://arxiv.org/abs/2507.09108", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gustavo-a-oliva", "kind": "person", "label": "Gustavo A. Oliva", "url": "https://arxiv.org/abs/2507.09108", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gopi-krishnan-rajbahadur", "kind": "person", "label": "Gopi Krishnan Rajbahadur", "url": "https://arxiv.org/abs/2507.09108", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:aaditya-bhatia", "kind": "person", "label": "Aaditya Bhatia", "url": "https://arxiv.org/abs/2507.09108", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haoxiang-zhang", "kind": "person", "label": "Haoxiang Zhang", "url": "https://arxiv.org/abs/2507.09108", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yihao-chen", "kind": "person", "label": "Yihao Chen", "url": "https://arxiv.org/abs/2507.09108", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhilong-chen", "kind": "person", "label": "Zhilong Chen", "url": "https://arxiv.org/abs/2507.09108", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:arthur-leung", "kind": "person", "label": "Arthur Leung", "url": "https://arxiv.org/abs/2507.09108", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dayi-lin", "kind": "person", "label": "Dayi Lin", "url": "https://arxiv.org/abs/2507.09108", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.09540", "kind": "paper", "label": "SWE-Bench Mobile: Can Large Language Model Agents Develop Industry-Level Mobile Applications?", "url": "https://arxiv.org/abs/2602.09540", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:muxin-tian", "kind": "person", "label": "Muxin Tian", "url": "https://arxiv.org/abs/2602.09540", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhe-wang", "kind": "person", "label": "Zhe Wang", "url": "https://arxiv.org/abs/2602.09540", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:blair-yang", "kind": "person", "label": "Blair Yang", "url": "https://arxiv.org/abs/2602.09540", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhenwei-tang", "kind": "person", "label": "Zhenwei Tang", "url": "https://arxiv.org/abs/2602.09540", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kunlun-zhu", "kind": "person", "label": "Kunlun Zhu", "url": "https://arxiv.org/abs/2602.09540", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:honghua-dong", "kind": "person", "label": "Honghua Dong", "url": "https://arxiv.org/abs/2602.09540", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hanchen-li", "kind": "person", "label": "Hanchen Li", "url": "https://arxiv.org/abs/2602.09540", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinni-xie", "kind": "person", "label": "Xinni Xie", "url": "https://arxiv.org/abs/2602.09540", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.12344", "kind": "paper", "label": "Claw-SWE-Bench: A Benchmark for Evaluating OpenClaw-style Agent Harnesses on Coding Tasks", "url": "https://arxiv.org/abs/2606.12344", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mengyu-zheng", "kind": "person", "label": "Mengyu Zheng", "url": "https://arxiv.org/abs/2606.12344", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kai-han", "kind": "person", "label": "Kai Han", "url": "https://arxiv.org/abs/2606.12344", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:boxun-li", "kind": "person", "label": "Boxun Li", "url": "https://arxiv.org/abs/2606.12344", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haiyang-xu", "kind": "person", "label": "Haiyang Xu", "url": "https://arxiv.org/abs/2606.12344", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuchuan-tian", "kind": "person", "label": "Yuchuan Tian", "url": "https://arxiv.org/abs/2606.12344", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hang-zhou", "kind": "person", "label": "Hang Zhou", "url": "https://arxiv.org/abs/2606.12344", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2607.00990", "kind": "paper", "label": "SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests", "url": "https://arxiv.org/abs/2607.00990", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yaoqi-guo", "kind": "person", "label": "Yaoqi Guo", "url": "https://arxiv.org/abs/2607.00990", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jie-m-zhang", "kind": "person", "label": "Jie M. Zhang", "url": "https://arxiv.org/abs/2607.00990", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yun-ma", "kind": "person", "label": "Yun Ma", "url": "https://arxiv.org/abs/2607.00990", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2512.10218", "kind": "paper", "label": "Does SWE-Bench-Verified Test Agent Ability or Model Memory?", "url": "https://arxiv.org/abs/2512.10218", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:thanosan-prathifkumar", "kind": "person", "label": "Thanosan Prathifkumar", "url": "https://arxiv.org/abs/2512.10218", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:noble-saji-mathews", "kind": "person", "label": "Noble Saji Mathews", "url": "https://arxiv.org/abs/2512.10218", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:meiyappan-nagappan", "kind": "person", "label": "Meiyappan Nagappan", "url": "https://arxiv.org/abs/2512.10218", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.11051", "kind": "paper", "label": "On Problems of Implicit Context Compression for Software Engineering Agents", "url": "https://arxiv.org/abs/2605.11051", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kirill-gelvan", "kind": "person", "label": "Kirill Gelvan", "url": "https://arxiv.org/abs/2605.11051", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:igor-slinko", "kind": "person", "label": "Igor Slinko", "url": "https://arxiv.org/abs/2605.11051", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:felix-steinbauer", "kind": "person", "label": "Felix Steinbauer", "url": "https://arxiv.org/abs/2605.11051", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:egor-bogomolov", "kind": "person", "label": "Egor Bogomolov", "url": "https://arxiv.org/abs/2605.11051", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:florian-kofler", "kind": "person", "label": "Florian Kofler", "url": "https://arxiv.org/abs/2605.11051", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yaroslav-zharov", "kind": "person", "label": "Yaroslav Zharov", "url": "https://arxiv.org/abs/2605.11051", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.13995", "kind": "paper", "label": "Dialogue SWE-Bench: A Benchmark for Dialogue-Driven Coding Agents", "url": "https://arxiv.org/abs/2606.13995", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:brendan-king", "kind": "person", "label": "Brendan King", "url": "https://arxiv.org/abs/2606.13995", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jeffrey-flanigan", "kind": "person", "label": "Jeffrey Flanigan", "url": "https://arxiv.org/abs/2606.13995", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.18332", "kind": "paper", "label": "Same Signal, Different Semantics: A Cross-Framework Behavioral Analysis of Software Engineering Agents", "url": "https://arxiv.org/abs/2605.18332", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wei-ma", "kind": "person", "label": "Wei Ma", "url": "https://arxiv.org/abs/2605.18332", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jingxu-gu", "kind": "person", "label": "Jingxu Gu", "url": "https://arxiv.org/abs/2605.18332", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tianling-li", "kind": "person", "label": "Tianling Li", "url": "https://arxiv.org/abs/2605.18332", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shangqing-liu", "kind": "person", "label": "Shangqing Liu", "url": "https://arxiv.org/abs/2605.18332", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lingxiao-jiang", "kind": "person", "label": "Lingxiao Jiang", "url": "https://arxiv.org/abs/2605.18332", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.00835", "kind": "paper", "label": "Agentic Tool Use in Large Language Models", "url": "https://arxiv.org/abs/2604.00835", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jinchao-hu", "kind": "person", "label": "Jinchao Hu", "url": "https://arxiv.org/abs/2604.00835", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:meizhi-zhong", "kind": "person", "label": "Meizhi Zhong", "url": "https://arxiv.org/abs/2604.00835", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:kehai-chen", "kind": "person", "label": "Kehai Chen", "url": "https://arxiv.org/abs/2604.00835", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xuefeng-bai", "kind": "person", "label": "Xuefeng Bai", "url": "https://arxiv.org/abs/2604.00835", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:min-zhang", "kind": "person", "label": "Min Zhang", "url": "https://arxiv.org/abs/2604.00835", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.12430", "kind": "paper", "label": "Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward", "url": "https://arxiv.org/abs/2602.12430", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:renjun-xu", "kind": "person", "label": "Renjun Xu", "url": "https://arxiv.org/abs/2602.12430", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yang-yan", "kind": "person", "label": "Yang Yan", "url": "https://arxiv.org/abs/2602.12430", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.12908", "kind": "paper", "label": "SENTINEL: Failure-Driven Reinforcement Learning for Training Tool-Using Language Model Agents", "url": "https://arxiv.org/abs/2606.12908", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ziyi-wang", "kind": "person", "label": "Ziyi Wang", "url": "https://arxiv.org/abs/2606.12908", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuxuan-lu", "kind": "person", "label": "Yuxuan Lu", "url": "https://arxiv.org/abs/2606.12908", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yimeng-zhang", "kind": "person", "label": "Yimeng Zhang", "url": "https://arxiv.org/abs/2606.12908", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qun-liu", "kind": "person", "label": "Qun Liu", "url": "https://arxiv.org/abs/2606.12908", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chen-luo", "kind": "person", "label": "Chen Luo", "url": "https://arxiv.org/abs/2606.12908", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiri-gesi", "kind": "person", "label": "Jiri Gesi", "url": "https://arxiv.org/abs/2606.12908", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hanqing-lu", "kind": "person", "label": "Hanqing Lu", "url": "https://arxiv.org/abs/2606.12908", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yisi-sang", "kind": "person", "label": "Yisi Sang", "url": "https://arxiv.org/abs/2606.12908", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.21590", "kind": "paper", "label": "AgenticQwen: Training Small Agentic Language Models with Dual Data Flywheels for Industrial-Scale Tool Use", "url": "https://arxiv.org/abs/2604.21590", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuanjie-lyu", "kind": "person", "label": "Yuanjie Lyu", "url": "https://arxiv.org/abs/2604.21590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chengyu-wang", "kind": "person", "label": "Chengyu Wang", "url": "https://arxiv.org/abs/2604.21590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haonan-zheng", "kind": "person", "label": "Haonan Zheng", "url": "https://arxiv.org/abs/2604.21590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuanhao-yue", "kind": "person", "label": "Yuanhao Yue", "url": "https://arxiv.org/abs/2604.21590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:junbing-yan", "kind": "person", "label": "Junbing Yan", "url": "https://arxiv.org/abs/2604.21590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ming-wang", "kind": "person", "label": "Ming Wang", "url": "https://arxiv.org/abs/2604.21590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jun-huang", "kind": "person", "label": "Jun Huang", "url": "https://arxiv.org/abs/2604.21590", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.01279", "kind": "paper", "label": "TUMIX: Multi-Agent Test-Time Scaling with Tool-Use Mixture", "url": "https://arxiv.org/abs/2510.01279", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yongchao-chen", "kind": "person", "label": "Yongchao Chen", "url": "https://arxiv.org/abs/2510.01279", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiefeng-chen", "kind": "person", "label": "Jiefeng Chen", "url": "https://arxiv.org/abs/2510.01279", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rui-meng", "kind": "person", "label": "Rui Meng", "url": "https://arxiv.org/abs/2510.01279", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ji-yin", "kind": "person", "label": "Ji Yin", "url": "https://arxiv.org/abs/2510.01279", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:na-li", "kind": "person", "label": "Na Li", "url": "https://arxiv.org/abs/2510.01279", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chuchu-fan", "kind": "person", "label": "Chuchu Fan", "url": "https://arxiv.org/abs/2510.01279", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chi-wang", "kind": "person", "label": "Chi Wang", "url": "https://arxiv.org/abs/2510.01279", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tomas-pfister", "kind": "person", "label": "Tomas Pfister", "url": "https://arxiv.org/abs/2510.01279", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2607.04686", "kind": "paper", "label": "ToolFailBench: Diagnosing Tool-Use Failures in LLM Agents", "url": "https://arxiv.org/abs/2607.04686", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:harsh-soni", "kind": "person", "label": "Harsh Soni", "url": "https://arxiv.org/abs/2607.04686", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.02050", "kind": "paper", "label": "Rethinking the Role of Entropy in Optimizing Tool-Use Behaviors for Large Language Model Agents", "url": "https://arxiv.org/abs/2602.02050", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zeping-li", "kind": "person", "label": "Zeping Li", "url": "https://arxiv.org/abs/2602.02050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hongru-wang", "kind": "person", "label": "Hongru Wang", "url": "https://arxiv.org/abs/2602.02050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yiwen-zhao", "kind": "person", "label": "Yiwen Zhao", "url": "https://arxiv.org/abs/2602.02050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guanhua-chen", "kind": "person", "label": "Guanhua Chen", "url": "https://arxiv.org/abs/2602.02050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yixia-li", "kind": "person", "label": "Yixia Li", "url": "https://arxiv.org/abs/2602.02050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:keyang-chen", "kind": "person", "label": "Keyang Chen", "url": "https://arxiv.org/abs/2602.02050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yixin-cao", "kind": "person", "label": "Yixin Cao", "url": "https://arxiv.org/abs/2602.02050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:guangnan-ye", "kind": "person", "label": "Guangnan Ye", "url": "https://arxiv.org/abs/2602.02050", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.08567", "kind": "paper", "label": "MATRIX: Multimodal Agent Tuning for Robust Tool-Use Reasoning", "url": "https://arxiv.org/abs/2510.08567", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tajamul-ashraf", "kind": "person", "label": "Tajamul Ashraf", "url": "https://arxiv.org/abs/2510.08567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:umair-nawaz", "kind": "person", "label": "Umair Nawaz", "url": "https://arxiv.org/abs/2510.08567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:abdelrahman-m-shaker", "kind": "person", "label": "Abdelrahman M. Shaker", "url": "https://arxiv.org/abs/2510.08567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:rao-anwer", "kind": "person", "label": "Rao Anwer", "url": "https://arxiv.org/abs/2510.08567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:philip-torr", "kind": "person", "label": "Philip Torr", "url": "https://arxiv.org/abs/2510.08567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fahad-shahbaz-khan", "kind": "person", "label": "Fahad Shahbaz Khan", "url": "https://arxiv.org/abs/2510.08567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:salman-khan", "kind": "person", "label": "Salman Khan", "url": "https://arxiv.org/abs/2510.08567", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2605.18747", "kind": "paper", "label": "Code as Agent Harness", "url": "https://arxiv.org/abs/2605.18747", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xuying-ning", "kind": "person", "label": "Xuying Ning", "url": "https://arxiv.org/abs/2605.18747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:katherine-tieu", "kind": "person", "label": "Katherine Tieu", "url": "https://arxiv.org/abs/2605.18747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dongqi-fu", "kind": "person", "label": "Dongqi Fu", "url": "https://arxiv.org/abs/2605.18747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tianxin-wei", "kind": "person", "label": "Tianxin Wei", "url": "https://arxiv.org/abs/2605.18747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zihao-li", "kind": "person", "label": "Zihao Li", "url": "https://arxiv.org/abs/2605.18747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yuanchen-bei", "kind": "person", "label": "Yuanchen Bei", "url": "https://arxiv.org/abs/2605.18747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiaru-zou", "kind": "person", "label": "Jiaru Zou", "url": "https://arxiv.org/abs/2605.18747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mengting-ai", "kind": "person", "label": "Mengting Ai", "url": "https://arxiv.org/abs/2605.18747", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.19369", "kind": "paper", "label": "SLM-Based Agentic AI with P-C-G: Optimized for Korean Tool Use", "url": "https://arxiv.org/abs/2509.19369", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:changhyun-jeon", "kind": "person", "label": "Changhyun Jeon", "url": "https://arxiv.org/abs/2509.19369", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jinhee-park", "kind": "person", "label": "Jinhee Park", "url": "https://arxiv.org/abs/2509.19369", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jungwoo-choi", "kind": "person", "label": "Jungwoo Choi", "url": "https://arxiv.org/abs/2509.19369", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:keonwoo-kim", "kind": "person", "label": "Keonwoo Kim", "url": "https://arxiv.org/abs/2509.19369", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jisu-kim", "kind": "person", "label": "Jisu Kim", "url": "https://arxiv.org/abs/2509.19369", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:minji-hong", "kind": "person", "label": "Minji Hong", "url": "https://arxiv.org/abs/2509.19369", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2508.16260", "kind": "paper", "label": "MCPVerse: An Expansive, Real-World Benchmark for Agentic Tool Use", "url": "https://arxiv.org/abs/2508.16260", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fei-lei", "kind": "person", "label": "Fei Lei", "url": "https://arxiv.org/abs/2508.16260", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yibo-yang", "kind": "person", "label": "Yibo Yang", "url": "https://arxiv.org/abs/2508.16260", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wenxiu-sun", "kind": "person", "label": "Wenxiu Sun", "url": "https://arxiv.org/abs/2508.16260", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dahua-lin", "kind": "person", "label": "Dahua Lin", "url": "https://arxiv.org/abs/2508.16260", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.14480", "kind": "paper", "label": "Process-Supervised Reinforcement Learning for Interactive Multimodal Tool-Use Agents", "url": "https://arxiv.org/abs/2509.14480", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:weiting-tan", "kind": "person", "label": "Weiting Tan", "url": "https://arxiv.org/abs/2509.14480", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinghua-qu", "kind": "person", "label": "Xinghua Qu", "url": "https://arxiv.org/abs/2509.14480", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ming-tu", "kind": "person", "label": "Ming Tu", "url": "https://arxiv.org/abs/2509.14480", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:meng-ge", "kind": "person", "label": "Meng Ge", "url": "https://arxiv.org/abs/2509.14480", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:andy-t-liu", "kind": "person", "label": "Andy T. Liu", "url": "https://arxiv.org/abs/2509.14480", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:philipp-koehn", "kind": "person", "label": "Philipp Koehn", "url": "https://arxiv.org/abs/2509.14480", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:lu-lu", "kind": "person", "label": "Lu Lu", "url": "https://arxiv.org/abs/2509.14480", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2511.14460", "kind": "paper", "label": "Agent-R1: A Unified and Modular Framework for Agentic Reinforcement Learning", "url": "https://arxiv.org/abs/2511.14460", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mingyue-cheng", "kind": "person", "label": "Mingyue Cheng", "url": "https://arxiv.org/abs/2511.14460", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shuo-yu", "kind": "person", "label": "Shuo Yu", "url": "https://arxiv.org/abs/2511.14460", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daoyu-wang", "kind": "person", "label": "Daoyu Wang", "url": "https://arxiv.org/abs/2511.14460", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:qingchuan-li", "kind": "person", "label": "Qingchuan Li", "url": "https://arxiv.org/abs/2511.14460", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiaoyu-tao", "kind": "person", "label": "Xiaoyu Tao", "url": "https://arxiv.org/abs/2511.14460", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jie-ouyang", "kind": "person", "label": "Jie Ouyang", "url": "https://arxiv.org/abs/2511.14460", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yucong-luo", "kind": "person", "label": "Yucong Luo", "url": "https://arxiv.org/abs/2511.14460", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yitong-zhou", "kind": "person", "label": "Yitong Zhou", "url": "https://arxiv.org/abs/2511.14460", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2503.12687", "kind": "paper", "label": "AI Agents: Evolution, Architecture, and Real-World Applications", "url": "https://arxiv.org/abs/2503.12687", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:naveen-krishnan", "kind": "person", "label": "Naveen Krishnan", "url": "https://arxiv.org/abs/2503.12687", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.20036", "kind": "paper", "label": "ToolScope: Enhancing LLM Agent Tool Use through Tool Merging and Context-Aware Filtering", "url": "https://arxiv.org/abs/2510.20036", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:marianne-menglin-liu", "kind": "person", "label": "Marianne Menglin Liu", "url": "https://arxiv.org/abs/2510.20036", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:daniel-garcia", "kind": "person", "label": "Daniel Garcia", "url": "https://arxiv.org/abs/2510.20036", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fjona-parllaku", "kind": "person", "label": "Fjona Parllaku", "url": "https://arxiv.org/abs/2510.20036", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:vikas-upadhyay", "kind": "person", "label": "Vikas Upadhyay", "url": "https://arxiv.org/abs/2510.20036", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:syed-fahad-allam-shah", "kind": "person", "label": "Syed Fahad Allam Shah", "url": "https://arxiv.org/abs/2510.20036", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:dan-roth", "kind": "person", "label": "Dan Roth", "url": "https://arxiv.org/abs/2510.20036", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2606.11652", "kind": "paper", "label": "IAPO: Input Attribution-Aware Policy Optimization for Tool Use in Small Multimodal Agents", "url": "https://arxiv.org/abs/2606.11652", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yifan-yang", "kind": "person", "label": "Yifan Yang", "url": "https://arxiv.org/abs/2606.11652", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhen-zhang", "kind": "person", "label": "Zhen Zhang", "url": "https://arxiv.org/abs/2606.11652", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiayi-tian", "kind": "person", "label": "Jiayi Tian", "url": "https://arxiv.org/abs/2606.11652", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:liyan-tan", "kind": "person", "label": "Liyan Tan", "url": "https://arxiv.org/abs/2606.11652", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zheng-zhang", "kind": "person", "label": "Zheng Zhang", "url": "https://arxiv.org/abs/2606.11652", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2510.04550", "kind": "paper", "label": "TRAJECT-Bench:A Trajectory-Aware Benchmark for Evaluating Agentic Tool Use", "url": "https://arxiv.org/abs/2510.04550", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:pengfei-he", "kind": "person", "label": "Pengfei He", "url": "https://arxiv.org/abs/2510.04550", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zhenwei-dai", "kind": "person", "label": "Zhenwei Dai", "url": "https://arxiv.org/abs/2510.04550", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:bing-he", "kind": "person", "label": "Bing He", "url": "https://arxiv.org/abs/2510.04550", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:hui-liu", "kind": "person", "label": "Hui Liu", "url": "https://arxiv.org/abs/2510.04550", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xianfeng-tang", "kind": "person", "label": "Xianfeng Tang", "url": "https://arxiv.org/abs/2510.04550", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:juanhui-li", "kind": "person", "label": "Juanhui Li", "url": "https://arxiv.org/abs/2510.04550", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jiayuan-ding", "kind": "person", "label": "Jiayuan Ding", "url": "https://arxiv.org/abs/2510.04550", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.05432", "kind": "paper", "label": "Your LLM Agent Can Leak Your Data: Data Exfiltration via Backdoored Tool Use", "url": "https://arxiv.org/abs/2604.05432", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wuyang-zhang", "kind": "person", "label": "Wuyang Zhang", "url": "https://arxiv.org/abs/2604.05432", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:shichao-pei", "kind": "person", "label": "Shichao Pei", "url": "https://arxiv.org/abs/2604.05432", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2604.25135", "kind": "paper", "label": "FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments", "url": "https://arxiv.org/abs/2604.25135", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:amir-saeidi", "kind": "person", "label": "Amir Saeidi", "url": "https://arxiv.org/abs/2604.25135", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:venkatesh-mishra", "kind": "person", "label": "Venkatesh Mishra", "url": "https://arxiv.org/abs/2604.25135", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:souradeep-mukhopadhyay", "kind": "person", "label": "Souradeep Mukhopadhyay", "url": "https://arxiv.org/abs/2604.25135", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:gaowen-liu", "kind": "person", "label": "Gaowen Liu", "url": "https://arxiv.org/abs/2604.25135", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ali-payani", "kind": "person", "label": "Ali Payani", "url": "https://arxiv.org/abs/2604.25135", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jayanth-srinivasa", "kind": "person", "label": "Jayanth Srinivasa", "url": "https://arxiv.org/abs/2604.25135", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chitta-baral", "kind": "person", "label": "Chitta Baral", "url": "https://arxiv.org/abs/2604.25135", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2412.20145", "kind": "paper", "label": "Efficient Multi-Agent Collaboration with Tool Use for Online Planning in Complex Table Question Answering", "url": "https://arxiv.org/abs/2412.20145", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:wei-zhou", "kind": "person", "label": "Wei Zhou", "url": "https://arxiv.org/abs/2412.20145", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mohsen-mesgar", "kind": "person", "label": "Mohsen Mesgar", "url": "https://arxiv.org/abs/2412.20145", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:annemarie-friedrich", "kind": "person", "label": "Annemarie Friedrich", "url": "https://arxiv.org/abs/2412.20145", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:heike-adel", "kind": "person", "label": "Heike Adel", "url": "https://arxiv.org/abs/2412.20145", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2603.22862", "kind": "paper", "label": "The Evolution of Tool Use in LLM Agents: From Single-Tool Call to Multi-Tool Orchestration", "url": "https://arxiv.org/abs/2603.22862", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:haoyuan-xu", "kind": "person", "label": "Haoyuan Xu", "url": "https://arxiv.org/abs/2603.22862", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:chang-li", "kind": "person", "label": "Chang Li", "url": "https://arxiv.org/abs/2603.22862", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xinyan-ma", "kind": "person", "label": "Xinyan Ma", "url": "https://arxiv.org/abs/2603.22862", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xianhao-ou", "kind": "person", "label": "Xianhao Ou", "url": "https://arxiv.org/abs/2603.22862", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zihan-zhang", "kind": "person", "label": "Zihan Zhang", "url": "https://arxiv.org/abs/2603.22862", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:tao-he", "kind": "person", "label": "Tao He", "url": "https://arxiv.org/abs/2603.22862", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiangyu-liu", "kind": "person", "label": "Xiangyu Liu", "url": "https://arxiv.org/abs/2603.22862", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:zixiang-wang", "kind": "person", "label": "Zixiang Wang", "url": "https://arxiv.org/abs/2603.22862", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2602.00994", "kind": "paper", "label": "Reasoning and Tool-use Compete in Agentic RL:From Quantifying Interference to Disentangled Tuning", "url": "https://arxiv.org/abs/2602.00994", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:mingyang-yi", "kind": "person", "label": "Mingyang Yi", "url": "https://arxiv.org/abs/2602.00994", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xiuyu-li", "kind": "person", "label": "Xiuyu Li", "url": "https://arxiv.org/abs/2602.00994", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:ju-fan", "kind": "person", "label": "Ju Fan", "url": "https://arxiv.org/abs/2602.00994", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:fuxin-jiang", "kind": "person", "label": "Fuxin Jiang", "url": "https://arxiv.org/abs/2602.00994", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:binbin-chen", "kind": "person", "label": "Binbin Chen", "url": "https://arxiv.org/abs/2602.00994", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:peng-li", "kind": "person", "label": "Peng Li", "url": "https://arxiv.org/abs/2602.00994", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jie-song", "kind": "person", "label": "Jie Song", "url": "https://arxiv.org/abs/2602.00994", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2506.01716", "kind": "paper", "label": "Self-Challenging Language Model Agents", "url": "https://arxiv.org/abs/2506.01716", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:yifei-zhou", "kind": "person", "label": "Yifei Zhou", "url": "https://arxiv.org/abs/2506.01716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sergey-levine", "kind": "person", "label": "Sergey Levine", "url": "https://arxiv.org/abs/2506.01716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jason-weston", "kind": "person", "label": "Jason Weston", "url": "https://arxiv.org/abs/2506.01716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:xian-li", "kind": "person", "label": "Xian Li", "url": "https://arxiv.org/abs/2506.01716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:sainbayar-sukhbaatar", "kind": "person", "label": "Sainbayar Sukhbaatar", "url": "https://arxiv.org/abs/2506.01716", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2509.22504", "kind": "paper", "label": "Estimating the Empowerment of Language Model Agents", "url": "https://arxiv.org/abs/2509.22504", "source": "arxiv", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jinyeop-song", "kind": "person", "label": "Jinyeop Song", "url": "https://arxiv.org/abs/2509.22504", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:jeff-gore", "kind": "person", "label": "Jeff Gore", "url": "https://arxiv.org/abs/2509.22504", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:person:max-kleiman-weiner", "kind": "person", "label": "Max Kleiman-Weiner", "url": "https://arxiv.org/abs/2509.22504", "source": "arxiv-author", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2409.16997", "kind": "paper", "label": "INT-FlashAttention: Enabling Flash Attention for INT8 Quantization", "url": "https://arxiv.org/abs/2409.16997", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:shimao-chen", "kind": "person", "label": "Shimao Chen", "url": "https://arxiv.org/abs/2409.16997", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zirui-liu", "kind": "person", "label": "Zirui Liu", "url": "https://arxiv.org/abs/2409.16997", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhiying-wu", "kind": "person", "label": "Zhiying Wu", "url": "https://arxiv.org/abs/2409.16997", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ce-zheng", "kind": "person", "label": "Ce Zheng", "url": "https://arxiv.org/abs/2409.16997", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:peizhuang-cong", "kind": "person", "label": "Peizhuang Cong", "url": "https://arxiv.org/abs/2409.16997", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zihan-jiang", "kind": "person", "label": "Zihan Jiang", "url": "https://arxiv.org/abs/2409.16997", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yuhan-wu", "kind": "person", "label": "Yuhan Wu", "url": "https://arxiv.org/abs/2409.16997", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:lei-su", "kind": "person", "label": "Lei Su", "url": "https://arxiv.org/abs/2409.16997", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2507.11331", "kind": "paper", "label": "SystolicAttention: Fusing FlashAttention within a Single Systolic Array", "url": "https://arxiv.org/abs/2507.11331", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:jiawei-lin", "kind": "person", "label": "Jiawei Lin", "url": "https://arxiv.org/abs/2507.11331", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yuanlong-li", "kind": "person", "label": "Yuanlong Li", "url": "https://arxiv.org/abs/2507.11331", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:guokai-chen", "kind": "person", "label": "Guokai Chen", "url": "https://arxiv.org/abs/2507.11331", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:thomas-bourgeat", "kind": "person", "label": "Thomas Bourgeat", "url": "https://arxiv.org/abs/2507.11331", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2505.14201", "kind": "paper", "label": "FLASH-D: FlashAttention with Hidden Softmax Division", "url": "https://arxiv.org/abs/2505.14201", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:kosmas-alexandridis", "kind": "person", "label": "Kosmas Alexandridis", "url": "https://arxiv.org/abs/2505.14201", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:vasileios-titopoulos", "kind": "person", "label": "Vasileios Titopoulos", "url": "https://arxiv.org/abs/2505.14201", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:giorgos-dimitrakopoulos", "kind": "person", "label": "Giorgos Dimitrakopoulos", "url": "https://arxiv.org/abs/2505.14201", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2508.00367", "kind": "paper", "label": "Representation Shift: Unifying Token Compression with FlashAttention", "url": "https://arxiv.org/abs/2508.00367", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:joonmyung-choi", "kind": "person", "label": "Joonmyung Choi", "url": "https://arxiv.org/abs/2508.00367", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:sanghyeok-lee", "kind": "person", "label": "Sanghyeok Lee", "url": "https://arxiv.org/abs/2508.00367", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:byungoh-ko", "kind": "person", "label": "Byungoh Ko", "url": "https://arxiv.org/abs/2508.00367", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:eunseo-kim", "kind": "person", "label": "Eunseo Kim", "url": "https://arxiv.org/abs/2508.00367", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jihyung-kil", "kind": "person", "label": "Jihyung Kil", "url": "https://arxiv.org/abs/2508.00367", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hyunwoo-j-kim", "kind": "person", "label": "Hyunwoo J. Kim", "url": "https://arxiv.org/abs/2508.00367", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2505.14314", "kind": "paper", "label": "Low-Cost FlashAttention with Fused Exponential and Multiplication Hardware Operators", "url": "https://arxiv.org/abs/2505.14314", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:paper:2410.01359", "kind": "paper", "label": "FlashMask: Efficient and Rich Mask Extension of FlashAttention", "url": "https://arxiv.org/abs/2410.01359", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:guoxia-wang", "kind": "person", "label": "Guoxia Wang", "url": "https://arxiv.org/abs/2410.01359", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jinle-zeng", "kind": "person", "label": "Jinle Zeng", "url": "https://arxiv.org/abs/2410.01359", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xiyuan-xiao", "kind": "person", "label": "Xiyuan Xiao", "url": "https://arxiv.org/abs/2410.01359", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:siming-wu", "kind": "person", "label": "Siming Wu", "url": "https://arxiv.org/abs/2410.01359", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jiabin-yang", "kind": "person", "label": "Jiabin Yang", "url": "https://arxiv.org/abs/2410.01359", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:lujing-zheng", "kind": "person", "label": "Lujing Zheng", "url": "https://arxiv.org/abs/2410.01359", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zeyu-chen", "kind": "person", "label": "Zeyu Chen", "url": "https://arxiv.org/abs/2410.01359", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2510.06834", "kind": "paper", "label": "Vectorized FlashAttention with Low-cost Exponential Computation in RISC-V Vector Processors", "url": "https://arxiv.org/abs/2510.06834", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:paper:2603.06738", "kind": "paper", "label": "Rank-Factorized Implicit Neural Bias: Scaling Super-Resolution Transformer with FlashAttention", "url": "https://arxiv.org/abs/2603.06738", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:dongheon-lee", "kind": "person", "label": "Dongheon Lee", "url": "https://arxiv.org/abs/2603.06738", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:seokju-yun", "kind": "person", "label": "Seokju Yun", "url": "https://arxiv.org/abs/2603.06738", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jaegyun-im", "kind": "person", "label": "Jaegyun Im", "url": "https://arxiv.org/abs/2603.06738", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:youngmin-ro", "kind": "person", "label": "Youngmin Ro", "url": "https://arxiv.org/abs/2603.06738", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2511.00295", "kind": "paper", "label": "H-FA: A Hybrid Floating-Point and Logarithmic Approach to Hardware Accelerated FlashAttention", "url": "https://arxiv.org/abs/2511.00295", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:paper:2412.03317", "kind": "paper", "label": "FlashAttention on a Napkin: A Diagrammatic Approach to Deep Learning IO-Awareness", "url": "https://arxiv.org/abs/2412.03317", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:vincent-abbott", "kind": "person", "label": "Vincent Abbott", "url": "https://arxiv.org/abs/2412.03317", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:gioele-zardini", "kind": "person", "label": "Gioele Zardini", "url": "https://arxiv.org/abs/2412.03317", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.00555", "kind": "paper", "label": "Sim-FA: A GPGPU Simulator Framework for Fine-Grained FlashAttention Pipeline Analysis", "url": "https://arxiv.org/abs/2605.00555", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:zhongchun-zhou", "kind": "person", "label": "Zhongchun Zhou", "url": "https://arxiv.org/abs/2605.00555", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yuhang-gu", "kind": "person", "label": "Yuhang Gu", "url": "https://arxiv.org/abs/2605.00555", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chengtao-lai", "kind": "person", "label": "Chengtao Lai", "url": "https://arxiv.org/abs/2605.00555", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ya-wang", "kind": "person", "label": "Ya Wang", "url": "https://arxiv.org/abs/2605.00555", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wei-zhang", "kind": "person", "label": "Wei Zhang", "url": "https://arxiv.org/abs/2605.00555", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2602.11016", "kind": "paper", "label": "From Buffers to Registers: Unlocking Fine-Grained FlashAttention with Hybrid-Bonded 3D NPU Co-Design", "url": "https://arxiv.org/abs/2602.11016", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:jinxin-yu", "kind": "person", "label": "Jinxin Yu", "url": "https://arxiv.org/abs/2602.11016", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yudong-pan", "kind": "person", "label": "Yudong Pan", "url": "https://arxiv.org/abs/2602.11016", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mengdi-wang", "kind": "person", "label": "Mengdi Wang", "url": "https://arxiv.org/abs/2602.11016", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:huawei-li", "kind": "person", "label": "Huawei Li", "url": "https://arxiv.org/abs/2602.11016", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yinhe-han", "kind": "person", "label": "Yinhe Han", "url": "https://arxiv.org/abs/2602.11016", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xiaowei-li", "kind": "person", "label": "Xiaowei Li", "url": "https://arxiv.org/abs/2602.11016", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ying-wang", "kind": "person", "label": "Ying Wang", "url": "https://arxiv.org/abs/2602.11016", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2509.25224", "kind": "paper", "label": "AMLA: MUL by ADD in FlashAttention Rescaling", "url": "https://arxiv.org/abs/2509.25224", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:qichen-liao", "kind": "person", "label": "Qichen Liao", "url": "https://arxiv.org/abs/2509.25224", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chengqiu-hu", "kind": "person", "label": "Chengqiu Hu", "url": "https://arxiv.org/abs/2509.25224", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:fangzheng-miao", "kind": "person", "label": "Fangzheng Miao", "url": "https://arxiv.org/abs/2509.25224", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:bao-li", "kind": "person", "label": "Bao Li", "url": "https://arxiv.org/abs/2509.25224", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yiyang-liu", "kind": "person", "label": "Yiyang Liu", "url": "https://arxiv.org/abs/2509.25224", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:junlong-lyu", "kind": "person", "label": "Junlong Lyu", "url": "https://arxiv.org/abs/2509.25224", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:lirui-jiang", "kind": "person", "label": "Lirui Jiang", "url": "https://arxiv.org/abs/2509.25224", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jun-wang", "kind": "person", "label": "Jun Wang", "url": "https://arxiv.org/abs/2509.25224", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2603.05451", "kind": "paper", "label": "FlashAttention-4: Algorithm and Kernel Pipelining Co-Design for Asymmetric Hardware Scaling", "url": "https://arxiv.org/abs/2603.05451", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:ted-zadouri", "kind": "person", "label": "Ted Zadouri", "url": "https://arxiv.org/abs/2603.05451", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:markus-hoehnerbach", "kind": "person", "label": "Markus Hoehnerbach", "url": "https://arxiv.org/abs/2603.05451", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jay-shah", "kind": "person", "label": "Jay Shah", "url": "https://arxiv.org/abs/2603.05451", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:timmy-liu", "kind": "person", "label": "Timmy Liu", "url": "https://arxiv.org/abs/2603.05451", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:vijay-thakkar", "kind": "person", "label": "Vijay Thakkar", "url": "https://arxiv.org/abs/2603.05451", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2607.04302", "kind": "paper", "label": "HiFA4: Training-Free 4-bit FlashAttention on Ascend HIF4 NPUs for LLM Inference", "url": "https://arxiv.org/abs/2607.04302", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:hui-dong", "kind": "person", "label": "Hui Dong", "url": "https://arxiv.org/abs/2607.04302", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yanzhao-li", "kind": "person", "label": "Yanzhao Li", "url": "https://arxiv.org/abs/2607.04302", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jie-gao", "kind": "person", "label": "Jie Gao", "url": "https://arxiv.org/abs/2607.04302", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chunlu-li", "kind": "person", "label": "Chunlu Li", "url": "https://arxiv.org/abs/2607.04302", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhiyuan-zhang", "kind": "person", "label": "Zhiyuan Zhang", "url": "https://arxiv.org/abs/2607.04302", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yupeng-sun", "kind": "person", "label": "Yupeng Sun", "url": "https://arxiv.org/abs/2607.04302", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhenyuan-chen", "kind": "person", "label": "Zhenyuan Chen", "url": "https://arxiv.org/abs/2607.04302", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhiqiang-zou", "kind": "person", "label": "Zhiqiang Zou", "url": "https://arxiv.org/abs/2607.04302", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.00028", "kind": "paper", "label": "Sequence-Aware Split Heuristic to Mitigate SM Underutilization in FlashAttention-3 Low-Head-Count Decoding", "url": "https://arxiv.org/abs/2604.00028", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:mart-llopart-font", "kind": "person", "label": "Mart\u00ed Llopart Font", "url": "https://arxiv.org/abs/2604.00028", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:javier-hernando", "kind": "person", "label": "Javier Hernando", "url": "https://arxiv.org/abs/2604.00028", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:cristina-espa-a-bonet", "kind": "person", "label": "Cristina Espa\u00f1a-Bonet", "url": "https://arxiv.org/abs/2604.00028", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2312.11918", "kind": "paper", "label": "A Case Study in CUDA Kernel Fusion: Implementing FlashAttention-2 on NVIDIA Hopper Architecture using the CUTLASS Library", "url": "https://arxiv.org/abs/2312.11918", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:ganesh-bikshandi", "kind": "person", "label": "Ganesh Bikshandi", "url": "https://arxiv.org/abs/2312.11918", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2410.16663", "kind": "paper", "label": "FastAttention: Extend FlashAttention2 to NPUs and Low-resource GPUs", "url": "https://arxiv.org/abs/2410.16663", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:haoran-lin", "kind": "person", "label": "Haoran Lin", "url": "https://arxiv.org/abs/2410.16663", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xianzhi-yu", "kind": "person", "label": "Xianzhi Yu", "url": "https://arxiv.org/abs/2410.16663", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:kang-zhao", "kind": "person", "label": "Kang Zhao", "url": "https://arxiv.org/abs/2410.16663", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:lu-hou", "kind": "person", "label": "Lu Hou", "url": "https://arxiv.org/abs/2410.16663", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zongyuan-zhan", "kind": "person", "label": "Zongyuan Zhan", "url": "https://arxiv.org/abs/2410.16663", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:stanislav-kamenev", "kind": "person", "label": "Stanislav Kamenev", "url": "https://arxiv.org/abs/2410.16663", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:han-bao", "kind": "person", "label": "Han Bao", "url": "https://arxiv.org/abs/2410.16663", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ting-hu", "kind": "person", "label": "Ting Hu", "url": "https://arxiv.org/abs/2410.16663", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.25306", "kind": "paper", "label": "QFlash: Bridging Quantization and Memory Efficiency in Vision Transformer Attention", "url": "https://arxiv.org/abs/2604.25306", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:sehyeon-oh", "kind": "person", "label": "Sehyeon Oh", "url": "https://arxiv.org/abs/2604.25306", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yongin-kwon", "kind": "person", "label": "Yongin Kwon", "url": "https://arxiv.org/abs/2604.25306", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jemin-lee", "kind": "person", "label": "Jemin Lee", "url": "https://arxiv.org/abs/2604.25306", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2402.07443", "kind": "paper", "label": "The I/O Complexity of Attention, or How Optimal is Flash Attention?", "url": "https://arxiv.org/abs/2402.07443", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:barna-saha", "kind": "person", "label": "Barna Saha", "url": "https://arxiv.org/abs/2402.07443", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:christopher-ye", "kind": "person", "label": "Christopher Ye", "url": "https://arxiv.org/abs/2402.07443", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2306.01160", "kind": "paper", "label": "Faster Causal Attention Over Large Sequences Through Sparse Flash Attention", "url": "https://arxiv.org/abs/2306.01160", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:matteo-pagliardini", "kind": "person", "label": "Matteo Pagliardini", "url": "https://arxiv.org/abs/2306.01160", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:daniele-paliotta", "kind": "person", "label": "Daniele Paliotta", "url": "https://arxiv.org/abs/2306.01160", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:martin-jaggi", "kind": "person", "label": "Martin Jaggi", "url": "https://arxiv.org/abs/2306.01160", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:fran-ois-fleuret", "kind": "person", "label": "Fran\u00e7ois Fleuret", "url": "https://arxiv.org/abs/2306.01160", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2310.03294", "kind": "paper", "label": "DISTFLASHATTN: Distributed Memory-efficient Attention for Long-context LLMs Training", "url": "https://arxiv.org/abs/2310.03294", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:dacheng-li", "kind": "person", "label": "Dacheng Li", "url": "https://arxiv.org/abs/2310.03294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:rulin-shao", "kind": "person", "label": "Rulin Shao", "url": "https://arxiv.org/abs/2310.03294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:anze-xie", "kind": "person", "label": "Anze Xie", "url": "https://arxiv.org/abs/2310.03294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:eric-p-xing", "kind": "person", "label": "Eric P. Xing", "url": "https://arxiv.org/abs/2310.03294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xuezhe-ma", "kind": "person", "label": "Xuezhe Ma", "url": "https://arxiv.org/abs/2310.03294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ion-stoica", "kind": "person", "label": "Ion Stoica", "url": "https://arxiv.org/abs/2310.03294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:joseph-e-gonzalez", "kind": "person", "label": "Joseph E. Gonzalez", "url": "https://arxiv.org/abs/2310.03294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hao-zhang", "kind": "person", "label": "Hao Zhang", "url": "https://arxiv.org/abs/2310.03294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2510.05175", "kind": "paper", "label": "Exact Causal Attention with 10% Fewer Operations", "url": "https://arxiv.org/abs/2510.05175", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:dmitry-rybin", "kind": "person", "label": "Dmitry Rybin", "url": "https://arxiv.org/abs/2510.05175", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yushun-zhang", "kind": "person", "label": "Yushun Zhang", "url": "https://arxiv.org/abs/2510.05175", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ding-tian", "kind": "person", "label": "Ding Tian", "url": "https://arxiv.org/abs/2510.05175", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhihang-lin", "kind": "person", "label": "Zhihang Lin", "url": "https://arxiv.org/abs/2510.05175", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhi-quan-luo", "kind": "person", "label": "Zhi-Quan Luo", "url": "https://arxiv.org/abs/2510.05175", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2601.16032", "kind": "paper", "label": "Sawtooth Wavefront Reordering: Enhanced CuTile FlashAttention on NVIDIA GB10", "url": "https://arxiv.org/abs/2601.16032", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yifan-zhu", "kind": "person", "label": "Yifan Zhu", "url": "https://arxiv.org/abs/2601.16032", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yekai-pan", "kind": "person", "label": "Yekai Pan", "url": "https://arxiv.org/abs/2601.16032", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chen-ding", "kind": "person", "label": "Chen Ding", "url": "https://arxiv.org/abs/2601.16032", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2412.05496", "kind": "paper", "label": "Flex Attention: A Programming Model for Generating Optimized Attention Kernels", "url": "https://arxiv.org/abs/2412.05496", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:juechu-dong", "kind": "person", "label": "Juechu Dong", "url": "https://arxiv.org/abs/2412.05496", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:boyuan-feng", "kind": "person", "label": "Boyuan Feng", "url": "https://arxiv.org/abs/2412.05496", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:driss-guessous", "kind": "person", "label": "Driss Guessous", "url": "https://arxiv.org/abs/2412.05496", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yanbo-liang", "kind": "person", "label": "Yanbo Liang", "url": "https://arxiv.org/abs/2412.05496", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:horace-he", "kind": "person", "label": "Horace He", "url": "https://arxiv.org/abs/2412.05496", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.15422", "kind": "paper", "label": "DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts", "url": "https://arxiv.org/abs/2605.15422", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:jiading-gai", "kind": "person", "label": "Jiading Gai", "url": "https://arxiv.org/abs/2605.15422", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shuai-zhang", "kind": "person", "label": "Shuai Zhang", "url": "https://arxiv.org/abs/2605.15422", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xiang-song", "kind": "person", "label": "Xiang Song", "url": "https://arxiv.org/abs/2605.15422", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:bernie-wang", "kind": "person", "label": "Bernie Wang", "url": "https://arxiv.org/abs/2605.15422", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:george-karypis", "kind": "person", "label": "George Karypis", "url": "https://arxiv.org/abs/2605.15422", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2501.06098", "kind": "paper", "label": "ELFATT: Efficient Linear Fast Attention for Vision Transformers", "url": "https://arxiv.org/abs/2501.06098", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:chong-wu", "kind": "person", "label": "Chong Wu", "url": "https://arxiv.org/abs/2501.06098", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:maolin-che", "kind": "person", "label": "Maolin Che", "url": "https://arxiv.org/abs/2501.06098", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:renjie-xu", "kind": "person", "label": "Renjie Xu", "url": "https://arxiv.org/abs/2501.06098", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhuoheng-ran", "kind": "person", "label": "Zhuoheng Ran", "url": "https://arxiv.org/abs/2501.06098", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hong-yan", "kind": "person", "label": "Hong Yan", "url": "https://arxiv.org/abs/2501.06098", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2404.07839", "kind": "paper", "label": "RecurrentGemma: Moving Past Transformers for Efficient Open Language Models", "url": "https://arxiv.org/abs/2404.07839", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:aleksandar-botev", "kind": "person", "label": "Aleksandar Botev", "url": "https://arxiv.org/abs/2404.07839", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:soham-de", "kind": "person", "label": "Soham De", "url": "https://arxiv.org/abs/2404.07839", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:samuel-l-smith", "kind": "person", "label": "Samuel L Smith", "url": "https://arxiv.org/abs/2404.07839", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:anushan-fernando", "kind": "person", "label": "Anushan Fernando", "url": "https://arxiv.org/abs/2404.07839", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:george-cristian-muraru", "kind": "person", "label": "George-Cristian Muraru", "url": "https://arxiv.org/abs/2404.07839", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ruba-haroun", "kind": "person", "label": "Ruba Haroun", "url": "https://arxiv.org/abs/2404.07839", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:leonard-berrada", "kind": "person", "label": "Leonard Berrada", "url": "https://arxiv.org/abs/2404.07839", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:razvan-pascanu", "kind": "person", "label": "Razvan Pascanu", "url": "https://arxiv.org/abs/2404.07839", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2603.21316", "kind": "paper", "label": "HELIX: Scaling Raw Audio Understanding with Hybrid Mamba-Attention Beyond the Quadratic Limit", "url": "https://arxiv.org/abs/2603.21316", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:khushiyant", "kind": "person", "label": "Khushiyant", "url": "https://arxiv.org/abs/2603.21316", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:param-thakkar", "kind": "person", "label": "Param Thakkar", "url": "https://arxiv.org/abs/2603.21316", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.01240", "kind": "paper", "label": "Rhamba: Region-Aware Hybrid Attention-Mamba Framework for Self-Supervised Learning in Resting-State fMRI", "url": "https://arxiv.org/abs/2605.01240", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:ruthwik-reddy-doodipala", "kind": "person", "label": "Ruthwik Reddy Doodipala", "url": "https://arxiv.org/abs/2605.01240", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:pankaj-pandey", "kind": "person", "label": "Pankaj Pandey", "url": "https://arxiv.org/abs/2605.01240", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:pratheek-eranki", "kind": "person", "label": "Pratheek Eranki", "url": "https://arxiv.org/abs/2605.01240", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:carolina-torres-rojas", "kind": "person", "label": "Carolina Torres-Rojas", "url": "https://arxiv.org/abs/2605.01240", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:manob-jyoti-saikia", "kind": "person", "label": "Manob Jyoti Saikia", "url": "https://arxiv.org/abs/2605.01240", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ranganatha-sitaram", "kind": "person", "label": "Ranganatha Sitaram", "url": "https://arxiv.org/abs/2605.01240", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2510.01958", "kind": "paper", "label": "Exploring Resolution-Wise Shared Attention in Hybrid Mamba-U-Nets for Improved Cross-Corpus Speech Enhancement", "url": "https://arxiv.org/abs/2510.01958", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:nikolai-lund-k-hne", "kind": "person", "label": "Nikolai Lund K\u00fchne", "url": "https://arxiv.org/abs/2510.01958", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jesper-jensen", "kind": "person", "label": "Jesper Jensen", "url": "https://arxiv.org/abs/2510.01958", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jan-stergaard", "kind": "person", "label": "Jan \u00d8stergaard", "url": "https://arxiv.org/abs/2510.01958", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zheng-hua-tan", "kind": "person", "label": "Zheng-Hua Tan", "url": "https://arxiv.org/abs/2510.01958", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2503.24067", "kind": "paper", "label": "TransMamba: A Sequence-Level Hybrid Transformer-Mamba Language Model", "url": "https://arxiv.org/abs/2503.24067", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yixing-li", "kind": "person", "label": "Yixing Li", "url": "https://arxiv.org/abs/2503.24067", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ruobing-xie", "kind": "person", "label": "Ruobing Xie", "url": "https://arxiv.org/abs/2503.24067", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhen-yang", "kind": "person", "label": "Zhen Yang", "url": "https://arxiv.org/abs/2503.24067", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xingwu-sun", "kind": "person", "label": "Xingwu Sun", "url": "https://arxiv.org/abs/2503.24067", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shuaipeng-li", "kind": "person", "label": "Shuaipeng Li", "url": "https://arxiv.org/abs/2503.24067", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:weidong-han", "kind": "person", "label": "Weidong Han", "url": "https://arxiv.org/abs/2503.24067", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhanhui-kang", "kind": "person", "label": "Zhanhui Kang", "url": "https://arxiv.org/abs/2503.24067", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2410.00871", "kind": "paper", "label": "MAP: Unleashing Hybrid Mamba-Transformer Vision Backbone's Potential with Masked Autoregressive Pretraining", "url": "https://arxiv.org/abs/2410.00871", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yunze-liu", "kind": "person", "label": "Yunze Liu", "url": "https://arxiv.org/abs/2410.00871", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:li-yi", "kind": "person", "label": "Li Yi", "url": "https://arxiv.org/abs/2410.00871", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.07552", "kind": "paper", "label": "VIMCAN: Visual-Inertial 3D Human Pose Estimation with Hybrid Mamba-Cross-Attention Network", "url": "https://arxiv.org/abs/2605.07552", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:zepeng-yang", "kind": "person", "label": "Zepeng Yang", "url": "https://arxiv.org/abs/2605.07552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:junxuan-bai", "kind": "person", "label": "Junxuan Bai", "url": "https://arxiv.org/abs/2605.07552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hao-li", "kind": "person", "label": "Hao Li", "url": "https://arxiv.org/abs/2605.07552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ju-dai", "kind": "person", "label": "Ju Dai", "url": "https://arxiv.org/abs/2605.07552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:junjun-pan", "kind": "person", "label": "Junjun Pan", "url": "https://arxiv.org/abs/2605.07552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yongfeng-yin", "kind": "person", "label": "Yongfeng Yin", "url": "https://arxiv.org/abs/2605.07552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:bin-li", "kind": "person", "label": "Bin Li", "url": "https://arxiv.org/abs/2605.07552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.14191", "kind": "paper", "label": "Attention to Mamba: A Recipe for Cross-Architecture Distillation", "url": "https://arxiv.org/abs/2604.14191", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:abhinav-moudgil", "kind": "person", "label": "Abhinav Moudgil", "url": "https://arxiv.org/abs/2604.14191", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ningyuan-huang", "kind": "person", "label": "Ningyuan Huang", "url": "https://arxiv.org/abs/2604.14191", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:eeshan-gunesh-dhekane", "kind": "person", "label": "Eeshan Gunesh Dhekane", "url": "https://arxiv.org/abs/2604.14191", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:pau-rodr-guez", "kind": "person", "label": "Pau Rodr\u00edguez", "url": "https://arxiv.org/abs/2604.14191", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:luca-zappella", "kind": "person", "label": "Luca Zappella", "url": "https://arxiv.org/abs/2604.14191", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:federico-danieli", "kind": "person", "label": "Federico Danieli", "url": "https://arxiv.org/abs/2604.14191", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2404.14757", "kind": "paper", "label": "SST: Multi-Scale Hybrid Mamba-Transformer Experts for Time Series Forecasting", "url": "https://arxiv.org/abs/2404.14757", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:xiongxiao-xu", "kind": "person", "label": "Xiongxiao Xu", "url": "https://arxiv.org/abs/2404.14757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:canyu-chen", "kind": "person", "label": "Canyu Chen", "url": "https://arxiv.org/abs/2404.14757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yueqing-liang", "kind": "person", "label": "Yueqing Liang", "url": "https://arxiv.org/abs/2404.14757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:baixiang-huang", "kind": "person", "label": "Baixiang Huang", "url": "https://arxiv.org/abs/2404.14757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:guangji-bai", "kind": "person", "label": "Guangji Bai", "url": "https://arxiv.org/abs/2404.14757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:liang-zhao", "kind": "person", "label": "Liang Zhao", "url": "https://arxiv.org/abs/2404.14757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:kai-shu", "kind": "person", "label": "Kai Shu", "url": "https://arxiv.org/abs/2404.14757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2501.18401", "kind": "paper", "label": "MatIR: A Hybrid Mamba-Transformer Image Restoration Model", "url": "https://arxiv.org/abs/2501.18401", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:juan-wen", "kind": "person", "label": "Juan Wen", "url": "https://arxiv.org/abs/2501.18401", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:weiyan-hou", "kind": "person", "label": "Weiyan Hou", "url": "https://arxiv.org/abs/2501.18401", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:luc-van-gool", "kind": "person", "label": "Luc Van Gool", "url": "https://arxiv.org/abs/2501.18401", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:radu-timofte", "kind": "person", "label": "Radu Timofte", "url": "https://arxiv.org/abs/2501.18401", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2505.17834", "kind": "paper", "label": "Hybrid Mamba-Transformer Decoder for Error-Correcting Codes", "url": "https://arxiv.org/abs/2505.17834", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:shy-el-cohen", "kind": "person", "label": "Shy-el Cohen", "url": "https://arxiv.org/abs/2505.17834", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yoni-choukroun", "kind": "person", "label": "Yoni Choukroun", "url": "https://arxiv.org/abs/2505.17834", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:eliya-nachmani", "kind": "person", "label": "Eliya Nachmani", "url": "https://arxiv.org/abs/2505.17834", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2408.15237", "kind": "paper", "label": "The Mamba in the Llama: Distilling and Accelerating Hybrid Models", "url": "https://arxiv.org/abs/2408.15237", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:junxiong-wang", "kind": "person", "label": "Junxiong Wang", "url": "https://arxiv.org/abs/2408.15237", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:avner-may", "kind": "person", "label": "Avner May", "url": "https://arxiv.org/abs/2408.15237", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:alexander-m-rush", "kind": "person", "label": "Alexander M. Rush", "url": "https://arxiv.org/abs/2408.15237", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2507.17296", "kind": "paper", "label": "PointLAMA: Latent Attention meets Mamba for Efficient Point Cloud Pretraining", "url": "https://arxiv.org/abs/2507.17296", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:xuanyu-lin", "kind": "person", "label": "Xuanyu Lin", "url": "https://arxiv.org/abs/2507.17296", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xiaona-zeng", "kind": "person", "label": "Xiaona Zeng", "url": "https://arxiv.org/abs/2507.17296", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xianwei-zheng", "kind": "person", "label": "Xianwei Zheng", "url": "https://arxiv.org/abs/2507.17296", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xutao-li", "kind": "person", "label": "Xutao Li", "url": "https://arxiv.org/abs/2507.17296", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.11131", "kind": "paper", "label": "USEMA: a Scalable Efficient Mamba Like Attention for Medical Image Segmentation", "url": "https://arxiv.org/abs/2605.11131", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:elisha-dayag", "kind": "person", "label": "Elisha Dayag", "url": "https://arxiv.org/abs/2605.11131", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:nhat-thanh-tran", "kind": "person", "label": "Nhat Thanh Tran", "url": "https://arxiv.org/abs/2605.11131", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jack-xin", "kind": "person", "label": "Jack Xin", "url": "https://arxiv.org/abs/2605.11131", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2409.19613", "kind": "paper", "label": "Hybrid Mamba for Few-Shot Segmentation", "url": "https://arxiv.org/abs/2409.19613", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:qianxiong-xu", "kind": "person", "label": "Qianxiong Xu", "url": "https://arxiv.org/abs/2409.19613", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xuanyi-liu", "kind": "person", "label": "Xuanyi Liu", "url": "https://arxiv.org/abs/2409.19613", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:lanyun-zhu", "kind": "person", "label": "Lanyun Zhu", "url": "https://arxiv.org/abs/2409.19613", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:guosheng-lin", "kind": "person", "label": "Guosheng Lin", "url": "https://arxiv.org/abs/2409.19613", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:cheng-long", "kind": "person", "label": "Cheng Long", "url": "https://arxiv.org/abs/2409.19613", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ziyue-li", "kind": "person", "label": "Ziyue Li", "url": "https://arxiv.org/abs/2409.19613", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:rui-zhao", "kind": "person", "label": "Rui Zhao", "url": "https://arxiv.org/abs/2409.19613", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2502.11178", "kind": "paper", "label": "DA-Mamba: Domain Adaptive Hybrid Mamba-Transformer Based One-Stage Object Detection", "url": "https://arxiv.org/abs/2502.11178", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:a-enes-doruk", "kind": "person", "label": "A. Enes Doruk", "url": "https://arxiv.org/abs/2502.11178", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hasan-f-ates", "kind": "person", "label": "Hasan F. Ates", "url": "https://arxiv.org/abs/2502.11178", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2601.02944", "kind": "paper", "label": "XLSR-MamBo: Scaling the Hybrid Mamba-Attention Backbone for Audio Deepfake Detection", "url": "https://arxiv.org/abs/2601.02944", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:kwok-ho-ng", "kind": "person", "label": "Kwok-Ho Ng", "url": "https://arxiv.org/abs/2601.02944", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tingting-song", "kind": "person", "label": "Tingting Song", "url": "https://arxiv.org/abs/2601.02944", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yongdong-wu", "kind": "person", "label": "Yongdong Wu", "url": "https://arxiv.org/abs/2601.02944", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhihua-xia", "kind": "person", "label": "Zhihua Xia", "url": "https://arxiv.org/abs/2601.02944", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2407.08083", "kind": "paper", "label": "MambaVision: A Hybrid Mamba-Transformer Vision Backbone", "url": "https://arxiv.org/abs/2407.08083", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:ali-hatamizadeh", "kind": "person", "label": "Ali Hatamizadeh", "url": "https://arxiv.org/abs/2407.08083", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jan-kautz", "kind": "person", "label": "Jan Kautz", "url": "https://arxiv.org/abs/2407.08083", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2407.13135", "kind": "paper", "label": "MLSA4Rec: Mamba Combined with Low-Rank Decomposed Self-Attention for Sequential Recommendation", "url": "https://arxiv.org/abs/2407.13135", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:jinzhao-su", "kind": "person", "label": "Jinzhao Su", "url": "https://arxiv.org/abs/2407.13135", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhenhua-huang", "kind": "person", "label": "Zhenhua Huang", "url": "https://arxiv.org/abs/2407.13135", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2507.00966", "kind": "paper", "label": "MambAttention: Mamba with Multi-Head Attention for Generalizable Single-Channel Speech Enhancement", "url": "https://arxiv.org/abs/2507.00966", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:paper:2602.12078", "kind": "paper", "label": "Tiny Recursive Reasoning with Mamba-2 Attention Hybrid", "url": "https://arxiv.org/abs/2602.12078", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:wenlong-wang", "kind": "person", "label": "Wenlong Wang", "url": "https://arxiv.org/abs/2602.12078", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:fergal-reid", "kind": "person", "label": "Fergal Reid", "url": "https://arxiv.org/abs/2602.12078", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2603.18031", "kind": "paper", "label": "InfoMamba: An Attention-Free Hybrid Mamba-Transformer Model", "url": "https://arxiv.org/abs/2603.18031", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:youjin-wang", "kind": "person", "label": "Youjin Wang", "url": "https://arxiv.org/abs/2603.18031", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jiaqiao-zhao", "kind": "person", "label": "Jiaqiao Zhao", "url": "https://arxiv.org/abs/2603.18031", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:rong-fu", "kind": "person", "label": "Rong Fu", "url": "https://arxiv.org/abs/2603.18031", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:run-zhou", "kind": "person", "label": "Run Zhou", "url": "https://arxiv.org/abs/2603.18031", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ruizhe-zhang", "kind": "person", "label": "Ruizhe Zhang", "url": "https://arxiv.org/abs/2603.18031", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jiani-liang", "kind": "person", "label": "Jiani Liang", "url": "https://arxiv.org/abs/2603.18031", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:suisuai-cao", "kind": "person", "label": "Suisuai Cao", "url": "https://arxiv.org/abs/2603.18031", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:feng-zhou", "kind": "person", "label": "Feng Zhou", "url": "https://arxiv.org/abs/2603.18031", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.22127", "kind": "paper", "label": "Where Should LoRA Go? Component-Type Placement in Hybrid Language Models", "url": "https://arxiv.org/abs/2604.22127", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:hector-borobia", "kind": "person", "label": "Hector Borobia", "url": "https://arxiv.org/abs/2604.22127", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:elies-segu-mas", "kind": "person", "label": "Elies Segu\u00ed-Mas", "url": "https://arxiv.org/abs/2604.22127", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:guillermina-tormo-carb", "kind": "person", "label": "Guillermina Tormo-Carb\u00f3", "url": "https://arxiv.org/abs/2604.22127", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2511.16595", "kind": "paper", "label": "TimeViper: A Hybrid Mamba-Transformer Vision-Language Model for Efficient Long Video Understanding", "url": "https://arxiv.org/abs/2511.16595", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:boshen-xu", "kind": "person", "label": "Boshen Xu", "url": "https://arxiv.org/abs/2511.16595", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zihan-xiao", "kind": "person", "label": "Zihan Xiao", "url": "https://arxiv.org/abs/2511.16595", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jiaze-li", "kind": "person", "label": "Jiaze Li", "url": "https://arxiv.org/abs/2511.16595", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jianzhong-ju", "kind": "person", "label": "Jianzhong Ju", "url": "https://arxiv.org/abs/2511.16595", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhenbo-luo", "kind": "person", "label": "Zhenbo Luo", "url": "https://arxiv.org/abs/2511.16595", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jian-luan", "kind": "person", "label": "Jian Luan", "url": "https://arxiv.org/abs/2511.16595", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:qin-jin", "kind": "person", "label": "Qin Jin", "url": "https://arxiv.org/abs/2511.16595", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2507.19931", "kind": "paper", "label": "MambaVesselNet++: A Hybrid CNN-Mamba Architecture for Medical Image Segmentation", "url": "https://arxiv.org/abs/2507.19931", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:qing-xu", "kind": "person", "label": "Qing Xu", "url": "https://arxiv.org/abs/2507.19931", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yanming-chen", "kind": "person", "label": "Yanming Chen", "url": "https://arxiv.org/abs/2507.19931", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yue-li", "kind": "person", "label": "Yue Li", "url": "https://arxiv.org/abs/2507.19931", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ziyu-liu", "kind": "person", "label": "Ziyu Liu", "url": "https://arxiv.org/abs/2507.19931", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhenye-lou", "kind": "person", "label": "Zhenye Lou", "url": "https://arxiv.org/abs/2507.19931", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xiangjian-he", "kind": "person", "label": "Xiangjian He", "url": "https://arxiv.org/abs/2507.19931", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.10581", "kind": "paper", "label": "Polygon-mamba: Retinal vessel segmentation using polygon scanning mamba and space-frequency collaborative attention", "url": "https://arxiv.org/abs/2605.10581", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yuanyuan-peng", "kind": "person", "label": "Yuanyuan Peng", "url": "https://arxiv.org/abs/2605.10581", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wen-li", "kind": "person", "label": "Wen Li", "url": "https://arxiv.org/abs/2605.10581", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2512.10353", "kind": "paper", "label": "Hybrid Transformer-Mamba for Weakly Supervised Volumetric Medical Segmentation", "url": "https://arxiv.org/abs/2512.10353", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yiheng-lyu", "kind": "person", "label": "Yiheng Lyu", "url": "https://arxiv.org/abs/2512.10353", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:lian-xu", "kind": "person", "label": "Lian Xu", "url": "https://arxiv.org/abs/2512.10353", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:coen-arrow", "kind": "person", "label": "Coen Arrow", "url": "https://arxiv.org/abs/2512.10353", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mohammed-bennamoun", "kind": "person", "label": "Mohammed Bennamoun", "url": "https://arxiv.org/abs/2512.10353", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:farid-boussaid", "kind": "person", "label": "Farid Boussaid", "url": "https://arxiv.org/abs/2512.10353", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:girish-dwivedi", "kind": "person", "label": "Girish Dwivedi", "url": "https://arxiv.org/abs/2512.10353", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2505.15703", "kind": "paper", "label": "HAMF: A Hybrid Attention-Mamba Framework for Joint Scene Context Understanding and Future Motion Representation Learning", "url": "https://arxiv.org/abs/2505.15703", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:xiaodong-mei", "kind": "person", "label": "Xiaodong Mei", "url": "https://arxiv.org/abs/2505.15703", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:sheng-wang", "kind": "person", "label": "Sheng Wang", "url": "https://arxiv.org/abs/2505.15703", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jie-cheng", "kind": "person", "label": "Jie Cheng", "url": "https://arxiv.org/abs/2505.15703", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yingbing-chen", "kind": "person", "label": "Yingbing Chen", "url": "https://arxiv.org/abs/2505.15703", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:dan-xu", "kind": "person", "label": "Dan Xu", "url": "https://arxiv.org/abs/2505.15703", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2511.17355", "kind": "paper", "label": "UAM: A Unified Attention-Mamba Backbone of Multimodal Framework for Tumor Cell Classification", "url": "https://arxiv.org/abs/2511.17355", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:taixi-chen", "kind": "person", "label": "Taixi Chen", "url": "https://arxiv.org/abs/2511.17355", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jingyun-chen", "kind": "person", "label": "Jingyun Chen", "url": "https://arxiv.org/abs/2511.17355", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:nancy-guo", "kind": "person", "label": "Nancy Guo", "url": "https://arxiv.org/abs/2511.17355", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2408.02922", "kind": "paper", "label": "Pose Magic: Efficient and Temporally Consistent Human Pose Estimation with a Hybrid Mamba-GCN Network", "url": "https://arxiv.org/abs/2408.02922", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:xinyi-zhang", "kind": "person", "label": "Xinyi Zhang", "url": "https://arxiv.org/abs/2408.02922", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:qiqi-bao", "kind": "person", "label": "Qiqi Bao", "url": "https://arxiv.org/abs/2408.02922", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:qinpeng-cui", "kind": "person", "label": "Qinpeng Cui", "url": "https://arxiv.org/abs/2408.02922", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wenming-yang", "kind": "person", "label": "Wenming Yang", "url": "https://arxiv.org/abs/2408.02922", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:qingmin-liao", "kind": "person", "label": "Qingmin Liao", "url": "https://arxiv.org/abs/2408.02922", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2509.24118", "kind": "paper", "label": "HyMaTE: A Hybrid Mamba and Transformer Model for EHR Representation Learning", "url": "https://arxiv.org/abs/2509.24118", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:md-mozaharul-mottalib", "kind": "person", "label": "Md Mozaharul Mottalib", "url": "https://arxiv.org/abs/2509.24118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:thao-ly-t-phan", "kind": "person", "label": "Thao-Ly T. Phan", "url": "https://arxiv.org/abs/2509.24118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:rahmatollah-beheshti", "kind": "person", "label": "Rahmatollah Beheshti", "url": "https://arxiv.org/abs/2509.24118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2408.12570", "kind": "paper", "label": "Jamba-1.5: Hybrid Transformer-Mamba Models at Scale", "url": "https://arxiv.org/abs/2408.12570", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:jamba-team", "kind": "person", "label": "Jamba Team", "url": "https://arxiv.org/abs/2408.12570", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:barak-lenz", "kind": "person", "label": "Barak Lenz", "url": "https://arxiv.org/abs/2408.12570", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:alan-arazi", "kind": "person", "label": "Alan Arazi", "url": "https://arxiv.org/abs/2408.12570", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:amir-bergman", "kind": "person", "label": "Amir Bergman", "url": "https://arxiv.org/abs/2408.12570", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:avshalom-manevich", "kind": "person", "label": "Avshalom Manevich", "url": "https://arxiv.org/abs/2408.12570", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:barak-peleg", "kind": "person", "label": "Barak Peleg", "url": "https://arxiv.org/abs/2408.12570", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ben-aviram", "kind": "person", "label": "Ben Aviram", "url": "https://arxiv.org/abs/2408.12570", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chen-almagor", "kind": "person", "label": "Chen Almagor", "url": "https://arxiv.org/abs/2408.12570", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2408.01627", "kind": "paper", "label": "JambaTalk: Speech-Driven 3D Talking Head Generation Based on Hybrid Transformer-Mamba Model", "url": "https://arxiv.org/abs/2408.01627", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:farzaneh-jafari", "kind": "person", "label": "Farzaneh Jafari", "url": "https://arxiv.org/abs/2408.01627", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:stefano-berretti", "kind": "person", "label": "Stefano Berretti", "url": "https://arxiv.org/abs/2408.01627", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:anup-basu", "kind": "person", "label": "Anup Basu", "url": "https://arxiv.org/abs/2408.01627", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2506.09507", "kind": "paper", "label": "TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding", "url": "https://arxiv.org/abs/2506.09507", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:bingheng-wu", "kind": "person", "label": "Bingheng Wu", "url": "https://arxiv.org/abs/2506.09507", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jingze-shi", "kind": "person", "label": "Jingze Shi", "url": "https://arxiv.org/abs/2506.09507", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yifan-wu", "kind": "person", "label": "Yifan Wu", "url": "https://arxiv.org/abs/2506.09507", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:nan-tang", "kind": "person", "label": "Nan Tang", "url": "https://arxiv.org/abs/2506.09507", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yuyu-luo", "kind": "person", "label": "Yuyu Luo", "url": "https://arxiv.org/abs/2506.09507", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2601.01972", "kind": "paper", "label": "Hidden State Poisoning Attacks against Mamba-based Language Models", "url": "https://arxiv.org/abs/2601.01972", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:alexandre-le-mercier", "kind": "person", "label": "Alexandre Le Mercier", "url": "https://arxiv.org/abs/2601.01972", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chris-develder", "kind": "person", "label": "Chris Develder", "url": "https://arxiv.org/abs/2601.01972", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:thomas-demeester", "kind": "person", "label": "Thomas Demeester", "url": "https://arxiv.org/abs/2601.01972", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2603.15589", "kind": "paper", "label": "LEXI: Lossless Exponent Coding for Efficient Inter-Chiplet Communication in Hybrid LLMs", "url": "https://arxiv.org/abs/2603.15589", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:miao-sun", "kind": "person", "label": "Miao Sun", "url": "https://arxiv.org/abs/2603.15589", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:alish-kanani", "kind": "person", "label": "Alish Kanani", "url": "https://arxiv.org/abs/2603.15589", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:kaushik-shroff", "kind": "person", "label": "Kaushik Shroff", "url": "https://arxiv.org/abs/2603.15589", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:umit-ogras", "kind": "person", "label": "Umit Ogras", "url": "https://arxiv.org/abs/2603.15589", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2606.02332", "kind": "paper", "label": "Forget Attention: Importance-Aware Attention Is All You Need", "url": "https://arxiv.org/abs/2606.02332", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:suhyeong-shin", "kind": "person", "label": "Suhyeong Shin", "url": "https://arxiv.org/abs/2606.02332", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yeongwook-yang", "kind": "person", "label": "Yeongwook Yang", "url": "https://arxiv.org/abs/2606.02332", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2506.18116", "kind": "paper", "label": "Mental Health Equity in LLMs: Leveraging Multi-Hop Question Answering to Detect Amplified and Silenced Perspectives", "url": "https://arxiv.org/abs/2506.18116", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:batool-haider", "kind": "person", "label": "Batool Haider", "url": "https://arxiv.org/abs/2506.18116", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:atmika-gorti", "kind": "person", "label": "Atmika Gorti", "url": "https://arxiv.org/abs/2506.18116", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:aman-chadha", "kind": "person", "label": "Aman Chadha", "url": "https://arxiv.org/abs/2506.18116", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:manas-gaur", "kind": "person", "label": "Manas Gaur", "url": "https://arxiv.org/abs/2506.18116", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2503.15521", "kind": "paper", "label": "From Divergence to Consensus: Evaluating the Role of Large Language Models in Facilitating Agreement through Adaptive Strategies", "url": "https://arxiv.org/abs/2503.15521", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:loukas-triantafyllopoulos", "kind": "person", "label": "Loukas Triantafyllopoulos", "url": "https://arxiv.org/abs/2503.15521", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:dimitris-kalles", "kind": "person", "label": "Dimitris Kalles", "url": "https://arxiv.org/abs/2503.15521", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.22416", "kind": "paper", "label": "Asymmetric Virtual Memory Paging for Hybrid Mamba-Transformer Inference", "url": "https://arxiv.org/abs/2605.22416", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:an-xuan-nguyen", "kind": "person", "label": "An Xuan Nguyen", "url": "https://arxiv.org/abs/2605.22416", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.22442", "kind": "paper", "label": "HubRouter: A Pluggable Sub-Quadratic Routing Primitive for Hybrid Sequence Models", "url": "https://arxiv.org/abs/2604.22442", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:abhinaba-basu", "kind": "person", "label": "Abhinaba Basu", "url": "https://arxiv.org/abs/2604.22442", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2503.18970", "kind": "paper", "label": "Advancing Intelligent Sequence Modeling: Evolution, Trade-offs, and Applications of State- Space Architectures from S4 to Mamba", "url": "https://arxiv.org/abs/2503.18970", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:shriyank-somvanshi", "kind": "person", "label": "Shriyank Somvanshi", "url": "https://arxiv.org/abs/2503.18970", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:md-monzurul-islam", "kind": "person", "label": "Md Monzurul Islam", "url": "https://arxiv.org/abs/2503.18970", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mahmuda-sultana-mimi", "kind": "person", "label": "Mahmuda Sultana Mimi", "url": "https://arxiv.org/abs/2503.18970", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:sazzad-bin-bashar-polock", "kind": "person", "label": "Sazzad Bin Bashar Polock", "url": "https://arxiv.org/abs/2503.18970", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:gaurab-chhetri", "kind": "person", "label": "Gaurab Chhetri", "url": "https://arxiv.org/abs/2503.18970", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:anandi-dutta", "kind": "person", "label": "Anandi Dutta", "url": "https://arxiv.org/abs/2503.18970", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:amir-rafe", "kind": "person", "label": "Amir Rafe", "url": "https://arxiv.org/abs/2503.18970", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:subasish-das", "kind": "person", "label": "Subasish Das", "url": "https://arxiv.org/abs/2503.18970", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2407.06324", "kind": "paper", "label": "B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory", "url": "https://arxiv.org/abs/2407.06324", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:luca-zancato", "kind": "person", "label": "Luca Zancato", "url": "https://arxiv.org/abs/2407.06324", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:arjun-seshadri", "kind": "person", "label": "Arjun Seshadri", "url": "https://arxiv.org/abs/2407.06324", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yonatan-dukler", "kind": "person", "label": "Yonatan Dukler", "url": "https://arxiv.org/abs/2407.06324", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:aditya-golatkar", "kind": "person", "label": "Aditya Golatkar", "url": "https://arxiv.org/abs/2407.06324", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yantao-shen", "kind": "person", "label": "Yantao Shen", "url": "https://arxiv.org/abs/2407.06324", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:benjamin-bowman", "kind": "person", "label": "Benjamin Bowman", "url": "https://arxiv.org/abs/2407.06324", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:matthew-trager", "kind": "person", "label": "Matthew Trager", "url": "https://arxiv.org/abs/2407.06324", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:alessandro-achille", "kind": "person", "label": "Alessandro Achille", "url": "https://arxiv.org/abs/2407.06324", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2510.19861", "kind": "paper", "label": "Some Attention is All You Need for Retrieval", "url": "https://arxiv.org/abs/2510.19861", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:felix-michalak", "kind": "person", "label": "Felix Michalak", "url": "https://arxiv.org/abs/2510.19861", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:steven-abreu", "kind": "person", "label": "Steven Abreu", "url": "https://arxiv.org/abs/2510.19861", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2607.03482", "kind": "paper", "label": "Lacuna Inc. at SemEval-2026 Task 4: Structurally Gated State-Space Models for Disentangling Narrative Similarity", "url": "https://arxiv.org/abs/2607.03482", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:aleksey-kudelya", "kind": "person", "label": "Aleksey Kudelya", "url": "https://arxiv.org/abs/2607.03482", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:rafif-alshawi", "kind": "person", "label": "Rafif Alshawi", "url": "https://arxiv.org/abs/2607.03482", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:alexander-shirnin", "kind": "person", "label": "Alexander Shirnin", "url": "https://arxiv.org/abs/2607.03482", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2603.01288", "kind": "paper", "label": "Efficient Extractive Summarization with MAMBA-Transformer Hybrids for Low-Resource Scenarios", "url": "https://arxiv.org/abs/2603.01288", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:nisrine-ait-khayi", "kind": "person", "label": "Nisrine Ait Khayi", "url": "https://arxiv.org/abs/2603.01288", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2502.06617", "kind": "paper", "label": "Scaling Multi-Document Event Summarization: Evaluating Compression vs. Full-Text Approaches", "url": "https://arxiv.org/abs/2502.06617", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:adithya-pratapa", "kind": "person", "label": "Adithya Pratapa", "url": "https://arxiv.org/abs/2502.06617", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:teruko-mitamura", "kind": "person", "label": "Teruko Mitamura", "url": "https://arxiv.org/abs/2502.06617", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.16424", "kind": "paper", "label": "Safety, Security, and Cognitive Risks in State-Space Models: A Systematic Threat Analysis with Spectral, Stateful, and Capacity Attacks", "url": "https://arxiv.org/abs/2604.16424", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:manoj-parmar", "kind": "person", "label": "Manoj Parmar", "url": "https://arxiv.org/abs/2604.16424", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.14825", "kind": "paper", "label": "Nautilus: An Auto-Scheduling Tensor Compiler for Efficient Tiled GPU Kernels", "url": "https://arxiv.org/abs/2604.14825", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yifan-zhao", "kind": "person", "label": "Yifan Zhao", "url": "https://arxiv.org/abs/2604.14825", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yuchen-yang", "kind": "person", "label": "Yuchen Yang", "url": "https://arxiv.org/abs/2604.14825", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:matei-budiu", "kind": "person", "label": "Matei Budiu", "url": "https://arxiv.org/abs/2604.14825", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:sasa-misailovic", "kind": "person", "label": "Sasa Misailovic", "url": "https://arxiv.org/abs/2604.14825", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2510.21956", "kind": "paper", "label": "Transformer Based Linear Attention with Optimized GPU Kernel Implementation", "url": "https://arxiv.org/abs/2510.21956", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:armin-gerami", "kind": "person", "label": "Armin Gerami", "url": "https://arxiv.org/abs/2510.21956", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ramani-duraiswami", "kind": "person", "label": "Ramani Duraiswami", "url": "https://arxiv.org/abs/2510.21956", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2606.20005", "kind": "paper", "label": "StreamKL: Fast and Memory-Efficient KL Divergence for Boosting Attention Distillation", "url": "https://arxiv.org/abs/2606.20005", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:guangda-liu", "kind": "person", "label": "Guangda Liu", "url": "https://arxiv.org/abs/2606.20005", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yiquan-wang", "kind": "person", "label": "Yiquan Wang", "url": "https://arxiv.org/abs/2606.20005", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chengwei-li", "kind": "person", "label": "Chengwei Li", "url": "https://arxiv.org/abs/2606.20005", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wenhao-chen", "kind": "person", "label": "Wenhao Chen", "url": "https://arxiv.org/abs/2606.20005", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jing-lin", "kind": "person", "label": "Jing Lin", "url": "https://arxiv.org/abs/2606.20005", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yiwu-yao", "kind": "person", "label": "Yiwu Yao", "url": "https://arxiv.org/abs/2606.20005", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:danning-ke", "kind": "person", "label": "Danning Ke", "url": "https://arxiv.org/abs/2606.20005", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wenchao-ding", "kind": "person", "label": "Wenchao Ding", "url": "https://arxiv.org/abs/2606.20005", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.12110", "kind": "paper", "label": "AB-Sparse: Sparse Attention with Adaptive Block Size for Accurate and Efficient Long-Context Inference", "url": "https://arxiv.org/abs/2605.12110", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:di-liu", "kind": "person", "label": "Di Liu", "url": "https://arxiv.org/abs/2605.12110", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ruitian-wang", "kind": "person", "label": "Ruitian Wang", "url": "https://arxiv.org/abs/2605.12110", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chen-chen", "kind": "person", "label": "Chen Chen", "url": "https://arxiv.org/abs/2605.12110", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mingliang-gong", "kind": "person", "label": "Mingliang Gong", "url": "https://arxiv.org/abs/2605.12110", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yongjie-yuan", "kind": "person", "label": "Yongjie Yuan", "url": "https://arxiv.org/abs/2605.12110", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:han-zhao", "kind": "person", "label": "Han Zhao", "url": "https://arxiv.org/abs/2605.12110", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yu-feng", "kind": "person", "label": "Yu Feng", "url": "https://arxiv.org/abs/2605.12110", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:quan-chen", "kind": "person", "label": "Quan Chen", "url": "https://arxiv.org/abs/2605.12110", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2607.03012", "kind": "paper", "label": "HyperVAttention: Efficient Sparse Attention with Spatio-Temporal Clustering for Video Diffusion", "url": "https://arxiv.org/abs/2607.03012", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:dongyeun-lee", "kind": "person", "label": "Dongyeun Lee", "url": "https://arxiv.org/abs/2607.03012", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:amir-zandieh", "kind": "person", "label": "Amir Zandieh", "url": "https://arxiv.org/abs/2607.03012", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:vahab-mirrokni", "kind": "person", "label": "Vahab Mirrokni", "url": "https://arxiv.org/abs/2607.03012", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:junmo-kim", "kind": "person", "label": "Junmo Kim", "url": "https://arxiv.org/abs/2607.03012", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:insu-han", "kind": "person", "label": "Insu Han", "url": "https://arxiv.org/abs/2607.03012", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2509.24006", "kind": "paper", "label": "SLA: Beyond Sparsity in Diffusion Transformers via Fine-Tunable Sparse-Linear Attention", "url": "https://arxiv.org/abs/2509.24006", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:jintao-zhang", "kind": "person", "label": "Jintao Zhang", "url": "https://arxiv.org/abs/2509.24006", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:haoxu-wang", "kind": "person", "label": "Haoxu Wang", "url": "https://arxiv.org/abs/2509.24006", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:kai-jiang", "kind": "person", "label": "Kai Jiang", "url": "https://arxiv.org/abs/2509.24006", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:kaiwen-zheng", "kind": "person", "label": "Kaiwen Zheng", "url": "https://arxiv.org/abs/2509.24006", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:haocheng-xi", "kind": "person", "label": "Haocheng Xi", "url": "https://arxiv.org/abs/2509.24006", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ziteng-wang", "kind": "person", "label": "Ziteng Wang", "url": "https://arxiv.org/abs/2509.24006", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hongzhou-zhu", "kind": "person", "label": "Hongzhou Zhu", "url": "https://arxiv.org/abs/2509.24006", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2507.04239", "kind": "paper", "label": "Scaling Context Requires Rethinking Attention", "url": "https://arxiv.org/abs/2507.04239", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:carles-gelada", "kind": "person", "label": "Carles Gelada", "url": "https://arxiv.org/abs/2507.04239", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jacob-buckman", "kind": "person", "label": "Jacob Buckman", "url": "https://arxiv.org/abs/2507.04239", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:sean-zhang", "kind": "person", "label": "Sean Zhang", "url": "https://arxiv.org/abs/2507.04239", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:txus-bach", "kind": "person", "label": "Txus Bach", "url": "https://arxiv.org/abs/2507.04239", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.05023", "kind": "paper", "label": "CuBridge: An LLM-Based Framework for Understanding and Reconstructing High-Performance Attention Kernels", "url": "https://arxiv.org/abs/2605.05023", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:xing-ma", "kind": "person", "label": "Xing Ma", "url": "https://arxiv.org/abs/2605.05023", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yangjie-zhou", "kind": "person", "label": "Yangjie Zhou", "url": "https://arxiv.org/abs/2605.05023", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wu-sun", "kind": "person", "label": "Wu Sun", "url": "https://arxiv.org/abs/2605.05023", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zihan-liu", "kind": "person", "label": "Zihan Liu", "url": "https://arxiv.org/abs/2605.05023", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jingwen-leng", "kind": "person", "label": "Jingwen Leng", "url": "https://arxiv.org/abs/2605.05023", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yun-lin", "kind": "person", "label": "Yun Lin", "url": "https://arxiv.org/abs/2605.05023", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shixuan-sun", "kind": "person", "label": "Shixuan Sun", "url": "https://arxiv.org/abs/2605.05023", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:minyi-guo", "kind": "person", "label": "Minyi Guo", "url": "https://arxiv.org/abs/2605.05023", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.27124", "kind": "paper", "label": "Better Models, Faster Training: Sigmoid Attention for single-cell Foundation Models", "url": "https://arxiv.org/abs/2604.27124", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:vijay-sadashivaiah", "kind": "person", "label": "Vijay Sadashivaiah", "url": "https://arxiv.org/abs/2604.27124", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:georgios-dasoulas", "kind": "person", "label": "Georgios Dasoulas", "url": "https://arxiv.org/abs/2604.27124", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:judith-mueller", "kind": "person", "label": "Judith Mueller", "url": "https://arxiv.org/abs/2604.27124", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:soumya-ghosh", "kind": "person", "label": "Soumya Ghosh", "url": "https://arxiv.org/abs/2604.27124", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2511.02132", "kind": "paper", "label": "Optimizing Attention on GPUs by Exploiting GPU Architectural NUMA Effects", "url": "https://arxiv.org/abs/2511.02132", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:mansi-choudhary", "kind": "person", "label": "Mansi Choudhary", "url": "https://arxiv.org/abs/2511.02132", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:karthik-sangaiah", "kind": "person", "label": "Karthik Sangaiah", "url": "https://arxiv.org/abs/2511.02132", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:sonali-singh", "kind": "person", "label": "Sonali Singh", "url": "https://arxiv.org/abs/2511.02132", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:muhammad-osama", "kind": "person", "label": "Muhammad Osama", "url": "https://arxiv.org/abs/2511.02132", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:lisa-wu-wills", "kind": "person", "label": "Lisa Wu Wills", "url": "https://arxiv.org/abs/2511.02132", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ganesh-dasika", "kind": "person", "label": "Ganesh Dasika", "url": "https://arxiv.org/abs/2511.02132", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2410.18038", "kind": "paper", "label": "POD-Attention: Unlocking Full Prefill-Decode Overlap for Faster LLM Inference", "url": "https://arxiv.org/abs/2410.18038", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:aditya-k-kamath", "kind": "person", "label": "Aditya K Kamath", "url": "https://arxiv.org/abs/2410.18038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ramya-prabhu", "kind": "person", "label": "Ramya Prabhu", "url": "https://arxiv.org/abs/2410.18038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jayashree-mohan", "kind": "person", "label": "Jayashree Mohan", "url": "https://arxiv.org/abs/2410.18038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:simon-peter", "kind": "person", "label": "Simon Peter", "url": "https://arxiv.org/abs/2410.18038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ramachandran-ramjee", "kind": "person", "label": "Ramachandran Ramjee", "url": "https://arxiv.org/abs/2410.18038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ashish-panwar", "kind": "person", "label": "Ashish Panwar", "url": "https://arxiv.org/abs/2410.18038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2012.02030", "kind": "paper", "label": "Data-Informed Global Sparseness in Attention Mechanisms for Deep Neural Networks", "url": "https://arxiv.org/abs/2012.02030", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:ileana-rugina", "kind": "person", "label": "Ileana Rugina", "url": "https://arxiv.org/abs/2012.02030", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:rumen-dangovski", "kind": "person", "label": "Rumen Dangovski", "url": "https://arxiv.org/abs/2012.02030", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:li-jing", "kind": "person", "label": "Li Jing", "url": "https://arxiv.org/abs/2012.02030", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:preslav-nakov", "kind": "person", "label": "Preslav Nakov", "url": "https://arxiv.org/abs/2012.02030", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:marin-solja-i", "kind": "person", "label": "Marin Solja\u010di\u0107", "url": "https://arxiv.org/abs/2012.02030", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.21221", "kind": "paper", "label": "Sparse Forcing: Native Trainable Sparse Attention for Real-time Autoregressive Diffusion Video Generation", "url": "https://arxiv.org/abs/2604.21221", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:boxun-xu", "kind": "person", "label": "Boxun Xu", "url": "https://arxiv.org/abs/2604.21221", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yuming-du", "kind": "person", "label": "Yuming Du", "url": "https://arxiv.org/abs/2604.21221", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zichang-liu", "kind": "person", "label": "Zichang Liu", "url": "https://arxiv.org/abs/2604.21221", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:siyu-yang", "kind": "person", "label": "Siyu Yang", "url": "https://arxiv.org/abs/2604.21221", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ziyang-jiang", "kind": "person", "label": "Ziyang Jiang", "url": "https://arxiv.org/abs/2604.21221", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:siqi-yan", "kind": "person", "label": "Siqi Yan", "url": "https://arxiv.org/abs/2604.21221", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:rajasi-saha", "kind": "person", "label": "Rajasi Saha", "url": "https://arxiv.org/abs/2604.21221", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:albert-pumarola", "kind": "person", "label": "Albert Pumarola", "url": "https://arxiv.org/abs/2604.21221", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2507.09071", "kind": "paper", "label": "BlindSight: Harnessing Sparsity for Efficient Vision-Language Models", "url": "https://arxiv.org/abs/2507.09071", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:tharun-adithya-srikrishnan", "kind": "person", "label": "Tharun Adithya Srikrishnan", "url": "https://arxiv.org/abs/2507.09071", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:deval-shah", "kind": "person", "label": "Deval Shah", "url": "https://arxiv.org/abs/2507.09071", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:timothy-hein", "kind": "person", "label": "Timothy Hein", "url": "https://arxiv.org/abs/2507.09071", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ahmed-hasssan", "kind": "person", "label": "Ahmed Hasssan", "url": "https://arxiv.org/abs/2507.09071", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:stephen-youn", "kind": "person", "label": "Stephen Youn", "url": "https://arxiv.org/abs/2507.09071", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:steven-k-reinhardt", "kind": "person", "label": "Steven K. Reinhardt", "url": "https://arxiv.org/abs/2507.09071", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.20813", "kind": "paper", "label": "PulseCol: Periodically Refreshed Column-Sparse Attention for Accelerating Diffusion Language Models", "url": "https://arxiv.org/abs/2605.20813", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yanyi-lyu", "kind": "person", "label": "Yanyi Lyu", "url": "https://arxiv.org/abs/2605.20813", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:letian-chen", "kind": "person", "label": "Letian Chen", "url": "https://arxiv.org/abs/2605.20813", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:futing-sun", "kind": "person", "label": "Futing Sun", "url": "https://arxiv.org/abs/2605.20813", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:miao-zhang", "kind": "person", "label": "Miao Zhang", "url": "https://arxiv.org/abs/2605.20813", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:weili-guan", "kind": "person", "label": "Weili Guan", "url": "https://arxiv.org/abs/2605.20813", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:liqiang-nie", "kind": "person", "label": "Liqiang Nie", "url": "https://arxiv.org/abs/2605.20813", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2407.02490", "kind": "paper", "label": "MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention", "url": "https://arxiv.org/abs/2407.02490", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:huiqiang-jiang", "kind": "person", "label": "Huiqiang Jiang", "url": "https://arxiv.org/abs/2407.02490", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yucheng-li", "kind": "person", "label": "Yucheng Li", "url": "https://arxiv.org/abs/2407.02490", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chengruidong-zhang", "kind": "person", "label": "Chengruidong Zhang", "url": "https://arxiv.org/abs/2407.02490", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:qianhui-wu", "kind": "person", "label": "Qianhui Wu", "url": "https://arxiv.org/abs/2407.02490", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xufang-luo", "kind": "person", "label": "Xufang Luo", "url": "https://arxiv.org/abs/2407.02490", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:surin-ahn", "kind": "person", "label": "Surin Ahn", "url": "https://arxiv.org/abs/2407.02490", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhenhua-han", "kind": "person", "label": "Zhenhua Han", "url": "https://arxiv.org/abs/2407.02490", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:amir-h-abdi", "kind": "person", "label": "Amir H. Abdi", "url": "https://arxiv.org/abs/2407.02490", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2504.16083", "kind": "paper", "label": "MMInference: Accelerating Pre-filling for Long-Context VLMs via Modality-Aware Permutation Sparse Attention", "url": "https://arxiv.org/abs/2504.16083", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:dongsheng-li", "kind": "person", "label": "Dongsheng Li", "url": "https://arxiv.org/abs/2504.16083", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2512.07884", "kind": "paper", "label": "GSPN-2: Efficient Parallel Sequence Modeling", "url": "https://arxiv.org/abs/2512.07884", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:hongjun-wang", "kind": "person", "label": "Hongjun Wang", "url": "https://arxiv.org/abs/2512.07884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yitong-jiang", "kind": "person", "label": "Yitong Jiang", "url": "https://arxiv.org/abs/2512.07884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:collin-mccarthy", "kind": "person", "label": "Collin McCarthy", "url": "https://arxiv.org/abs/2512.07884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:david-wehr", "kind": "person", "label": "David Wehr", "url": "https://arxiv.org/abs/2512.07884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hanrong-ye", "kind": "person", "label": "Hanrong Ye", "url": "https://arxiv.org/abs/2512.07884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xinhao-li", "kind": "person", "label": "Xinhao Li", "url": "https://arxiv.org/abs/2512.07884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ka-chun-cheung", "kind": "person", "label": "Ka Chun Cheung", "url": "https://arxiv.org/abs/2512.07884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wonmin-byeon", "kind": "person", "label": "Wonmin Byeon", "url": "https://arxiv.org/abs/2512.07884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2603.02883", "kind": "paper", "label": "SemanticDialect: Semantic-Aware Mixed-Format Quantization for Video Diffusion Transformers", "url": "https://arxiv.org/abs/2603.02883", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:wonsuk-jang", "kind": "person", "label": "Wonsuk Jang", "url": "https://arxiv.org/abs/2603.02883", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:thierry-tambe", "kind": "person", "label": "Thierry Tambe", "url": "https://arxiv.org/abs/2603.02883", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.23466", "kind": "paper", "label": "Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs", "url": "https://arxiv.org/abs/2604.23466", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:divakar-kumar-yadav", "kind": "person", "label": "Divakar Kumar Yadav", "url": "https://arxiv.org/abs/2604.23466", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tian-zhao", "kind": "person", "label": "Tian Zhao", "url": "https://arxiv.org/abs/2604.23466", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:deepak-kumar", "kind": "person", "label": "Deepak Kumar", "url": "https://arxiv.org/abs/2604.23466", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2601.13345", "kind": "paper", "label": "FlipFlop: A Static Analysis-based Energy Optimization Framework for GPU Kernels", "url": "https://arxiv.org/abs/2601.13345", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:saurabhsingh-rajput", "kind": "person", "label": "Saurabhsingh Rajput", "url": "https://arxiv.org/abs/2601.13345", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:alexander-brandt", "kind": "person", "label": "Alexander Brandt", "url": "https://arxiv.org/abs/2601.13345", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:vadim-elisseev", "kind": "person", "label": "Vadim Elisseev", "url": "https://arxiv.org/abs/2601.13345", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tushar-sharma", "kind": "person", "label": "Tushar Sharma", "url": "https://arxiv.org/abs/2601.13345", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:1010.1482", "kind": "paper", "label": "Treecode and fast multipole method for N-body simulation with CUDA", "url": "https://arxiv.org/abs/1010.1482", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:rio-yokota", "kind": "person", "label": "Rio Yokota", "url": "https://arxiv.org/abs/1010.1482", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:lorena-barba", "kind": "person", "label": "Lorena Barba", "url": "https://arxiv.org/abs/1010.1482", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2410.24169", "kind": "paper", "label": "The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains", "url": "https://arxiv.org/abs/2410.24169", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:eric-qu", "kind": "person", "label": "Eric Qu", "url": "https://arxiv.org/abs/2410.24169", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:aditi-s-krishnapriyan", "kind": "person", "label": "Aditi S. Krishnapriyan", "url": "https://arxiv.org/abs/2410.24169", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2505.14884", "kind": "paper", "label": "Polar Sparsity: High Throughput Batched LLM Inferencing with Scalable Contextual Sparsity", "url": "https://arxiv.org/abs/2505.14884", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:susav-shrestha", "kind": "person", "label": "Susav Shrestha", "url": "https://arxiv.org/abs/2505.14884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:brad-settlemyer", "kind": "person", "label": "Brad Settlemyer", "url": "https://arxiv.org/abs/2505.14884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:nikoli-dryden", "kind": "person", "label": "Nikoli Dryden", "url": "https://arxiv.org/abs/2505.14884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:narasimha-reddy", "kind": "person", "label": "Narasimha Reddy", "url": "https://arxiv.org/abs/2505.14884", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.31500", "kind": "paper", "label": "On Efficient Scaling of GNNs via IO-Aware Layers Implementations", "url": "https://arxiv.org/abs/2605.31500", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:daria-fomina", "kind": "person", "label": "Daria Fomina", "url": "https://arxiv.org/abs/2605.31500", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:daniil-krasylnikov", "kind": "person", "label": "Daniil Krasylnikov", "url": "https://arxiv.org/abs/2605.31500", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:alexey-boykov", "kind": "person", "label": "Alexey Boykov", "url": "https://arxiv.org/abs/2605.31500", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:andrey-dolgovyazov", "kind": "person", "label": "Andrey Dolgovyazov", "url": "https://arxiv.org/abs/2605.31500", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:vyacheslav-zhdanovskiy", "kind": "person", "label": "Vyacheslav Zhdanovskiy", "url": "https://arxiv.org/abs/2605.31500", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:fedor-velikonivtsev", "kind": "person", "label": "Fedor Velikonivtsev", "url": "https://arxiv.org/abs/2605.31500", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.19269", "kind": "paper", "label": "CODA: Rewriting Transformer Blocks as GEMM-Epilogue Programs", "url": "https://arxiv.org/abs/2605.19269", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:han-guo", "kind": "person", "label": "Han Guo", "url": "https://arxiv.org/abs/2605.19269", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jack-zhang", "kind": "person", "label": "Jack Zhang", "url": "https://arxiv.org/abs/2605.19269", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:arjun-menon", "kind": "person", "label": "Arjun Menon", "url": "https://arxiv.org/abs/2605.19269", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yoon-kim", "kind": "person", "label": "Yoon Kim", "url": "https://arxiv.org/abs/2605.19269", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2407.21118", "kind": "paper", "label": "Palu: Compressing KV-Cache with Low-Rank Projection", "url": "https://arxiv.org/abs/2407.21118", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:chi-chih-chang", "kind": "person", "label": "Chi-Chih Chang", "url": "https://arxiv.org/abs/2407.21118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wei-cheng-lin", "kind": "person", "label": "Wei-Cheng Lin", "url": "https://arxiv.org/abs/2407.21118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chien-yu-lin", "kind": "person", "label": "Chien-Yu Lin", "url": "https://arxiv.org/abs/2407.21118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chong-yan-chen", "kind": "person", "label": "Chong-Yan Chen", "url": "https://arxiv.org/abs/2407.21118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yu-fang-hu", "kind": "person", "label": "Yu-Fang Hu", "url": "https://arxiv.org/abs/2407.21118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:pei-shuo-wang", "kind": "person", "label": "Pei-Shuo Wang", "url": "https://arxiv.org/abs/2407.21118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ning-chi-huang", "kind": "person", "label": "Ning-Chi Huang", "url": "https://arxiv.org/abs/2407.21118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:luis-ceze", "kind": "person", "label": "Luis Ceze", "url": "https://arxiv.org/abs/2407.21118", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2308.00442", "kind": "paper", "label": "FLatten Transformer: Vision Transformer using Focused Linear Attention", "url": "https://arxiv.org/abs/2308.00442", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:dongchen-han", "kind": "person", "label": "Dongchen Han", "url": "https://arxiv.org/abs/2308.00442", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xuran-pan", "kind": "person", "label": "Xuran Pan", "url": "https://arxiv.org/abs/2308.00442", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yizeng-han", "kind": "person", "label": "Yizeng Han", "url": "https://arxiv.org/abs/2308.00442", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shiji-song", "kind": "person", "label": "Shiji Song", "url": "https://arxiv.org/abs/2308.00442", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:gao-huang", "kind": "person", "label": "Gao Huang", "url": "https://arxiv.org/abs/2308.00442", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2411.16170", "kind": "paper", "label": "CARE Transformer: Mobile-Friendly Linear Visual Transformer via Decoupled Dual Interaction", "url": "https://arxiv.org/abs/2411.16170", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yuan-zhou", "kind": "person", "label": "Yuan Zhou", "url": "https://arxiv.org/abs/2411.16170", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:qingshan-xu", "kind": "person", "label": "Qingshan Xu", "url": "https://arxiv.org/abs/2411.16170", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jiequan-cui", "kind": "person", "label": "Jiequan Cui", "url": "https://arxiv.org/abs/2411.16170", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:junbao-zhou", "kind": "person", "label": "Junbao Zhou", "url": "https://arxiv.org/abs/2411.16170", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jing-zhang", "kind": "person", "label": "Jing Zhang", "url": "https://arxiv.org/abs/2411.16170", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:richang-hong", "kind": "person", "label": "Richang Hong", "url": "https://arxiv.org/abs/2411.16170", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hanwang-zhang", "kind": "person", "label": "Hanwang Zhang", "url": "https://arxiv.org/abs/2411.16170", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2410.22710", "kind": "paper", "label": "LoFLAT: Local Feature Matching using Focused Linear Attention Transformer", "url": "https://arxiv.org/abs/2410.22710", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:naijian-cao", "kind": "person", "label": "Naijian Cao", "url": "https://arxiv.org/abs/2410.22710", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:renjie-he", "kind": "person", "label": "Renjie He", "url": "https://arxiv.org/abs/2410.22710", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yuchao-dai", "kind": "person", "label": "Yuchao Dai", "url": "https://arxiv.org/abs/2410.22710", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mingyi-he", "kind": "person", "label": "Mingyi He", "url": "https://arxiv.org/abs/2410.22710", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2206.10552", "kind": "paper", "label": "Vicinity Vision Transformer", "url": "https://arxiv.org/abs/2206.10552", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:weixuan-sun", "kind": "person", "label": "Weixuan Sun", "url": "https://arxiv.org/abs/2206.10552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhen-qin", "kind": "person", "label": "Zhen Qin", "url": "https://arxiv.org/abs/2206.10552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hui-deng", "kind": "person", "label": "Hui Deng", "url": "https://arxiv.org/abs/2206.10552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jianyuan-wang", "kind": "person", "label": "Jianyuan Wang", "url": "https://arxiv.org/abs/2206.10552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:kaihao-zhang", "kind": "person", "label": "Kaihao Zhang", "url": "https://arxiv.org/abs/2206.10552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:nick-barnes", "kind": "person", "label": "Nick Barnes", "url": "https://arxiv.org/abs/2206.10552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:stan-birchfield", "kind": "person", "label": "Stan Birchfield", "url": "https://arxiv.org/abs/2206.10552", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2501.16182", "kind": "paper", "label": "The Linear Attention Resurrection in Vision Transformer", "url": "https://arxiv.org/abs/2501.16182", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:chuanyang-zheng", "kind": "person", "label": "Chuanyang Zheng", "url": "https://arxiv.org/abs/2501.16182", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2508.20407", "kind": "paper", "label": "Rethinking Transformer Connectivity: TLinFormer, A Path to Exact, Full Context-Aware Linear Attention", "url": "https://arxiv.org/abs/2508.20407", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:zhongpan-tang", "kind": "person", "label": "Zhongpan Tang", "url": "https://arxiv.org/abs/2508.20407", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.10064", "kind": "paper", "label": "On The Application of Linear Attention in Multimodal Transformers", "url": "https://arxiv.org/abs/2604.10064", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:seyedehanita-madani", "kind": "person", "label": "Seyedehanita Madani", "url": "https://arxiv.org/abs/2604.10064", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2506.09316", "kind": "paper", "label": "On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention", "url": "https://arxiv.org/abs/2506.09316", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yeonju-ro", "kind": "person", "label": "Yeonju Ro", "url": "https://arxiv.org/abs/2506.09316", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhenyu-zhang", "kind": "person", "label": "Zhenyu Zhang", "url": "https://arxiv.org/abs/2506.09316", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:souvik-kundu", "kind": "person", "label": "Souvik Kundu", "url": "https://arxiv.org/abs/2506.09316", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhangyang-wang", "kind": "person", "label": "Zhangyang Wang", "url": "https://arxiv.org/abs/2506.09316", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:aditya-akella", "kind": "person", "label": "Aditya Akella", "url": "https://arxiv.org/abs/2506.09316", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2508.19528", "kind": "paper", "label": "FLASepformer: Efficient Speech Separation with Gated Focused Linear Attention Transformer", "url": "https://arxiv.org/abs/2508.19528", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yiheng-jiang", "kind": "person", "label": "Yiheng Jiang", "url": "https://arxiv.org/abs/2508.19528", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:gang-qiao", "kind": "person", "label": "Gang Qiao", "url": "https://arxiv.org/abs/2508.19528", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:pengteng-shi", "kind": "person", "label": "Pengteng Shi", "url": "https://arxiv.org/abs/2508.19528", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:biao-tian", "kind": "person", "label": "Biao Tian", "url": "https://arxiv.org/abs/2508.19528", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2512.15038", "kind": "paper", "label": "LADY: Linear Attention for Autonomous Driving Efficiency without Transformers", "url": "https://arxiv.org/abs/2512.15038", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:jihao-huang", "kind": "person", "label": "Jihao Huang", "url": "https://arxiv.org/abs/2512.15038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xi-xia", "kind": "person", "label": "Xi Xia", "url": "https://arxiv.org/abs/2512.15038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhiyuan-li", "kind": "person", "label": "Zhiyuan Li", "url": "https://arxiv.org/abs/2512.15038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tianle-liu", "kind": "person", "label": "Tianle Liu", "url": "https://arxiv.org/abs/2512.15038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jingke-wang", "kind": "person", "label": "Jingke Wang", "url": "https://arxiv.org/abs/2512.15038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:junbo-chen", "kind": "person", "label": "Junbo Chen", "url": "https://arxiv.org/abs/2512.15038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tengju-ye", "kind": "person", "label": "Tengju Ye", "url": "https://arxiv.org/abs/2512.15038", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2401.00912", "kind": "paper", "label": "ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention", "url": "https://arxiv.org/abs/2401.00912", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:chenhang-he", "kind": "person", "label": "Chenhang He", "url": "https://arxiv.org/abs/2401.00912", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ruihuang-li", "kind": "person", "label": "Ruihuang Li", "url": "https://arxiv.org/abs/2401.00912", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:guowen-zhang", "kind": "person", "label": "Guowen Zhang", "url": "https://arxiv.org/abs/2401.00912", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2601.13683", "kind": "paper", "label": "Dynamic Differential Linear Attention: Enhancing Linear Diffusion Transformer for High-Quality Image Generation", "url": "https://arxiv.org/abs/2601.13683", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:boyuan-cao", "kind": "person", "label": "Boyuan Cao", "url": "https://arxiv.org/abs/2601.13683", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xingbo-yao", "kind": "person", "label": "Xingbo Yao", "url": "https://arxiv.org/abs/2601.13683", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chenhui-wang", "kind": "person", "label": "Chenhui Wang", "url": "https://arxiv.org/abs/2601.13683", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jiaxin-ye", "kind": "person", "label": "Jiaxin Ye", "url": "https://arxiv.org/abs/2601.13683", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yujie-wei", "kind": "person", "label": "Yujie Wei", "url": "https://arxiv.org/abs/2601.13683", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hongming-shan", "kind": "person", "label": "Hongming Shan", "url": "https://arxiv.org/abs/2601.13683", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2603.16063", "kind": "paper", "label": "ViT-AdaLA: Adapting Vision Transformers with Linear Attention", "url": "https://arxiv.org/abs/2603.16063", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yifan-li", "kind": "person", "label": "Yifan Li", "url": "https://arxiv.org/abs/2603.16063", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:seunghyun-yoon", "kind": "person", "label": "Seunghyun Yoon", "url": "https://arxiv.org/abs/2603.16063", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:viet-dac-lai", "kind": "person", "label": "Viet Dac Lai", "url": "https://arxiv.org/abs/2603.16063", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:franck-dernoncourt", "kind": "person", "label": "Franck Dernoncourt", "url": "https://arxiv.org/abs/2603.16063", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jason-kuen", "kind": "person", "label": "Jason Kuen", "url": "https://arxiv.org/abs/2603.16063", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yu-kong", "kind": "person", "label": "Yu Kong", "url": "https://arxiv.org/abs/2603.16063", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:trung-bui", "kind": "person", "label": "Trung Bui", "url": "https://arxiv.org/abs/2603.16063", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.18848", "kind": "paper", "label": "Exact Linear Attention", "url": "https://arxiv.org/abs/2605.18848", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:weinuo-ou", "kind": "person", "label": "Weinuo Ou", "url": "https://arxiv.org/abs/2605.18848", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2511.06294", "kind": "paper", "label": "Transolver is a Linear Transformer: Revisiting Physics-Attention through the Lens of Linear Attention", "url": "https://arxiv.org/abs/2511.06294", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:wenjie-hu", "kind": "person", "label": "Wenjie Hu", "url": "https://arxiv.org/abs/2511.06294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:sidun-liu", "kind": "person", "label": "Sidun Liu", "url": "https://arxiv.org/abs/2511.06294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:peng-qiao", "kind": "person", "label": "Peng Qiao", "url": "https://arxiv.org/abs/2511.06294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhenglun-sun", "kind": "person", "label": "Zhenglun Sun", "url": "https://arxiv.org/abs/2511.06294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yong-dou", "kind": "person", "label": "Yong Dou", "url": "https://arxiv.org/abs/2511.06294", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.07333", "kind": "paper", "label": "Beyond Linear Attention: Softmax Transformers Implement In-Context Reinforcement Learning", "url": "https://arxiv.org/abs/2605.07333", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:zixuan-xie", "kind": "person", "label": "Zixuan Xie", "url": "https://arxiv.org/abs/2605.07333", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xinyu-liu", "kind": "person", "label": "Xinyu Liu", "url": "https://arxiv.org/abs/2605.07333", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:claire-chen", "kind": "person", "label": "Claire Chen", "url": "https://arxiv.org/abs/2605.07333", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shuze-daniel-liu", "kind": "person", "label": "Shuze Daniel Liu", "url": "https://arxiv.org/abs/2605.07333", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:rohan-chandra", "kind": "person", "label": "Rohan Chandra", "url": "https://arxiv.org/abs/2605.07333", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shangtong-zhang", "kind": "person", "label": "Shangtong Zhang", "url": "https://arxiv.org/abs/2605.07333", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2310.11685", "kind": "paper", "label": "Why Softmax Attention Outperforms Linear Attention", "url": "https://arxiv.org/abs/2310.11685", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yichuan-deng", "kind": "person", "label": "Yichuan Deng", "url": "https://arxiv.org/abs/2310.11685", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhao-song", "kind": "person", "label": "Zhao Song", "url": "https://arxiv.org/abs/2310.11685", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:kaijun-yuan", "kind": "person", "label": "Kaijun Yuan", "url": "https://arxiv.org/abs/2310.11685", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tianyi-zhou", "kind": "person", "label": "Tianyi Zhou", "url": "https://arxiv.org/abs/2310.11685", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2405.11582", "kind": "paper", "label": "SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization", "url": "https://arxiv.org/abs/2405.11582", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:jialong-guo", "kind": "person", "label": "Jialong Guo", "url": "https://arxiv.org/abs/2405.11582", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xinghao-chen", "kind": "person", "label": "Xinghao Chen", "url": "https://arxiv.org/abs/2405.11582", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yehui-tang", "kind": "person", "label": "Yehui Tang", "url": "https://arxiv.org/abs/2405.11582", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yunhe-wang", "kind": "person", "label": "Yunhe Wang", "url": "https://arxiv.org/abs/2405.11582", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2410.10101", "kind": "paper", "label": "Learning Linear Attention in Polynomial Time", "url": "https://arxiv.org/abs/2410.10101", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:morris-yau", "kind": "person", "label": "Morris Yau", "url": "https://arxiv.org/abs/2410.10101", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ekin-aky-rek", "kind": "person", "label": "Ekin Aky\u00fcrek", "url": "https://arxiv.org/abs/2410.10101", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jiayuan-mao", "kind": "person", "label": "Jiayuan Mao", "url": "https://arxiv.org/abs/2410.10101", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:joshua-b-tenenbaum", "kind": "person", "label": "Joshua B. Tenenbaum", "url": "https://arxiv.org/abs/2410.10101", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:stefanie-jegelka", "kind": "person", "label": "Stefanie Jegelka", "url": "https://arxiv.org/abs/2410.10101", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jacob-andreas", "kind": "person", "label": "Jacob Andreas", "url": "https://arxiv.org/abs/2410.10101", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2602.05230", "kind": "paper", "label": "ZeroS: Zero-Sum Linear Attention for Efficient Transformers", "url": "https://arxiv.org/abs/2602.05230", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:jiecheng-lu", "kind": "person", "label": "Jiecheng Lu", "url": "https://arxiv.org/abs/2602.05230", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xu-han", "kind": "person", "label": "Xu Han", "url": "https://arxiv.org/abs/2602.05230", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yan-sun", "kind": "person", "label": "Yan Sun", "url": "https://arxiv.org/abs/2602.05230", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:viresh-pati", "kind": "person", "label": "Viresh Pati", "url": "https://arxiv.org/abs/2602.05230", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yubin-kim", "kind": "person", "label": "Yubin Kim", "url": "https://arxiv.org/abs/2602.05230", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:siddhartha-somani", "kind": "person", "label": "Siddhartha Somani", "url": "https://arxiv.org/abs/2602.05230", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shihao-yang", "kind": "person", "label": "Shihao Yang", "url": "https://arxiv.org/abs/2602.05230", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2405.16605", "kind": "paper", "label": "Demystify Mamba in Vision: A Linear Attention Perspective", "url": "https://arxiv.org/abs/2405.16605", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:zhuofan-xia", "kind": "person", "label": "Zhuofan Xia", "url": "https://arxiv.org/abs/2405.16605", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yifan-pu", "kind": "person", "label": "Yifan Pu", "url": "https://arxiv.org/abs/2405.16605", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chunjiang-ge", "kind": "person", "label": "Chunjiang Ge", "url": "https://arxiv.org/abs/2405.16605", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jun-song", "kind": "person", "label": "Jun Song", "url": "https://arxiv.org/abs/2405.16605", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2602.12128", "kind": "paper", "label": "HLA: Hadamard Linear Attention", "url": "https://arxiv.org/abs/2602.12128", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:hanno-ackermann", "kind": "person", "label": "Hanno Ackermann", "url": "https://arxiv.org/abs/2602.12128", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hong-cai", "kind": "person", "label": "Hong Cai", "url": "https://arxiv.org/abs/2602.12128", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mohsen-ghafoorian", "kind": "person", "label": "Mohsen Ghafoorian", "url": "https://arxiv.org/abs/2602.12128", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:amirhossein-habibian", "kind": "person", "label": "Amirhossein Habibian", "url": "https://arxiv.org/abs/2602.12128", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2411.07635", "kind": "paper", "label": "Breaking the Low-Rank Dilemma of Linear Attention", "url": "https://arxiv.org/abs/2411.07635", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:qihang-fan", "kind": "person", "label": "Qihang Fan", "url": "https://arxiv.org/abs/2411.07635", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:huaibo-huang", "kind": "person", "label": "Huaibo Huang", "url": "https://arxiv.org/abs/2411.07635", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ran-he", "kind": "person", "label": "Ran He", "url": "https://arxiv.org/abs/2411.07635", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2404.02882", "kind": "paper", "label": "Linear Attention Sequence Parallelism", "url": "https://arxiv.org/abs/2404.02882", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:weigao-sun", "kind": "person", "label": "Weigao Sun", "url": "https://arxiv.org/abs/2404.02882", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:dong-li", "kind": "person", "label": "Dong Li", "url": "https://arxiv.org/abs/2404.02882", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xuyang-shen", "kind": "person", "label": "Xuyang Shen", "url": "https://arxiv.org/abs/2404.02882", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yu-qiao", "kind": "person", "label": "Yu Qiao", "url": "https://arxiv.org/abs/2404.02882", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yiran-zhong", "kind": "person", "label": "Yiran Zhong", "url": "https://arxiv.org/abs/2404.02882", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2507.00698", "kind": "paper", "label": "Rectifying Magnitude Neglect in Linear Attention", "url": "https://arxiv.org/abs/2507.00698", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yuang-ai", "kind": "person", "label": "Yuang Ai", "url": "https://arxiv.org/abs/2507.00698", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2509.25223", "kind": "paper", "label": "Enhancing Linear Attention with Residual Learning", "url": "https://arxiv.org/abs/2509.25223", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:xunhao-lai", "kind": "person", "label": "Xunhao Lai", "url": "https://arxiv.org/abs/2509.25223", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jialiang-kang", "kind": "person", "label": "Jialiang Kang", "url": "https://arxiv.org/abs/2509.25223", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jianqiao-lu", "kind": "person", "label": "Jianqiao Lu", "url": "https://arxiv.org/abs/2509.25223", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tong-lin", "kind": "person", "label": "Tong Lin", "url": "https://arxiv.org/abs/2509.25223", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:pengyu-zhao", "kind": "person", "label": "Pengyu Zhao", "url": "https://arxiv.org/abs/2509.25223", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2506.04761", "kind": "paper", "label": "Log-Linear Attention", "url": "https://arxiv.org/abs/2506.04761", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:songlin-yang", "kind": "person", "label": "Songlin Yang", "url": "https://arxiv.org/abs/2506.04761", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tarushii-goel", "kind": "person", "label": "Tarushii Goel", "url": "https://arxiv.org/abs/2506.04761", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2402.04347", "kind": "paper", "label": "The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry", "url": "https://arxiv.org/abs/2402.04347", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:michael-zhang", "kind": "person", "label": "Michael Zhang", "url": "https://arxiv.org/abs/2402.04347", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:kush-bhatia", "kind": "person", "label": "Kush Bhatia", "url": "https://arxiv.org/abs/2402.04347", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hermann-kumbong", "kind": "person", "label": "Hermann Kumbong", "url": "https://arxiv.org/abs/2402.04347", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:christopher-r", "kind": "person", "label": "Christopher R\u00e9", "url": "https://arxiv.org/abs/2402.04347", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2604.21957", "kind": "paper", "label": "MambaCSP: Hybrid-Attention State Space Models for Hardware-Efficient Channel State Prediction", "url": "https://arxiv.org/abs/2604.21957", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:aladin-djuhera", "kind": "person", "label": "Aladin Djuhera", "url": "https://arxiv.org/abs/2604.21957", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:haris-gacanin", "kind": "person", "label": "Haris Gacanin", "url": "https://arxiv.org/abs/2604.21957", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:holger-boche", "kind": "person", "label": "Holger Boche", "url": "https://arxiv.org/abs/2604.21957", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2507.16624", "kind": "paper", "label": "A2Mamba: Attention-augmented State Space Models for Visual Recognition", "url": "https://arxiv.org/abs/2507.16624", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:meng-lou", "kind": "person", "label": "Meng Lou", "url": "https://arxiv.org/abs/2507.16624", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yunxiang-fu", "kind": "person", "label": "Yunxiang Fu", "url": "https://arxiv.org/abs/2507.16624", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yizhou-yu", "kind": "person", "label": "Yizhou Yu", "url": "https://arxiv.org/abs/2507.16624", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2505.05397", "kind": "paper", "label": "PillarMamba: Learning Local-Global Context for Roadside Point Cloud via Hybrid State Space Model", "url": "https://arxiv.org/abs/2505.05397", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:zhang-zhang", "kind": "person", "label": "Zhang Zhang", "url": "https://arxiv.org/abs/2505.05397", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chao-sun", "kind": "person", "label": "Chao Sun", "url": "https://arxiv.org/abs/2505.05397", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chao-yue", "kind": "person", "label": "Chao Yue", "url": "https://arxiv.org/abs/2505.05397", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:da-wen", "kind": "person", "label": "Da Wen", "url": "https://arxiv.org/abs/2505.05397", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tianze-wang", "kind": "person", "label": "Tianze Wang", "url": "https://arxiv.org/abs/2505.05397", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jianghao-leng", "kind": "person", "label": "Jianghao Leng", "url": "https://arxiv.org/abs/2505.05397", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2605.08301", "kind": "paper", "label": "Priming: Hybrid State Space Models From Pre-trained Transformers", "url": "https://arxiv.org/abs/2605.08301", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:aditya-chattopadhyay", "kind": "person", "label": "Aditya Chattopadhyay", "url": "https://arxiv.org/abs/2605.08301", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:elvis-nunez", "kind": "person", "label": "Elvis Nunez", "url": "https://arxiv.org/abs/2605.08301", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:prannay-kaul", "kind": "person", "label": "Prannay Kaul", "url": "https://arxiv.org/abs/2605.08301", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:evan-becker", "kind": "person", "label": "Evan Becker", "url": "https://arxiv.org/abs/2605.08301", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:david-thomas", "kind": "person", "label": "David Thomas", "url": "https://arxiv.org/abs/2605.08301", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wei-xia", "kind": "person", "label": "Wei Xia", "url": "https://arxiv.org/abs/2605.08301", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2410.04159", "kind": "paper", "label": "Efficient and Robust Long-Form Speech Recognition with Hybrid H3-Conformer", "url": "https://arxiv.org/abs/2410.04159", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:tomoki-honda", "kind": "person", "label": "Tomoki Honda", "url": "https://arxiv.org/abs/2410.04159", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shinsuke-sakai", "kind": "person", "label": "Shinsuke Sakai", "url": "https://arxiv.org/abs/2410.04159", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tatsuya-kawahara", "kind": "person", "label": "Tatsuya Kawahara", "url": "https://arxiv.org/abs/2410.04159", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2412.13328", "kind": "paper", "label": "Expansion Span: Combining Fading Memory and Retrieval in Hybrid State Space Models", "url": "https://arxiv.org/abs/2412.13328", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:stefano-soatto", "kind": "person", "label": "Stefano Soatto", "url": "https://arxiv.org/abs/2412.13328", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2406.06069", "kind": "paper", "label": "PointABM:Integrating Bidirectional State Space Model with Multi-Head Self-Attention for Point Cloud Analysis", "url": "https://arxiv.org/abs/2406.06069", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:jia-wei-chen", "kind": "person", "label": "Jia-wei Chen", "url": "https://arxiv.org/abs/2406.06069", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yu-jie-xiong", "kind": "person", "label": "Yu-jie Xiong", "url": "https://arxiv.org/abs/2406.06069", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yong-bin-gao", "kind": "person", "label": "Yong-bin Gao", "url": "https://arxiv.org/abs/2406.06069", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2406.07522", "kind": "paper", "label": "Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling", "url": "https://arxiv.org/abs/2406.07522", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:liliang-ren", "kind": "person", "label": "Liliang Ren", "url": "https://arxiv.org/abs/2406.07522", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yadong-lu", "kind": "person", "label": "Yadong Lu", "url": "https://arxiv.org/abs/2406.07522", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yelong-shen", "kind": "person", "label": "Yelong Shen", "url": "https://arxiv.org/abs/2406.07522", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chen-liang", "kind": "person", "label": "Chen Liang", "url": "https://arxiv.org/abs/2406.07522", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:weizhu-chen", "kind": "person", "label": "Weizhu Chen", "url": "https://arxiv.org/abs/2406.07522", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2506.03654", "kind": "paper", "label": "MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection", "url": "https://arxiv.org/abs/2506.03654", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:xiaochun-lei", "kind": "person", "label": "Xiaochun Lei", "url": "https://arxiv.org/abs/2506.03654", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:siqi-wu", "kind": "person", "label": "Siqi Wu", "url": "https://arxiv.org/abs/2506.03654", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:weilin-wu", "kind": "person", "label": "Weilin Wu", "url": "https://arxiv.org/abs/2506.03654", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zetao-jiang", "kind": "person", "label": "Zetao Jiang", "url": "https://arxiv.org/abs/2506.03654", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2603.02874", "kind": "paper", "label": "Retrievit: In-context Retrieval Capabilities of Transformers, State Space Models, and Hybrid Architectures", "url": "https://arxiv.org/abs/2603.02874", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:georgios-pantazopoulos", "kind": "person", "label": "Georgios Pantazopoulos", "url": "https://arxiv.org/abs/2603.02874", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:malvina-nikandrou", "kind": "person", "label": "Malvina Nikandrou", "url": "https://arxiv.org/abs/2603.02874", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ioannis-konstas", "kind": "person", "label": "Ioannis Konstas", "url": "https://arxiv.org/abs/2603.02874", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:alessandro-suglia", "kind": "person", "label": "Alessandro Suglia", "url": "https://arxiv.org/abs/2603.02874", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2406.16495", "kind": "paper", "label": "OTCE: Hybrid SSM and Attention with Cross Domain Mixture of Experts to construct Observer-Thinker-Conceiver-Expresser", "url": "https://arxiv.org/abs/2406.16495", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:ting-xie", "kind": "person", "label": "Ting Xie", "url": "https://arxiv.org/abs/2406.16495", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:chunjun-zheng", "kind": "person", "label": "Chunjun Zheng", "url": "https://arxiv.org/abs/2406.16495", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:kai-wang", "kind": "person", "label": "Kai Wang", "url": "https://arxiv.org/abs/2406.16495", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2506.05320", "kind": "paper", "label": "Generalizable, real-time neural decoding with hybrid state-space models", "url": "https://arxiv.org/abs/2506.05320", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:avery-hee-woon-ryoo", "kind": "person", "label": "Avery Hee-Woon Ryoo", "url": "https://arxiv.org/abs/2506.05320", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:nanda-h-krishna", "kind": "person", "label": "Nanda H. Krishna", "url": "https://arxiv.org/abs/2506.05320", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ximeng-mao", "kind": "person", "label": "Ximeng Mao", "url": "https://arxiv.org/abs/2506.05320", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mehdi-azabou", "kind": "person", "label": "Mehdi Azabou", "url": "https://arxiv.org/abs/2506.05320", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:eva-l-dyer", "kind": "person", "label": "Eva L. Dyer", "url": "https://arxiv.org/abs/2506.05320", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:matthew-g-perich", "kind": "person", "label": "Matthew G. Perich", "url": "https://arxiv.org/abs/2506.05320", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:guillaume-lajoie", "kind": "person", "label": "Guillaume Lajoie", "url": "https://arxiv.org/abs/2506.05320", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2509.00259", "kind": "paper", "label": "Quantum-Optimized Selective State Space Model for Efficient Time Series Prediction", "url": "https://arxiv.org/abs/2509.00259", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:stefan-alexandru-jura", "kind": "person", "label": "Stefan-Alexandru Jura", "url": "https://arxiv.org/abs/2509.00259", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mihai-udrescu", "kind": "person", "label": "Mihai Udrescu", "url": "https://arxiv.org/abs/2509.00259", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:alexandru-topirceanu", "kind": "person", "label": "Alexandru Topirceanu", "url": "https://arxiv.org/abs/2509.00259", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2506.21330", "kind": "paper", "label": "Holistic Surgical Phase Recognition with Hierarchical Input Dependent State Space Models", "url": "https://arxiv.org/abs/2506.21330", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:haoyang-wu", "kind": "person", "label": "Haoyang Wu", "url": "https://arxiv.org/abs/2506.21330", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tsun-hsuan-wang", "kind": "person", "label": "Tsun-Hsuan Wang", "url": "https://arxiv.org/abs/2506.21330", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mathias-lechner", "kind": "person", "label": "Mathias Lechner", "url": "https://arxiv.org/abs/2506.21330", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ramin-hasani", "kind": "person", "label": "Ramin Hasani", "url": "https://arxiv.org/abs/2506.21330", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jennifer-a-eckhoff", "kind": "person", "label": "Jennifer A. Eckhoff", "url": "https://arxiv.org/abs/2506.21330", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:paul-pak", "kind": "person", "label": "Paul Pak", "url": "https://arxiv.org/abs/2506.21330", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ozanan-r-meireles", "kind": "person", "label": "Ozanan R. Meireles", "url": "https://arxiv.org/abs/2506.21330", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:guy-rosman", "kind": "person", "label": "Guy Rosman", "url": "https://arxiv.org/abs/2506.21330", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2412.11890", "kind": "paper", "label": "SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentation", "url": "https://arxiv.org/abs/2412.11890", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:paper:2411.15459", "kind": "paper", "label": "MambaVLT: Time-Evolving Multimodal State Space Model for Vision-Language Tracking", "url": "https://arxiv.org/abs/2411.15459", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:xinqi-liu", "kind": "person", "label": "Xinqi Liu", "url": "https://arxiv.org/abs/2411.15459", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:li-zhou", "kind": "person", "label": "Li Zhou", "url": "https://arxiv.org/abs/2411.15459", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zikun-zhou", "kind": "person", "label": "Zikun Zhou", "url": "https://arxiv.org/abs/2411.15459", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jianqiu-chen", "kind": "person", "label": "Jianqiu Chen", "url": "https://arxiv.org/abs/2411.15459", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:zhenyu-he", "kind": "person", "label": "Zhenyu He", "url": "https://arxiv.org/abs/2411.15459", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2507.16955", "kind": "paper", "label": "A Hybrid CNN-VSSM model for Multi-View, Multi-Task Mammography Analysis: Robust Diagnosis with Attention-Based Fusion", "url": "https://arxiv.org/abs/2507.16955", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yalda-zafari", "kind": "person", "label": "Yalda Zafari", "url": "https://arxiv.org/abs/2507.16955", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:roaa-elalfy", "kind": "person", "label": "Roaa Elalfy", "url": "https://arxiv.org/abs/2507.16955", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mohamed-mabrok", "kind": "person", "label": "Mohamed Mabrok", "url": "https://arxiv.org/abs/2507.16955", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:somaya-al-maadeed", "kind": "person", "label": "Somaya Al-Maadeed", "url": "https://arxiv.org/abs/2507.16955", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tamer-khattab", "kind": "person", "label": "Tamer Khattab", "url": "https://arxiv.org/abs/2507.16955", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:essam-a-rashed", "kind": "person", "label": "Essam A. Rashed", "url": "https://arxiv.org/abs/2507.16955", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2606.23126", "kind": "paper", "label": "MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection", "url": "https://arxiv.org/abs/2606.23126", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:xiaobin-hu", "kind": "person", "label": "Xiaobin Hu", "url": "https://arxiv.org/abs/2606.23126", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:haoyang-he", "kind": "person", "label": "Haoyang He", "url": "https://arxiv.org/abs/2606.23126", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:bo-yin", "kind": "person", "label": "Bo Yin", "url": "https://arxiv.org/abs/2606.23126", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yu-he", "kind": "person", "label": "Yu He", "url": "https://arxiv.org/abs/2606.23126", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:lei-xie", "kind": "person", "label": "Lei Xie", "url": "https://arxiv.org/abs/2606.23126", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jiangning-zhang", "kind": "person", "label": "Jiangning Zhang", "url": "https://arxiv.org/abs/2606.23126", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yu-gang-jiang", "kind": "person", "label": "Yu-Gang Jiang", "url": "https://arxiv.org/abs/2606.23126", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shuicheng-yan", "kind": "person", "label": "Shuicheng Yan", "url": "https://arxiv.org/abs/2606.23126", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2510.00862", "kind": "paper", "label": "Gather-Scatter Mamba: Accelerating Propagation with Efficient State Space Model", "url": "https://arxiv.org/abs/2510.00862", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:hyun-kyu-ko", "kind": "person", "label": "Hyun-kyu Ko", "url": "https://arxiv.org/abs/2510.00862", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:youbin-kim", "kind": "person", "label": "Youbin Kim", "url": "https://arxiv.org/abs/2510.00862", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jihyeon-park", "kind": "person", "label": "Jihyeon Park", "url": "https://arxiv.org/abs/2510.00862", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:dongheok-park", "kind": "person", "label": "Dongheok Park", "url": "https://arxiv.org/abs/2510.00862", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:gyeongjin-kang", "kind": "person", "label": "Gyeongjin Kang", "url": "https://arxiv.org/abs/2510.00862", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wonjun-cho", "kind": "person", "label": "Wonjun Cho", "url": "https://arxiv.org/abs/2510.00862", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hyung-yi", "kind": "person", "label": "Hyung Yi", "url": "https://arxiv.org/abs/2510.00862", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:eunbyung-park", "kind": "person", "label": "Eunbyung Park", "url": "https://arxiv.org/abs/2510.00862", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2603.08859", "kind": "paper", "label": "Expressivity-Efficiency Tradeoffs for Hybrid Sequence Models", "url": "https://arxiv.org/abs/2603.08859", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:john-cooper", "kind": "person", "label": "John Cooper", "url": "https://arxiv.org/abs/2603.08859", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ilias-diakonikolas", "kind": "person", "label": "Ilias Diakonikolas", "url": "https://arxiv.org/abs/2603.08859", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:mingchen-ma", "kind": "person", "label": "Mingchen Ma", "url": "https://arxiv.org/abs/2603.08859", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:frederic-sala", "kind": "person", "label": "Frederic Sala", "url": "https://arxiv.org/abs/2603.08859", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2603.18757", "kind": "paper", "label": "DA-Mamba: Learning Domain-Aware State Space Model for Global-Local Alignment in Domain Adaptive Object Detection", "url": "https://arxiv.org/abs/2603.18757", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:haochen-li", "kind": "person", "label": "Haochen Li", "url": "https://arxiv.org/abs/2603.18757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:rui-zhang", "kind": "person", "label": "Rui Zhang", "url": "https://arxiv.org/abs/2603.18757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hantao-yao", "kind": "person", "label": "Hantao Yao", "url": "https://arxiv.org/abs/2603.18757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:xin-zhang", "kind": "person", "label": "Xin Zhang", "url": "https://arxiv.org/abs/2603.18757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yifan-hao", "kind": "person", "label": "Yifan Hao", "url": "https://arxiv.org/abs/2603.18757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shaohui-peng", "kind": "person", "label": "Shaohui Peng", "url": "https://arxiv.org/abs/2603.18757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:yongwei-zhao", "kind": "person", "label": "Yongwei Zhao", "url": "https://arxiv.org/abs/2603.18757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:ling-li", "kind": "person", "label": "Ling Li", "url": "https://arxiv.org/abs/2603.18757", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2512.11503", "kind": "paper", "label": "TSkel-Mamba: Temporal Dynamic Modeling via State Space Model for Human Skeleton-based Action Recognition", "url": "https://arxiv.org/abs/2512.11503", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:yanan-liu", "kind": "person", "label": "Yanan Liu", "url": "https://arxiv.org/abs/2512.11503", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:qiuhong-ke", "kind": "person", "label": "Qiuhong Ke", "url": "https://arxiv.org/abs/2512.11503", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2407.05489", "kind": "paper", "label": "How Effective are State Space Models for Machine Translation?", "url": "https://arxiv.org/abs/2407.05489", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:hugo-pitorro", "kind": "person", "label": "Hugo Pitorro", "url": "https://arxiv.org/abs/2407.05489", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:pavlo-vasylenko", "kind": "person", "label": "Pavlo Vasylenko", "url": "https://arxiv.org/abs/2407.05489", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:marcos-treviso", "kind": "person", "label": "Marcos Treviso", "url": "https://arxiv.org/abs/2407.05489", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:andr-f-t-martins", "kind": "person", "label": "Andr\u00e9 F. T. Martins", "url": "https://arxiv.org/abs/2407.05489", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2510.26912", "kind": "paper", "label": "Understanding and Enhancing Mamba-Transformer Hybrids for Memory Recall and Language Modeling", "url": "https://arxiv.org/abs/2510.26912", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:hyunji-lee", "kind": "person", "label": "Hyunji Lee", "url": "https://arxiv.org/abs/2510.26912", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wenhao-yu", "kind": "person", "label": "Wenhao Yu", "url": "https://arxiv.org/abs/2510.26912", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:hongming-zhang", "kind": "person", "label": "Hongming Zhang", "url": "https://arxiv.org/abs/2510.26912", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:kaixin-ma", "kind": "person", "label": "Kaixin Ma", "url": "https://arxiv.org/abs/2510.26912", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:jiyeon-kim", "kind": "person", "label": "Jiyeon Kim", "url": "https://arxiv.org/abs/2510.26912", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:dong-yu", "kind": "person", "label": "Dong Yu", "url": "https://arxiv.org/abs/2510.26912", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:minjoon-seo", "kind": "person", "label": "Minjoon Seo", "url": "https://arxiv.org/abs/2510.26912", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2511.08872", "kind": "paper", "label": "SasMamba: A Lightweight Structure-Aware Stride State Space Model for 3D Human Pose Estimation", "url": "https://arxiv.org/abs/2511.08872", "source": "arxiv", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:hu-cui", "kind": "person", "label": "Hu Cui", "url": "https://arxiv.org/abs/2511.08872", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:wenqiang-hua", "kind": "person", "label": "Wenqiang Hua", "url": "https://arxiv.org/abs/2511.08872", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:renjing-huang", "kind": "person", "label": "Renjing Huang", "url": "https://arxiv.org/abs/2511.08872", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:shurui-jia", "kind": "person", "label": "Shurui Jia", "url": "https://arxiv.org/abs/2511.08872", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:person:tessai-hayama", "kind": "person", "label": "Tessai Hayama", "url": "https://arxiv.org/abs/2511.08872", "source": "arxiv-author", "axis": "attention", "layer": 0}
{"type": "node", "id": "p2:paper:2109.04318", "kind": "paper", "label": "Estimation of Corporate Greenhouse Gas Emissions via Machine Learning", "url": "https://arxiv.org/abs/2109.04318", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:you-han", "kind": "person", "label": "You Han", "url": "https://arxiv.org/abs/2109.04318", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:achintya-gopal", "kind": "person", "label": "Achintya Gopal", "url": "https://arxiv.org/abs/2109.04318", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:liwen-ouyang", "kind": "person", "label": "Liwen Ouyang", "url": "https://arxiv.org/abs/2109.04318", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:aaron-key", "kind": "person", "label": "Aaron Key", "url": "https://arxiv.org/abs/2109.04318", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2403.19009", "kind": "paper", "label": "Towards Sustainable SecureML: Quantifying Carbon Footprint of Adversarial Machine Learning", "url": "https://arxiv.org/abs/2403.19009", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:syed-mhamudul-hasan", "kind": "person", "label": "Syed Mhamudul Hasan", "url": "https://arxiv.org/abs/2403.19009", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:abdur-r-shahid", "kind": "person", "label": "Abdur R. Shahid", "url": "https://arxiv.org/abs/2403.19009", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ahmed-imteaj", "kind": "person", "label": "Ahmed Imteaj", "url": "https://arxiv.org/abs/2403.19009", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2204.05149", "kind": "paper", "label": "The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink", "url": "https://arxiv.org/abs/2204.05149", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:david-patterson", "kind": "person", "label": "David Patterson", "url": "https://arxiv.org/abs/2204.05149", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:joseph-gonzalez", "kind": "person", "label": "Joseph Gonzalez", "url": "https://arxiv.org/abs/2204.05149", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:urs-h-lzle", "kind": "person", "label": "Urs H\u00f6lzle", "url": "https://arxiv.org/abs/2204.05149", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:quoc-le", "kind": "person", "label": "Quoc Le", "url": "https://arxiv.org/abs/2204.05149", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lluis-miquel-munguia", "kind": "person", "label": "Lluis-Miquel Munguia", "url": "https://arxiv.org/abs/2204.05149", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:daniel-rothchild", "kind": "person", "label": "Daniel Rothchild", "url": "https://arxiv.org/abs/2204.05149", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:david-so", "kind": "person", "label": "David So", "url": "https://arxiv.org/abs/2204.05149", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2011.12443", "kind": "paper", "label": "The Human Effect Requires Affect: Addressing Social-Psychological Factors of Climate Change with Machine Learning", "url": "https://arxiv.org/abs/2011.12443", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:kyle-tilbury", "kind": "person", "label": "Kyle Tilbury", "url": "https://arxiv.org/abs/2011.12443", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jesse-hoey", "kind": "person", "label": "Jesse Hoey", "url": "https://arxiv.org/abs/2011.12443", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2407.19724", "kind": "paper", "label": "Constructing artificial life and materials scientists with accelerated AI using Deep AndersoNN", "url": "https://arxiv.org/abs/2407.19724", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:saleem-abdul-fattah-ahmed-al-dajani", "kind": "person", "label": "Saleem Abdul Fattah Ahmed Al Dajani", "url": "https://arxiv.org/abs/2407.19724", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:david-keyes", "kind": "person", "label": "David Keyes", "url": "https://arxiv.org/abs/2407.19724", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2305.11164", "kind": "paper", "label": "Exploring the Carbon Footprint of Hugging Face's ML Models: A Repository Mining Study", "url": "https://arxiv.org/abs/2305.11164", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:joel-casta-o", "kind": "person", "label": "Joel Casta\u00f1o", "url": "https://arxiv.org/abs/2305.11164", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:silverio-mart-nez-fern-ndez", "kind": "person", "label": "Silverio Mart\u00ednez-Fern\u00e1ndez", "url": "https://arxiv.org/abs/2305.11164", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:justus-bogner", "kind": "person", "label": "Justus Bogner", "url": "https://arxiv.org/abs/2305.11164", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2410.02950", "kind": "paper", "label": "LLMCO2: Advancing Accurate Carbon Footprint Prediction for LLM Inferences", "url": "https://arxiv.org/abs/2410.02950", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:zhenxiao-fu", "kind": "person", "label": "Zhenxiao Fu", "url": "https://arxiv.org/abs/2410.02950", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:fan-chen", "kind": "person", "label": "Fan Chen", "url": "https://arxiv.org/abs/2410.02950", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:shan-zhou", "kind": "person", "label": "Shan Zhou", "url": "https://arxiv.org/abs/2410.02950", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:haitong-li", "kind": "person", "label": "Haitong Li", "url": "https://arxiv.org/abs/2410.02950", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lei-jiang", "kind": "person", "label": "Lei Jiang", "url": "https://arxiv.org/abs/2410.02950", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2310.17972", "kind": "paper", "label": "EcoLearn: Optimizing the Carbon Footprint of Federated Learning", "url": "https://arxiv.org/abs/2310.17972", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:talha-mehboob", "kind": "person", "label": "Talha Mehboob", "url": "https://arxiv.org/abs/2310.17972", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:noman-bashir", "kind": "person", "label": "Noman Bashir", "url": "https://arxiv.org/abs/2310.17972", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jesus-omana-iglesias", "kind": "person", "label": "Jesus Omana Iglesias", "url": "https://arxiv.org/abs/2310.17972", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:michael-zink", "kind": "person", "label": "Michael Zink", "url": "https://arxiv.org/abs/2310.17972", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:david-irwin", "kind": "person", "label": "David Irwin", "url": "https://arxiv.org/abs/2310.17972", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2102.07627", "kind": "paper", "label": "A first look into the carbon footprint of federated learning", "url": "https://arxiv.org/abs/2102.07627", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:xinchi-qiu", "kind": "person", "label": "Xinchi Qiu", "url": "https://arxiv.org/abs/2102.07627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:titouan-parcollet", "kind": "person", "label": "Titouan Parcollet", "url": "https://arxiv.org/abs/2102.07627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:javier-fernandez-marques", "kind": "person", "label": "Javier Fernandez-Marques", "url": "https://arxiv.org/abs/2102.07627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:pedro-porto-buarque-de-gusmao", "kind": "person", "label": "Pedro Porto Buarque de Gusmao", "url": "https://arxiv.org/abs/2102.07627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yan-gao", "kind": "person", "label": "Yan Gao", "url": "https://arxiv.org/abs/2102.07627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:daniel-j-beutel", "kind": "person", "label": "Daniel J. Beutel", "url": "https://arxiv.org/abs/2102.07627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:taner-topal", "kind": "person", "label": "Taner Topal", "url": "https://arxiv.org/abs/2102.07627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:akhil-mathur", "kind": "person", "label": "Akhil Mathur", "url": "https://arxiv.org/abs/2102.07627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2206.03227", "kind": "paper", "label": "Does Crypto Kill? Relationship between Electricity Consumption Carbon Footprints and Bitcoin Transactions", "url": "https://arxiv.org/abs/2206.03227", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:altanai-bisht", "kind": "person", "label": "Altanai Bisht", "url": "https://arxiv.org/abs/2206.03227", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:arielle-wilson", "kind": "person", "label": "Arielle Wilson", "url": "https://arxiv.org/abs/2206.03227", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:zachary-jeffreys", "kind": "person", "label": "Zachary Jeffreys", "url": "https://arxiv.org/abs/2206.03227", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:shadrokh-samavi", "kind": "person", "label": "Shadrokh Samavi", "url": "https://arxiv.org/abs/2206.03227", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:1911.11658", "kind": "paper", "label": "A User Study of Perceived Carbon Footprint", "url": "https://arxiv.org/abs/1911.11658", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:victor-kristof", "kind": "person", "label": "Victor Kristof", "url": "https://arxiv.org/abs/1911.11658", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:valentin-quelquejay-lecl-re", "kind": "person", "label": "Valentin Quelquejay-Lecl\u00e8re", "url": "https://arxiv.org/abs/1911.11658", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:robin-zbinden", "kind": "person", "label": "Robin Zbinden", "url": "https://arxiv.org/abs/1911.11658", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lucas-maystre", "kind": "person", "label": "Lucas Maystre", "url": "https://arxiv.org/abs/1911.11658", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:matthias-grossglauser", "kind": "person", "label": "Matthias Grossglauser", "url": "https://arxiv.org/abs/1911.11658", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:patrick-thiran", "kind": "person", "label": "Patrick Thiran", "url": "https://arxiv.org/abs/1911.11658", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2309.14393", "kind": "paper", "label": "LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models", "url": "https://arxiv.org/abs/2309.14393", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ahmad-faiz", "kind": "person", "label": "Ahmad Faiz", "url": "https://arxiv.org/abs/2309.14393", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sotaro-kaneda", "kind": "person", "label": "Sotaro Kaneda", "url": "https://arxiv.org/abs/2309.14393", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ruhan-wang", "kind": "person", "label": "Ruhan Wang", "url": "https://arxiv.org/abs/2309.14393", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:rita-osi", "kind": "person", "label": "Rita Osi", "url": "https://arxiv.org/abs/2309.14393", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:prateek-sharma", "kind": "person", "label": "Prateek Sharma", "url": "https://arxiv.org/abs/2309.14393", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2403.14092", "kind": "paper", "label": "Carbon Footprint Reduction for Sustainable Data Centers in Real-Time", "url": "https://arxiv.org/abs/2403.14092", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:soumyendu-sarkar", "kind": "person", "label": "Soumyendu Sarkar", "url": "https://arxiv.org/abs/2403.14092", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:avisek-naug", "kind": "person", "label": "Avisek Naug", "url": "https://arxiv.org/abs/2403.14092", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ricardo-luna", "kind": "person", "label": "Ricardo Luna", "url": "https://arxiv.org/abs/2403.14092", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:antonio-guillen", "kind": "person", "label": "Antonio Guillen", "url": "https://arxiv.org/abs/2403.14092", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:vineet-gundecha", "kind": "person", "label": "Vineet Gundecha", "url": "https://arxiv.org/abs/2403.14092", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sahand-ghorbanpour", "kind": "person", "label": "Sahand Ghorbanpour", "url": "https://arxiv.org/abs/2403.14092", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sajad-mousavi", "kind": "person", "label": "Sajad Mousavi", "url": "https://arxiv.org/abs/2403.14092", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:dejan-markovikj", "kind": "person", "label": "Dejan Markovikj", "url": "https://arxiv.org/abs/2403.14092", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2403.10984", "kind": "paper", "label": "IoTCO2: Assessing the End-To-End Carbon Footprint of Internet-of-Things-Enabled Deep Learning", "url": "https://arxiv.org/abs/2403.10984", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:shahzeen-attari", "kind": "person", "label": "Shahzeen Attari", "url": "https://arxiv.org/abs/2403.10984", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:gayle-buck", "kind": "person", "label": "Gayle Buck", "url": "https://arxiv.org/abs/2403.10984", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2203.02202", "kind": "paper", "label": "Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis", "url": "https://arxiv.org/abs/2203.02202", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:raghavendra-selvan", "kind": "person", "label": "Raghavendra Selvan", "url": "https://arxiv.org/abs/2203.02202", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:nikhil-bhagwat", "kind": "person", "label": "Nikhil Bhagwat", "url": "https://arxiv.org/abs/2203.02202", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lasse-f-wolff-anthony", "kind": "person", "label": "Lasse F. Wolff Anthony", "url": "https://arxiv.org/abs/2203.02202", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:benjamin-kanding", "kind": "person", "label": "Benjamin Kanding", "url": "https://arxiv.org/abs/2203.02202", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:erik-b-dam", "kind": "person", "label": "Erik B. Dam", "url": "https://arxiv.org/abs/2203.02202", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:1911.08354", "kind": "paper", "label": "Energy Usage Reports: Environmental awareness as part of algorithmic accountability", "url": "https://arxiv.org/abs/1911.08354", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:kadan-lottick", "kind": "person", "label": "Kadan Lottick", "url": "https://arxiv.org/abs/1911.08354", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:silvia-susai", "kind": "person", "label": "Silvia Susai", "url": "https://arxiv.org/abs/1911.08354", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sorelle-a-friedler", "kind": "person", "label": "Sorelle A. Friedler", "url": "https://arxiv.org/abs/1911.08354", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jonathan-p-wilson", "kind": "person", "label": "Jonathan P. Wilson", "url": "https://arxiv.org/abs/1911.08354", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2605.05615", "kind": "paper", "label": "LLMSpace: Carbon Footprint Modeling for Large Language Model Inference on LEO Satellites", "url": "https://arxiv.org/abs/2605.05615", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:adrian-ildefonso", "kind": "person", "label": "Adrian Ildefonso", "url": "https://arxiv.org/abs/2605.05615", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:daniel-loveless", "kind": "person", "label": "Daniel Loveless", "url": "https://arxiv.org/abs/2605.05615", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2604.02347", "kind": "paper", "label": "FTimeXer: Frequency-aware Time-series Transformer with Exogenous variables for Robust Carbon Footprint Forecasting", "url": "https://arxiv.org/abs/2604.02347", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:qingzhong-li", "kind": "person", "label": "Qingzhong Li", "url": "https://arxiv.org/abs/2604.02347", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yue-hu", "kind": "person", "label": "Yue Hu", "url": "https://arxiv.org/abs/2604.02347", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:zhou-long", "kind": "person", "label": "Zhou Long", "url": "https://arxiv.org/abs/2604.02347", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:qingchang-ma", "kind": "person", "label": "Qingchang Ma", "url": "https://arxiv.org/abs/2604.02347", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:hui-ma", "kind": "person", "label": "Hui Ma", "url": "https://arxiv.org/abs/2604.02347", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jinhai-sa", "kind": "person", "label": "Jinhai Sa", "url": "https://arxiv.org/abs/2604.02347", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2409.07853", "kind": "paper", "label": "Improve Machine Learning carbon footprint using Nvidia GPU and Mixed Precision training for classification models -- Part I", "url": "https://arxiv.org/abs/2409.07853", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:andrew-antonopoulos", "kind": "person", "label": "Andrew Antonopoulos", "url": "https://arxiv.org/abs/2409.07853", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2409.11071", "kind": "paper", "label": "Improve Machine Learning carbon footprint using Parquet dataset format and Mixed Precision training for regression models -- Part II", "url": "https://arxiv.org/abs/2409.11071", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:paper:2404.04642", "kind": "paper", "label": "Power-Efficient Image Storage: Leveraging Super Resolution Generative Adversarial Network for Sustainable Compression and Reduced Carbon Footprint", "url": "https://arxiv.org/abs/2404.04642", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ashok-mondal", "kind": "person", "label": "Ashok Mondal", "url": "https://arxiv.org/abs/2404.04642", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:satyam-singh", "kind": "person", "label": "Satyam Singh", "url": "https://arxiv.org/abs/2404.04642", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2002.05651", "kind": "paper", "label": "Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning", "url": "https://arxiv.org/abs/2002.05651", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:peter-henderson", "kind": "person", "label": "Peter Henderson", "url": "https://arxiv.org/abs/2002.05651", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jieru-hu", "kind": "person", "label": "Jieru Hu", "url": "https://arxiv.org/abs/2002.05651", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:joshua-romoff", "kind": "person", "label": "Joshua Romoff", "url": "https://arxiv.org/abs/2002.05651", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:emma-brunskill", "kind": "person", "label": "Emma Brunskill", "url": "https://arxiv.org/abs/2002.05651", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:dan-jurafsky", "kind": "person", "label": "Dan Jurafsky", "url": "https://arxiv.org/abs/2002.05651", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:joelle-pineau", "kind": "person", "label": "Joelle Pineau", "url": "https://arxiv.org/abs/2002.05651", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2405.14505", "kind": "paper", "label": "Explainable automatic industrial carbon footprint estimation from bank transaction classification using natural language processing", "url": "https://arxiv.org/abs/2405.14505", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:jaime-gonz-lez-gonz-lez", "kind": "person", "label": "Jaime Gonz\u00e1lez-Gonz\u00e1lez", "url": "https://arxiv.org/abs/2405.14505", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:silvia-garc-a-m-ndez", "kind": "person", "label": "Silvia Garc\u00eda-M\u00e9ndez", "url": "https://arxiv.org/abs/2405.14505", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:francisco-de-arriba-p-rez", "kind": "person", "label": "Francisco de Arriba-P\u00e9rez", "url": "https://arxiv.org/abs/2405.14505", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:francisco-j-gonz-lez-casta-o", "kind": "person", "label": "Francisco J. Gonz\u00e1lez-Casta\u00f1o", "url": "https://arxiv.org/abs/2405.14505", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:scar-barba-seara", "kind": "person", "label": "\u00d3scar Barba-Seara", "url": "https://arxiv.org/abs/2405.14505", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2301.11899", "kind": "paper", "label": "Is TinyML Sustainable? Assessing the Environmental Impacts of Machine Learning on Microcontrollers", "url": "https://arxiv.org/abs/2301.11899", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:shvetank-prakash", "kind": "person", "label": "Shvetank Prakash", "url": "https://arxiv.org/abs/2301.11899", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:matthew-stewart", "kind": "person", "label": "Matthew Stewart", "url": "https://arxiv.org/abs/2301.11899", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:colby-banbury", "kind": "person", "label": "Colby Banbury", "url": "https://arxiv.org/abs/2301.11899", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mark-mazumder", "kind": "person", "label": "Mark Mazumder", "url": "https://arxiv.org/abs/2301.11899", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:pete-warden", "kind": "person", "label": "Pete Warden", "url": "https://arxiv.org/abs/2301.11899", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:brian-plancher", "kind": "person", "label": "Brian Plancher", "url": "https://arxiv.org/abs/2301.11899", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:vijay-janapa-reddi", "kind": "person", "label": "Vijay Janapa Reddi", "url": "https://arxiv.org/abs/2301.11899", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2302.08476", "kind": "paper", "label": "Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning", "url": "https://arxiv.org/abs/2302.08476", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:alexandra-sasha-luccioni", "kind": "person", "label": "Alexandra Sasha Luccioni", "url": "https://arxiv.org/abs/2302.08476", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:alex-hernandez-garcia", "kind": "person", "label": "Alex Hernandez-Garcia", "url": "https://arxiv.org/abs/2302.08476", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2509.13001", "kind": "paper", "label": "Green Recommender Systems: Understanding and Minimizing the Carbon Footprint of AI-Powered Personalization", "url": "https://arxiv.org/abs/2509.13001", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:lukas-wegmeth", "kind": "person", "label": "Lukas Wegmeth", "url": "https://arxiv.org/abs/2509.13001", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:tobias-vente", "kind": "person", "label": "Tobias Vente", "url": "https://arxiv.org/abs/2509.13001", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:alan-said", "kind": "person", "label": "Alan Said", "url": "https://arxiv.org/abs/2509.13001", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:joeran-beel", "kind": "person", "label": "Joeran Beel", "url": "https://arxiv.org/abs/2509.13001", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2206.10380", "kind": "paper", "label": "An Energy and Carbon Footprint Analysis of Distributed and Federated Learning", "url": "https://arxiv.org/abs/2206.10380", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:stefano-savazzi", "kind": "person", "label": "Stefano Savazzi", "url": "https://arxiv.org/abs/2206.10380", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:vittorio-rampa", "kind": "person", "label": "Vittorio Rampa", "url": "https://arxiv.org/abs/2206.10380", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sanaz-kianoush", "kind": "person", "label": "Sanaz Kianoush", "url": "https://arxiv.org/abs/2206.10380", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mehdi-bennis", "kind": "person", "label": "Mehdi Bennis", "url": "https://arxiv.org/abs/2206.10380", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2107.06946", "kind": "paper", "label": "Towards Quantifying the Carbon Emissions of Differentially Private Machine Learning", "url": "https://arxiv.org/abs/2107.06946", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:rakshit-naidu", "kind": "person", "label": "Rakshit Naidu", "url": "https://arxiv.org/abs/2107.06946", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:harshita-diddee", "kind": "person", "label": "Harshita Diddee", "url": "https://arxiv.org/abs/2107.06946", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ajinkya-mulay", "kind": "person", "label": "Ajinkya Mulay", "url": "https://arxiv.org/abs/2107.06946", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:aleti-vardhan", "kind": "person", "label": "Aleti Vardhan", "url": "https://arxiv.org/abs/2107.06946", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:krithika-ramesh", "kind": "person", "label": "Krithika Ramesh", "url": "https://arxiv.org/abs/2107.06946", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ahmed-zamzam", "kind": "person", "label": "Ahmed Zamzam", "url": "https://arxiv.org/abs/2107.06946", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2509.22092", "kind": "paper", "label": "Ground-Truthing AI Energy Consumption: Validating CodeCarbon Against External Measurements", "url": "https://arxiv.org/abs/2509.22092", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:raphael-fischer", "kind": "person", "label": "Raphael Fischer", "url": "https://arxiv.org/abs/2509.22092", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2208.00406", "kind": "paper", "label": "Eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI", "url": "https://arxiv.org/abs/2208.00406", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:semen-budennyy", "kind": "person", "label": "Semen Budennyy", "url": "https://arxiv.org/abs/2208.00406", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:vladimir-lazarev", "kind": "person", "label": "Vladimir Lazarev", "url": "https://arxiv.org/abs/2208.00406", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:nikita-zakharenko", "kind": "person", "label": "Nikita Zakharenko", "url": "https://arxiv.org/abs/2208.00406", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:alexey-korovin", "kind": "person", "label": "Alexey Korovin", "url": "https://arxiv.org/abs/2208.00406", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:olga-plosskaya", "kind": "person", "label": "Olga Plosskaya", "url": "https://arxiv.org/abs/2208.00406", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:denis-dimitrov", "kind": "person", "label": "Denis Dimitrov", "url": "https://arxiv.org/abs/2208.00406", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:vladimir-arkhipkin", "kind": "person", "label": "Vladimir Arkhipkin", "url": "https://arxiv.org/abs/2208.00406", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ivan-oseledets", "kind": "person", "label": "Ivan Oseledets", "url": "https://arxiv.org/abs/2208.00406", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2511.17683", "kind": "paper", "label": "Datacenters in the Desert: Feasibility and Sustainability of LLM Inference in the Middle East", "url": "https://arxiv.org/abs/2511.17683", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:lara-hassan", "kind": "person", "label": "Lara Hassan", "url": "https://arxiv.org/abs/2511.17683", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mohamed-elzeftawy", "kind": "person", "label": "Mohamed ElZeftawy", "url": "https://arxiv.org/abs/2511.17683", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:abdulrahman-mahmoud", "kind": "person", "label": "Abdulrahman Mahmoud", "url": "https://arxiv.org/abs/2511.17683", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2507.08836", "kind": "paper", "label": "Accuracy and Consumption analysis from a compressed model by CompactifAI from Multiverse Computing", "url": "https://arxiv.org/abs/2507.08836", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:damien-fovet", "kind": "person", "label": "Damien Fovet", "url": "https://arxiv.org/abs/2507.08836", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:shashank-chamoli", "kind": "person", "label": "Shashank Chamoli", "url": "https://arxiv.org/abs/2507.08836", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sarah-oury", "kind": "person", "label": "Sarah Oury", "url": "https://arxiv.org/abs/2507.08836", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:srishti-singhal", "kind": "person", "label": "Srishti Singhal", "url": "https://arxiv.org/abs/2507.08836", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2509.13516", "kind": "paper", "label": "An Analysis of Optimizer Choice on Energy Efficiency and Performance in Neural Network Training", "url": "https://arxiv.org/abs/2509.13516", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:tom-almog", "kind": "person", "label": "Tom Almog", "url": "https://arxiv.org/abs/2509.13516", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2604.02754", "kind": "paper", "label": "An Empirical Study of Sustainability in Prompt-driven Test Script Generation Using Small Language Models", "url": "https://arxiv.org/abs/2604.02754", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:pragati-kumari", "kind": "person", "label": "Pragati Kumari", "url": "https://arxiv.org/abs/2604.02754", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:novarun-deb", "kind": "person", "label": "Novarun Deb", "url": "https://arxiv.org/abs/2604.02754", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2602.17442", "kind": "paper", "label": "WarpRec: Unifying Academic Rigor and Industrial Scale for Responsible, Reproducible, and Efficient Recommendation", "url": "https://arxiv.org/abs/2602.17442", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:marco-avolio", "kind": "person", "label": "Marco Avolio", "url": "https://arxiv.org/abs/2602.17442", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:potito-aghilar", "kind": "person", "label": "Potito Aghilar", "url": "https://arxiv.org/abs/2602.17442", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sabino-roccotelli", "kind": "person", "label": "Sabino Roccotelli", "url": "https://arxiv.org/abs/2602.17442", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:vito-walter-anelli", "kind": "person", "label": "Vito Walter Anelli", "url": "https://arxiv.org/abs/2602.17442", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:chiara-mallamaci", "kind": "person", "label": "Chiara Mallamaci", "url": "https://arxiv.org/abs/2602.17442", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:vincenzo-paparella", "kind": "person", "label": "Vincenzo Paparella", "url": "https://arxiv.org/abs/2602.17442", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:marco-valentini", "kind": "person", "label": "Marco Valentini", "url": "https://arxiv.org/abs/2602.17442", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:alejandro-bellog-n", "kind": "person", "label": "Alejandro Bellog\u00edn", "url": "https://arxiv.org/abs/2602.17442", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2602.18012", "kind": "paper", "label": "DeCEAT: Decoding Carbon Emissions for AI-driven Software Testing", "url": "https://arxiv.org/abs/2602.18012", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:paper:2603.26712", "kind": "paper", "label": "On the Carbon Footprint of Economic Research in the Age of Generative AI", "url": "https://arxiv.org/abs/2603.26712", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:andres-alonso-robisco", "kind": "person", "label": "Andres Alonso-Robisco", "url": "https://arxiv.org/abs/2603.26712", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:carlos-esparcia", "kind": "person", "label": "Carlos Esparcia", "url": "https://arxiv.org/abs/2603.26712", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:francisco-jare-o", "kind": "person", "label": "Francisco Jare\u00f1o", "url": "https://arxiv.org/abs/2603.26712", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2602.00343", "kind": "paper", "label": "Standardized Methods and Recommendations for Green Federated Learning", "url": "https://arxiv.org/abs/2602.00343", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:austin-tapp", "kind": "person", "label": "Austin Tapp", "url": "https://arxiv.org/abs/2602.00343", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:holger-r-roth", "kind": "person", "label": "Holger R. Roth", "url": "https://arxiv.org/abs/2602.00343", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ziyue-xu", "kind": "person", "label": "Ziyue Xu", "url": "https://arxiv.org/abs/2602.00343", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:abhijeet-parida", "kind": "person", "label": "Abhijeet Parida", "url": "https://arxiv.org/abs/2602.00343", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:hareem-nisar", "kind": "person", "label": "Hareem Nisar", "url": "https://arxiv.org/abs/2602.00343", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:marius-george-linguraru", "kind": "person", "label": "Marius George Linguraru", "url": "https://arxiv.org/abs/2602.00343", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2601.00893", "kind": "paper", "label": "Towards eco friendly cybersecurity: machine learning based anomaly detection with carbon and energy metrics", "url": "https://arxiv.org/abs/2601.00893", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:kc-aashish", "kind": "person", "label": "KC Aashish", "url": "https://arxiv.org/abs/2601.00893", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:md-zakir-hossain-zamil", "kind": "person", "label": "Md Zakir Hossain Zamil", "url": "https://arxiv.org/abs/2601.00893", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:md-shafiqul-islam-mridul", "kind": "person", "label": "Md Shafiqul Islam Mridul", "url": "https://arxiv.org/abs/2601.00893", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lamia-akter", "kind": "person", "label": "Lamia Akter", "url": "https://arxiv.org/abs/2601.00893", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:farmina-sharmin", "kind": "person", "label": "Farmina Sharmin", "url": "https://arxiv.org/abs/2601.00893", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:eftekhar-hossain-ayon", "kind": "person", "label": "Eftekhar Hossain Ayon", "url": "https://arxiv.org/abs/2601.00893", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:md-maruf-bin-reza", "kind": "person", "label": "Md Maruf Bin Reza", "url": "https://arxiv.org/abs/2601.00893", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ali-hassan", "kind": "person", "label": "Ali Hassan", "url": "https://arxiv.org/abs/2601.00893", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2509.19063", "kind": "paper", "label": "Beyond Backpropagation: Exploring Innovative Algorithms for Energy-Efficient Deep Neural Network Training", "url": "https://arxiv.org/abs/2509.19063", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:przemys-aw-spyra", "kind": "person", "label": "Przemys\u0142aw Spyra", "url": "https://arxiv.org/abs/2509.19063", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2512.03054", "kind": "paper", "label": "Energy-Efficient Federated Learning via Adaptive Encoder Freezing for MRI-to-CT Conversion: A Green AI-Guided Research", "url": "https://arxiv.org/abs/2512.03054", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ciro-benito-raggio", "kind": "person", "label": "Ciro Benito Raggio", "url": "https://arxiv.org/abs/2512.03054", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lucia-migliorelli", "kind": "person", "label": "Lucia Migliorelli", "url": "https://arxiv.org/abs/2512.03054", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:nils-skupien", "kind": "person", "label": "Nils Skupien", "url": "https://arxiv.org/abs/2512.03054", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mathias-krohmer-zabaleta", "kind": "person", "label": "Mathias Krohmer Zabaleta", "url": "https://arxiv.org/abs/2512.03054", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:oliver-blanck", "kind": "person", "label": "Oliver Blanck", "url": "https://arxiv.org/abs/2512.03054", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:francesco-cicone", "kind": "person", "label": "Francesco Cicone", "url": "https://arxiv.org/abs/2512.03054", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:giuseppe-lucio-cascini", "kind": "person", "label": "Giuseppe Lucio Cascini", "url": "https://arxiv.org/abs/2512.03054", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:paolo-zaffino", "kind": "person", "label": "Paolo Zaffino", "url": "https://arxiv.org/abs/2512.03054", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2605.14331", "kind": "paper", "label": "Analog RF Computing: A New Paradigm for Energy-Efficient Edge AI Over MU-MIMO Systems", "url": "https://arxiv.org/abs/2605.14331", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:wentao-yu", "kind": "person", "label": "Wentao Yu", "url": "https://arxiv.org/abs/2605.14331", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:vincent-w-s-wong", "kind": "person", "label": "Vincent W. S. Wong", "url": "https://arxiv.org/abs/2605.14331", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:1611.07151", "kind": "paper", "label": "Fast and Energy-Efficient CNN Inference on IoT Devices", "url": "https://arxiv.org/abs/1611.07151", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:mohammad-motamedi", "kind": "person", "label": "Mohammad Motamedi", "url": "https://arxiv.org/abs/1611.07151", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:daniel-fong", "kind": "person", "label": "Daniel Fong", "url": "https://arxiv.org/abs/1611.07151", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:soheil-ghiasi", "kind": "person", "label": "Soheil Ghiasi", "url": "https://arxiv.org/abs/1611.07151", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2406.09322", "kind": "paper", "label": "Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines", "url": "https://arxiv.org/abs/2406.09322", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:yavar-taheri-yeganeh", "kind": "person", "label": "Yavar Taheri Yeganeh", "url": "https://arxiv.org/abs/2406.09322", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mohsen-jafari", "kind": "person", "label": "Mohsen Jafari", "url": "https://arxiv.org/abs/2406.09322", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:andrea-matta", "kind": "person", "label": "Andrea Matta", "url": "https://arxiv.org/abs/2406.09322", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2506.12598", "kind": "paper", "label": "ECLIP: Energy-efficient and Practical Co-Location of ML Inference on Spatially Partitioned GPUs", "url": "https://arxiv.org/abs/2506.12598", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ryan-quach", "kind": "person", "label": "Ryan Quach", "url": "https://arxiv.org/abs/2506.12598", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yidi-wang", "kind": "person", "label": "Yidi Wang", "url": "https://arxiv.org/abs/2506.12598", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ali-jahanshahi", "kind": "person", "label": "Ali Jahanshahi", "url": "https://arxiv.org/abs/2506.12598", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:daniel-wong", "kind": "person", "label": "Daniel Wong", "url": "https://arxiv.org/abs/2506.12598", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:hyoseung-kim", "kind": "person", "label": "Hyoseung Kim", "url": "https://arxiv.org/abs/2506.12598", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2508.12590", "kind": "paper", "label": "Energy-Efficient Wireless LLM Inference via Uncertainty and Importance-Aware Speculative Decoding", "url": "https://arxiv.org/abs/2508.12590", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:jihoon-park", "kind": "person", "label": "Jihoon Park", "url": "https://arxiv.org/abs/2508.12590", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:seungeun-oh", "kind": "person", "label": "Seungeun Oh", "url": "https://arxiv.org/abs/2508.12590", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:seong-lyun-kim", "kind": "person", "label": "Seong-Lyun Kim", "url": "https://arxiv.org/abs/2508.12590", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2606.29629", "kind": "paper", "label": "Energy-Efficient Multimodal Inference Serving with Tri-serve", "url": "https://arxiv.org/abs/2606.29629", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ziyang-jia", "kind": "person", "label": "Ziyang Jia", "url": "https://arxiv.org/abs/2606.29629", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sara-rashidi-golrouye", "kind": "person", "label": "Sara Rashidi Golrouye", "url": "https://arxiv.org/abs/2606.29629", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:laxmi-bhuyan", "kind": "person", "label": "Laxmi Bhuyan", "url": "https://arxiv.org/abs/2606.29629", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:benjamin-kubwimana", "kind": "person", "label": "Benjamin Kubwimana", "url": "https://arxiv.org/abs/2606.29629", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:devashree-tripathy", "kind": "person", "label": "Devashree Tripathy", "url": "https://arxiv.org/abs/2606.29629", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:zexin-li", "kind": "person", "label": "Zexin Li", "url": "https://arxiv.org/abs/2606.29629", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:cong-liu", "kind": "person", "label": "Cong Liu", "url": "https://arxiv.org/abs/2606.29629", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2005.02544", "kind": "paper", "label": "AutoScale: Optimizing Energy Efficiency of End-to-End Edge Inference under Stochastic Variance", "url": "https://arxiv.org/abs/2005.02544", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:young-geun-kim", "kind": "person", "label": "Young Geun Kim", "url": "https://arxiv.org/abs/2005.02544", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:carole-jean-wu", "kind": "person", "label": "Carole-Jean Wu", "url": "https://arxiv.org/abs/2005.02544", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2503.04865", "kind": "paper", "label": "E4: Energy-Efficient DNN Inference for Edge Video Analytics Via Early-Exit and DVFS", "url": "https://arxiv.org/abs/2503.04865", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ziyang-zhang", "kind": "person", "label": "Ziyang Zhang", "url": "https://arxiv.org/abs/2503.04865", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yang-zhao", "kind": "person", "label": "Yang Zhao", "url": "https://arxiv.org/abs/2503.04865", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ming-ching-chang", "kind": "person", "label": "Ming-Ching Chang", "url": "https://arxiv.org/abs/2503.04865", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:changyao-lin", "kind": "person", "label": "Changyao Lin", "url": "https://arxiv.org/abs/2503.04865", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jie-liu", "kind": "person", "label": "Jie Liu", "url": "https://arxiv.org/abs/2503.04865", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2404.19209", "kind": "paper", "label": "AdaOper: Energy-efficient and Responsive Concurrent DNN Inference on Mobile Devices", "url": "https://arxiv.org/abs/2404.19209", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:zheng-lin", "kind": "person", "label": "Zheng Lin", "url": "https://arxiv.org/abs/2404.19209", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:bin-guo", "kind": "person", "label": "Bin Guo", "url": "https://arxiv.org/abs/2404.19209", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sicong-liu", "kind": "person", "label": "Sicong Liu", "url": "https://arxiv.org/abs/2404.19209", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:wentao-zhou", "kind": "person", "label": "Wentao Zhou", "url": "https://arxiv.org/abs/2404.19209", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yasan-ding", "kind": "person", "label": "Yasan Ding", "url": "https://arxiv.org/abs/2404.19209", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:zhiwen-yu", "kind": "person", "label": "Zhiwen Yu", "url": "https://arxiv.org/abs/2404.19209", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2503.00298", "kind": "paper", "label": "Energy-Efficient Edge Inference in Integrated Sensing, Communication, and Computation Networks", "url": "https://arxiv.org/abs/2503.00298", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:jiacheng-yao", "kind": "person", "label": "Jiacheng Yao", "url": "https://arxiv.org/abs/2503.00298", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:wei-xu", "kind": "person", "label": "Wei Xu", "url": "https://arxiv.org/abs/2503.00298", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:guangxu-zhu", "kind": "person", "label": "Guangxu Zhu", "url": "https://arxiv.org/abs/2503.00298", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:kaibin-huang", "kind": "person", "label": "Kaibin Huang", "url": "https://arxiv.org/abs/2503.00298", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:shuguang-cui", "kind": "person", "label": "Shuguang Cui", "url": "https://arxiv.org/abs/2503.00298", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2603.21908", "kind": "paper", "label": "SparseDVFS: Sparse-Aware DVFS for Energy-Efficient Edge Inference", "url": "https://arxiv.org/abs/2603.21908", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:zheshun-wu", "kind": "person", "label": "Zheshun Wu", "url": "https://arxiv.org/abs/2603.21908", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:luca-mottola", "kind": "person", "label": "Luca Mottola", "url": "https://arxiv.org/abs/2603.21908", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2503.18706", "kind": "paper", "label": "Energy-Efficient Dynamic Training and Inference for GNN-Based Network Modeling", "url": "https://arxiv.org/abs/2503.18706", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:chetna-singhal", "kind": "person", "label": "Chetna Singhal", "url": "https://arxiv.org/abs/2503.18706", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yassine-hadjadj-aoul", "kind": "person", "label": "Yassine Hadjadj-Aoul", "url": "https://arxiv.org/abs/2503.18706", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2502.16627", "kind": "paper", "label": "Energy-Efficient Transformer Inference: Optimization Strategies for Time Series Classification", "url": "https://arxiv.org/abs/2502.16627", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:arshia-kermani", "kind": "person", "label": "Arshia Kermani", "url": "https://arxiv.org/abs/2502.16627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ehsan-zeraatkar", "kind": "person", "label": "Ehsan Zeraatkar", "url": "https://arxiv.org/abs/2502.16627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:habib-irani", "kind": "person", "label": "Habib Irani", "url": "https://arxiv.org/abs/2502.16627", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2405.19257", "kind": "paper", "label": "Hybrid-Parallel: Achieving High Performance and Energy Efficient Distributed Inference on Robots", "url": "https://arxiv.org/abs/2405.19257", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:zekai-sun", "kind": "person", "label": "Zekai Sun", "url": "https://arxiv.org/abs/2405.19257", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:xiuxian-guan", "kind": "person", "label": "Xiuxian Guan", "url": "https://arxiv.org/abs/2405.19257", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:junming-wang", "kind": "person", "label": "Junming Wang", "url": "https://arxiv.org/abs/2405.19257", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:haoze-song", "kind": "person", "label": "Haoze Song", "url": "https://arxiv.org/abs/2405.19257", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yuhao-qing", "kind": "person", "label": "Yuhao Qing", "url": "https://arxiv.org/abs/2405.19257", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:tianxiang-shen", "kind": "person", "label": "Tianxiang Shen", "url": "https://arxiv.org/abs/2405.19257", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:dong-huang", "kind": "person", "label": "Dong Huang", "url": "https://arxiv.org/abs/2405.19257", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:fangming-liu", "kind": "person", "label": "Fangming Liu", "url": "https://arxiv.org/abs/2405.19257", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2403.07036", "kind": "paper", "label": "A Converting Autoencoder Toward Low-latency and Energy-efficient DNN Inference at the Edge", "url": "https://arxiv.org/abs/2403.07036", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:hasanul-mahmud", "kind": "person", "label": "Hasanul Mahmud", "url": "https://arxiv.org/abs/2403.07036", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:peng-kang", "kind": "person", "label": "Peng Kang", "url": "https://arxiv.org/abs/2403.07036", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:kevin-desai", "kind": "person", "label": "Kevin Desai", "url": "https://arxiv.org/abs/2403.07036", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:palden-lama", "kind": "person", "label": "Palden Lama", "url": "https://arxiv.org/abs/2403.07036", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sushil-prasad", "kind": "person", "label": "Sushil Prasad", "url": "https://arxiv.org/abs/2403.07036", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2206.04685", "kind": "paper", "label": "Predictive Exit: Prediction of Fine-Grained Early Exits for Computation- and Energy-Efficient Inference", "url": "https://arxiv.org/abs/2206.04685", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:xiangjie-li", "kind": "person", "label": "Xiangjie Li", "url": "https://arxiv.org/abs/2206.04685", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:chenfei-lou", "kind": "person", "label": "Chenfei Lou", "url": "https://arxiv.org/abs/2206.04685", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:zhengping-zhu", "kind": "person", "label": "Zhengping Zhu", "url": "https://arxiv.org/abs/2206.04685", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yuchi-chen", "kind": "person", "label": "Yuchi Chen", "url": "https://arxiv.org/abs/2206.04685", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yingtao-shen", "kind": "person", "label": "Yingtao Shen", "url": "https://arxiv.org/abs/2206.04685", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yehan-ma", "kind": "person", "label": "Yehan Ma", "url": "https://arxiv.org/abs/2206.04685", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:an-zou", "kind": "person", "label": "An Zou", "url": "https://arxiv.org/abs/2206.04685", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2604.27032", "kind": "paper", "label": "LLM-Guided Runtime Parameter Optimization for Energy-Efficient Model Inference", "url": "https://arxiv.org/abs/2604.27032", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:katelyn-crumpacker", "kind": "person", "label": "Katelyn Crumpacker", "url": "https://arxiv.org/abs/2604.27032", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:dimitrios-nikolopoulos", "kind": "person", "label": "Dimitrios Nikolopoulos", "url": "https://arxiv.org/abs/2604.27032", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:1805.07978", "kind": "paper", "label": "Energy-Efficient Inference Accelerator for Memory-Augmented Neural Networks on an FPGA", "url": "https://arxiv.org/abs/1805.07978", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:seongsik-park", "kind": "person", "label": "Seongsik Park", "url": "https://arxiv.org/abs/1805.07978", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jaehee-jang", "kind": "person", "label": "Jaehee Jang", "url": "https://arxiv.org/abs/1805.07978", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:seijoon-kim", "kind": "person", "label": "Seijoon Kim", "url": "https://arxiv.org/abs/1805.07978", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sungroh-yoon", "kind": "person", "label": "Sungroh Yoon", "url": "https://arxiv.org/abs/1805.07978", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2202.02015", "kind": "paper", "label": "Energy-Efficient High-Accuracy Spiking Neural Network Inference Using Time-Domain Neurons", "url": "https://arxiv.org/abs/2202.02015", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:joonghyun-song", "kind": "person", "label": "Joonghyun Song", "url": "https://arxiv.org/abs/2202.02015", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jiwon-shin", "kind": "person", "label": "Jiwon Shin", "url": "https://arxiv.org/abs/2202.02015", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:hanseok-kim", "kind": "person", "label": "Hanseok Kim", "url": "https://arxiv.org/abs/2202.02015", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:woo-seok-choi", "kind": "person", "label": "Woo-Seok Choi", "url": "https://arxiv.org/abs/2202.02015", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2105.11848", "kind": "paper", "label": "DTNN: Energy-efficient Inference with Dendrite Tree Inspired Neural Networks for Edge Vision Applications", "url": "https://arxiv.org/abs/2105.11848", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:tao-luo", "kind": "person", "label": "Tao Luo", "url": "https://arxiv.org/abs/2105.11848", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:wai-teng-tang", "kind": "person", "label": "Wai Teng Tang", "url": "https://arxiv.org/abs/2105.11848", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:matthew-kay-fei-lee", "kind": "person", "label": "Matthew Kay Fei Lee", "url": "https://arxiv.org/abs/2105.11848", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:chuping-qu", "kind": "person", "label": "Chuping Qu", "url": "https://arxiv.org/abs/2105.11848", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:weng-fai-wong", "kind": "person", "label": "Weng-Fai Wong", "url": "https://arxiv.org/abs/2105.11848", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:rick-goh", "kind": "person", "label": "Rick Goh", "url": "https://arxiv.org/abs/2105.11848", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2405.00738", "kind": "paper", "label": "HLSTransform: Energy-Efficient Llama 2 Inference on FPGAs Via High Level Synthesis", "url": "https://arxiv.org/abs/2405.00738", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:andy-he", "kind": "person", "label": "Andy He", "url": "https://arxiv.org/abs/2405.00738", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:darren-key", "kind": "person", "label": "Darren Key", "url": "https://arxiv.org/abs/2405.00738", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mason-bulling", "kind": "person", "label": "Mason Bulling", "url": "https://arxiv.org/abs/2405.00738", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:andrew-chang", "kind": "person", "label": "Andrew Chang", "url": "https://arxiv.org/abs/2405.00738", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:skyler-shapiro", "kind": "person", "label": "Skyler Shapiro", "url": "https://arxiv.org/abs/2405.00738", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:everett-lee", "kind": "person", "label": "Everett Lee", "url": "https://arxiv.org/abs/2405.00738", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:1810.02068", "kind": "paper", "label": "Towards Fast and Energy-Efficient Binarized Neural Network Inference on FPGA", "url": "https://arxiv.org/abs/1810.02068", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:cheng-fu", "kind": "person", "label": "Cheng Fu", "url": "https://arxiv.org/abs/1810.02068", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:shilin-zhu", "kind": "person", "label": "Shilin Zhu", "url": "https://arxiv.org/abs/1810.02068", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:hao-su", "kind": "person", "label": "Hao Su", "url": "https://arxiv.org/abs/1810.02068", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ching-en-lee", "kind": "person", "label": "Ching-En Lee", "url": "https://arxiv.org/abs/1810.02068", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jishen-zhao", "kind": "person", "label": "Jishen Zhao", "url": "https://arxiv.org/abs/1810.02068", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:1910.05340", "kind": "paper", "label": "EDEN: Enabling Energy-Efficient, High-Performance Deep Neural Network Inference Using Approximate DRAM", "url": "https://arxiv.org/abs/1910.05340", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:skanda-koppula", "kind": "person", "label": "Skanda Koppula", "url": "https://arxiv.org/abs/1910.05340", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lois-orosa", "kind": "person", "label": "Lois Orosa", "url": "https://arxiv.org/abs/1910.05340", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:abdullah-giray-ya-l-k", "kind": "person", "label": "Abdullah Giray Ya\u011fl\u0131k\u00e7\u0131", "url": "https://arxiv.org/abs/1910.05340", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:roknoddin-azizi", "kind": "person", "label": "Roknoddin Azizi", "url": "https://arxiv.org/abs/1910.05340", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:taha-shahroodi", "kind": "person", "label": "Taha Shahroodi", "url": "https://arxiv.org/abs/1910.05340", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:konstantinos-kanellopoulos", "kind": "person", "label": "Konstantinos Kanellopoulos", "url": "https://arxiv.org/abs/1910.05340", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:onur-mutlu", "kind": "person", "label": "Onur Mutlu", "url": "https://arxiv.org/abs/1910.05340", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:1907.12475", "kind": "paper", "label": "Energy-Efficient Processing and Robust Wireless Cooperative Transmission for Edge Inference", "url": "https://arxiv.org/abs/1907.12475", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:kai-yang", "kind": "person", "label": "Kai Yang", "url": "https://arxiv.org/abs/1907.12475", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yuanming-shi", "kind": "person", "label": "Yuanming Shi", "url": "https://arxiv.org/abs/1907.12475", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:wei-yu", "kind": "person", "label": "Wei Yu", "url": "https://arxiv.org/abs/1907.12475", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:zhi-ding", "kind": "person", "label": "Zhi Ding", "url": "https://arxiv.org/abs/1907.12475", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2502.05640", "kind": "paper", "label": "ETHEREAL: Energy-efficient and High-throughput Inference using Compressed Tsetlin Machine", "url": "https://arxiv.org/abs/2502.05640", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:shengyu-duan", "kind": "person", "label": "Shengyu Duan", "url": "https://arxiv.org/abs/2502.05640", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:rishad-shafik", "kind": "person", "label": "Rishad Shafik", "url": "https://arxiv.org/abs/2502.05640", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:alex-yakovlev", "kind": "person", "label": "Alex Yakovlev", "url": "https://arxiv.org/abs/2502.05640", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2511.23166", "kind": "paper", "label": "Energy-Efficient Vision Transformer Inference for Edge-AI Deployment", "url": "https://arxiv.org/abs/2511.23166", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:nursultan-amanzhol", "kind": "person", "label": "Nursultan Amanzhol", "url": "https://arxiv.org/abs/2511.23166", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jurn-gyu-park", "kind": "person", "label": "Jurn-Gyu Park", "url": "https://arxiv.org/abs/2511.23166", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2309.03194", "kind": "paper", "label": "Signatures of Bayesian inference emerge from energy efficient synapses", "url": "https://arxiv.org/abs/2309.03194", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:james-malkin", "kind": "person", "label": "James Malkin", "url": "https://arxiv.org/abs/2309.03194", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:cian-o-donnell", "kind": "person", "label": "Cian O'Donnell", "url": "https://arxiv.org/abs/2309.03194", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:conor-houghton", "kind": "person", "label": "Conor Houghton", "url": "https://arxiv.org/abs/2309.03194", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:laurence-aitchison", "kind": "person", "label": "Laurence Aitchison", "url": "https://arxiv.org/abs/2309.03194", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2306.09789", "kind": "paper", "label": "Dynamic Decision Tree Ensembles for Energy-Efficient Inference on IoT Edge Nodes", "url": "https://arxiv.org/abs/2306.09789", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:francesco-daghero", "kind": "person", "label": "Francesco Daghero", "url": "https://arxiv.org/abs/2306.09789", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:alessio-burrello", "kind": "person", "label": "Alessio Burrello", "url": "https://arxiv.org/abs/2306.09789", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:enrico-macii", "kind": "person", "label": "Enrico Macii", "url": "https://arxiv.org/abs/2306.09789", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:paolo-montuschi", "kind": "person", "label": "Paolo Montuschi", "url": "https://arxiv.org/abs/2306.09789", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:massimo-poncino", "kind": "person", "label": "Massimo Poncino", "url": "https://arxiv.org/abs/2306.09789", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:daniele-jahier-pagliari", "kind": "person", "label": "Daniele Jahier Pagliari", "url": "https://arxiv.org/abs/2306.09789", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2108.12648", "kind": "paper", "label": "Energy-efficient neural network inference with microcavity exciton-polaritons", "url": "https://arxiv.org/abs/2108.12648", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:m-matuszewski", "kind": "person", "label": "M. Matuszewski", "url": "https://arxiv.org/abs/2108.12648", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:a-opala", "kind": "person", "label": "A. Opala", "url": "https://arxiv.org/abs/2108.12648", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:r-mirek", "kind": "person", "label": "R. Mirek", "url": "https://arxiv.org/abs/2108.12648", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:m-furman", "kind": "person", "label": "M. Furman", "url": "https://arxiv.org/abs/2108.12648", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:m-kr-l", "kind": "person", "label": "M. Kr\u00f3l", "url": "https://arxiv.org/abs/2108.12648", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:k-tyszka", "kind": "person", "label": "K. Tyszka", "url": "https://arxiv.org/abs/2108.12648", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:t-c-h-liew", "kind": "person", "label": "T. C. H. Liew", "url": "https://arxiv.org/abs/2108.12648", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:d-ballarini", "kind": "person", "label": "D. Ballarini", "url": "https://arxiv.org/abs/2108.12648", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2205.15062", "kind": "paper", "label": "A Transistor Operations Model for Deep Learning Energy Consumption Scaling Law", "url": "https://arxiv.org/abs/2205.15062", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:chen-li", "kind": "person", "label": "Chen Li", "url": "https://arxiv.org/abs/2205.15062", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:antonios-tsourdos", "kind": "person", "label": "Antonios Tsourdos", "url": "https://arxiv.org/abs/2205.15062", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:weisi-guo", "kind": "person", "label": "Weisi Guo", "url": "https://arxiv.org/abs/2205.15062", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2307.00368", "kind": "paper", "label": "Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training", "url": "https://arxiv.org/abs/2307.00368", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:dario-lazzaro", "kind": "person", "label": "Dario Lazzaro", "url": "https://arxiv.org/abs/2307.00368", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:antonio-emanuele-cin", "kind": "person", "label": "Antonio Emanuele Cin\u00e0", "url": "https://arxiv.org/abs/2307.00368", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:maura-pintor", "kind": "person", "label": "Maura Pintor", "url": "https://arxiv.org/abs/2307.00368", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ambra-demontis", "kind": "person", "label": "Ambra Demontis", "url": "https://arxiv.org/abs/2307.00368", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:battista-biggio", "kind": "person", "label": "Battista Biggio", "url": "https://arxiv.org/abs/2307.00368", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:fabio-roli", "kind": "person", "label": "Fabio Roli", "url": "https://arxiv.org/abs/2307.00368", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:marcello-pelillo", "kind": "person", "label": "Marcello Pelillo", "url": "https://arxiv.org/abs/2307.00368", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2307.05520", "kind": "paper", "label": "Estimating Deep Learning energy consumption based on model architecture and training environment", "url": "https://arxiv.org/abs/2307.05520", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:santiago-del-rey", "kind": "person", "label": "Santiago del Rey", "url": "https://arxiv.org/abs/2307.05520", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lu-s-cruz", "kind": "person", "label": "Lu\u00eds Cruz", "url": "https://arxiv.org/abs/2307.05520", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2111.12861", "kind": "paper", "label": "A Deep Learning Approach for Macroscopic Energy Consumption Prediction with Microscopic Quality for Electric Vehicles", "url": "https://arxiv.org/abs/2111.12861", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ayman-moawad", "kind": "person", "label": "Ayman Moawad", "url": "https://arxiv.org/abs/2111.12861", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:krishna-murthy-gurumurthy", "kind": "person", "label": "Krishna Murthy Gurumurthy", "url": "https://arxiv.org/abs/2111.12861", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:omer-verbas", "kind": "person", "label": "Omer Verbas", "url": "https://arxiv.org/abs/2111.12861", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:zhijian-li", "kind": "person", "label": "Zhijian Li", "url": "https://arxiv.org/abs/2111.12861", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ehsan-islam", "kind": "person", "label": "Ehsan Islam", "url": "https://arxiv.org/abs/2111.12861", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:vincent-freyermuth", "kind": "person", "label": "Vincent Freyermuth", "url": "https://arxiv.org/abs/2111.12861", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:aymeric-rousseau", "kind": "person", "label": "Aymeric Rousseau", "url": "https://arxiv.org/abs/2111.12861", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2207.01595", "kind": "paper", "label": "Deep Learning for Short-term Instant Energy Consumption Forecasting in the Manufacturing Sector", "url": "https://arxiv.org/abs/2207.01595", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:nuno-oliveira", "kind": "person", "label": "Nuno Oliveira", "url": "https://arxiv.org/abs/2207.01595", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:norberto-sousa", "kind": "person", "label": "Norberto Sousa", "url": "https://arxiv.org/abs/2207.01595", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:isabel-pra-a", "kind": "person", "label": "Isabel Pra\u00e7a", "url": "https://arxiv.org/abs/2207.01595", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2603.06195", "kind": "paper", "label": "Can Adjusting Hyperparameters Lead to Green Deep Learning: An Empirical Study on Correlations between Hyperparameters and Energy Consumption of Deep Learning Models", "url": "https://arxiv.org/abs/2603.06195", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:taoran-wang", "kind": "person", "label": "Taoran Wang", "url": "https://arxiv.org/abs/2603.06195", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yanhui-li", "kind": "person", "label": "Yanhui Li", "url": "https://arxiv.org/abs/2603.06195", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mingliang-ma", "kind": "person", "label": "Mingliang Ma", "url": "https://arxiv.org/abs/2603.06195", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lin-chen", "kind": "person", "label": "Lin Chen", "url": "https://arxiv.org/abs/2603.06195", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yuming-zhou", "kind": "person", "label": "Yuming Zhou", "url": "https://arxiv.org/abs/2603.06195", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2511.08644", "kind": "paper", "label": "Energy Consumption of Dataframe Libraries for End-to-End Deep Learning Pipelines:A Comparative Analysis", "url": "https://arxiv.org/abs/2511.08644", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:punit-kumar", "kind": "person", "label": "Punit Kumar", "url": "https://arxiv.org/abs/2511.08644", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:asif-imran", "kind": "person", "label": "Asif Imran", "url": "https://arxiv.org/abs/2511.08644", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:tevfik-kosar", "kind": "person", "label": "Tevfik Kosar", "url": "https://arxiv.org/abs/2511.08644", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2501.06099", "kind": "paper", "label": "Explaining Deep Learning-based Anomaly Detection in Energy Consumption Data by Focusing on Contextually Relevant Data", "url": "https://arxiv.org/abs/2501.06099", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:mohammad-noorchenarboo", "kind": "person", "label": "Mohammad Noorchenarboo", "url": "https://arxiv.org/abs/2501.06099", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:katarina-grolinger", "kind": "person", "label": "Katarina Grolinger", "url": "https://arxiv.org/abs/2501.06099", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2108.13465", "kind": "paper", "label": "Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision", "url": "https://arxiv.org/abs/2108.13465", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:xinyang-jiang", "kind": "person", "label": "Xinyang Jiang", "url": "https://arxiv.org/abs/2108.13465", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:donglin-bai", "kind": "person", "label": "Donglin Bai", "url": "https://arxiv.org/abs/2108.13465", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yuge-zhang", "kind": "person", "label": "Yuge Zhang", "url": "https://arxiv.org/abs/2108.13465", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ningxin-zheng", "kind": "person", "label": "Ningxin Zheng", "url": "https://arxiv.org/abs/2108.13465", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:xuanyi-dong", "kind": "person", "label": "Xuanyi Dong", "url": "https://arxiv.org/abs/2108.13465", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lu-liu", "kind": "person", "label": "Lu Liu", "url": "https://arxiv.org/abs/2108.13465", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yuqing-yang", "kind": "person", "label": "Yuqing Yang", "url": "https://arxiv.org/abs/2108.13465", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2212.00582", "kind": "paper", "label": "Understanding the Energy Consumption of HPC Scale Artificial Intelligence", "url": "https://arxiv.org/abs/2212.00582", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:danilo-carastan-dos-santos", "kind": "person", "label": "Danilo Carastan dos Santos", "url": "https://arxiv.org/abs/2212.00582", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2203.08630", "kind": "paper", "label": "Extended vehicle energy dataset (eVED): an enhanced large-scale dataset for deep learning on vehicle trip energy consumption", "url": "https://arxiv.org/abs/2203.08630", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:shiliang-zhang", "kind": "person", "label": "Shiliang Zhang", "url": "https://arxiv.org/abs/2203.08630", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:dyako-fatih", "kind": "person", "label": "Dyako Fatih", "url": "https://arxiv.org/abs/2203.08630", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:fahmi-abdulqadir", "kind": "person", "label": "Fahmi Abdulqadir", "url": "https://arxiv.org/abs/2203.08630", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:tobias-schwarz", "kind": "person", "label": "Tobias Schwarz", "url": "https://arxiv.org/abs/2203.08630", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:xuehui-ma", "kind": "person", "label": "Xuehui Ma", "url": "https://arxiv.org/abs/2203.08630", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2107.02621", "kind": "paper", "label": "Energy Consumption of Deep Generative Audio Models", "url": "https://arxiv.org/abs/2107.02621", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:constance-douwes", "kind": "person", "label": "Constance Douwes", "url": "https://arxiv.org/abs/2107.02621", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:philippe-esling", "kind": "person", "label": "Philippe Esling", "url": "https://arxiv.org/abs/2107.02621", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jean-pierre-briot", "kind": "person", "label": "Jean-Pierre Briot", "url": "https://arxiv.org/abs/2107.02621", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:1810.10090", "kind": "paper", "label": "NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Vision", "url": "https://arxiv.org/abs/1810.10090", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:biyi-fang", "kind": "person", "label": "Biyi Fang", "url": "https://arxiv.org/abs/1810.10090", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:xiao-zeng", "kind": "person", "label": "Xiao Zeng", "url": "https://arxiv.org/abs/1810.10090", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mi-zhang", "kind": "person", "label": "Mi Zhang", "url": "https://arxiv.org/abs/1810.10090", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2210.06015", "kind": "paper", "label": "EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search", "url": "https://arxiv.org/abs/2210.06015", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:pedram-bakhtiarifard", "kind": "person", "label": "Pedram Bakhtiarifard", "url": "https://arxiv.org/abs/2210.06015", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:christian-igel", "kind": "person", "label": "Christian Igel", "url": "https://arxiv.org/abs/2210.06015", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2207.06883", "kind": "paper", "label": "RF-Photonic Deep Learning Processor with Shannon-Limited Data Movement", "url": "https://arxiv.org/abs/2207.06883", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ronald-davis", "kind": "person", "label": "Ronald Davis", "url": "https://arxiv.org/abs/2207.06883", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:zaijun-chen", "kind": "person", "label": "Zaijun Chen", "url": "https://arxiv.org/abs/2207.06883", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ryan-hamerly", "kind": "person", "label": "Ryan Hamerly", "url": "https://arxiv.org/abs/2207.06883", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:dirk-englund", "kind": "person", "label": "Dirk Englund", "url": "https://arxiv.org/abs/2207.06883", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2206.01609", "kind": "paper", "label": "A Comparative Study on Energy Consumption Models for Drones", "url": "https://arxiv.org/abs/2206.01609", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:carlos-muli", "kind": "person", "label": "Carlos Muli", "url": "https://arxiv.org/abs/2206.01609", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sangyoung-park", "kind": "person", "label": "Sangyoung Park", "url": "https://arxiv.org/abs/2206.01609", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mingming-liu", "kind": "person", "label": "Mingming Liu", "url": "https://arxiv.org/abs/2206.01609", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2409.08763", "kind": "paper", "label": "Energy Consumption Trends in Sound Event Detection Systems", "url": "https://arxiv.org/abs/2409.08763", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:romain-serizel", "kind": "person", "label": "Romain Serizel", "url": "https://arxiv.org/abs/2409.08763", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2212.01698", "kind": "paper", "label": "Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads", "url": "https://arxiv.org/abs/2212.01698", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ren-caspart", "kind": "person", "label": "Ren\u00e9 Caspart", "url": "https://arxiv.org/abs/2212.01698", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sebastian-ziegler", "kind": "person", "label": "Sebastian Ziegler", "url": "https://arxiv.org/abs/2212.01698", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:arvid-weyrauch", "kind": "person", "label": "Arvid Weyrauch", "url": "https://arxiv.org/abs/2212.01698", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:holger-obermaier", "kind": "person", "label": "Holger Obermaier", "url": "https://arxiv.org/abs/2212.01698", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:simon-raffeiner", "kind": "person", "label": "Simon Raffeiner", "url": "https://arxiv.org/abs/2212.01698", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:leon-pascal-schuhmacher", "kind": "person", "label": "Leon Pascal Schuhmacher", "url": "https://arxiv.org/abs/2212.01698", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jan-scholtyssek", "kind": "person", "label": "Jan Scholtyssek", "url": "https://arxiv.org/abs/2212.01698", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:darya-trofimova", "kind": "person", "label": "Darya Trofimova", "url": "https://arxiv.org/abs/2212.01698", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2410.14107", "kind": "paper", "label": "Transfer Learning on Transformers for Building Energy Consumption Forecasting -- A Comparative Study", "url": "https://arxiv.org/abs/2410.14107", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:robert-spencer", "kind": "person", "label": "Robert Spencer", "url": "https://arxiv.org/abs/2410.14107", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:surangika-ranathunga", "kind": "person", "label": "Surangika Ranathunga", "url": "https://arxiv.org/abs/2410.14107", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mikael-boulic", "kind": "person", "label": "Mikael Boulic", "url": "https://arxiv.org/abs/2410.14107", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:andries-van-heerden", "kind": "person", "label": "Andries van Heerden", "url": "https://arxiv.org/abs/2410.14107", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2303.01980", "kind": "paper", "label": "Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle", "url": "https://arxiv.org/abs/2303.01980", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:vanessa-mehlin", "kind": "person", "label": "Vanessa Mehlin", "url": "https://arxiv.org/abs/2303.01980", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sigurd-schacht", "kind": "person", "label": "Sigurd Schacht", "url": "https://arxiv.org/abs/2303.01980", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:carsten-lanquillon", "kind": "person", "label": "Carsten Lanquillon", "url": "https://arxiv.org/abs/2303.01980", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2207.11953", "kind": "paper", "label": "Deep Learning for Forecasting the Energy Consumption in Public Buildings", "url": "https://arxiv.org/abs/2207.11953", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:viorica-rozina-chifu", "kind": "person", "label": "Viorica Rozina Chifu", "url": "https://arxiv.org/abs/2207.11953", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:cristina-bianca-pop", "kind": "person", "label": "Cristina Bianca Pop", "url": "https://arxiv.org/abs/2207.11953", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:emil-st-chifu", "kind": "person", "label": "Emil St. Chifu", "url": "https://arxiv.org/abs/2207.11953", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:horatiu-barleanu", "kind": "person", "label": "Horatiu Barleanu", "url": "https://arxiv.org/abs/2207.11953", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2601.17110", "kind": "paper", "label": "Forecasting Energy Consumption using Recurrent Neural Networks: A Comparative Analysis", "url": "https://arxiv.org/abs/2601.17110", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:abhishek-maity", "kind": "person", "label": "Abhishek Maity", "url": "https://arxiv.org/abs/2601.17110", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:viraj-tukarul", "kind": "person", "label": "Viraj Tukarul", "url": "https://arxiv.org/abs/2601.17110", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2210.01625", "kind": "paper", "label": "Energy Consumption of Neural Networks on NVIDIA Edge Boards: an Empirical Model", "url": "https://arxiv.org/abs/2210.01625", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:seyyidahmed-lahmer", "kind": "person", "label": "Seyyidahmed Lahmer", "url": "https://arxiv.org/abs/2210.01625", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:aria-khoshsirat", "kind": "person", "label": "Aria Khoshsirat", "url": "https://arxiv.org/abs/2210.01625", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:michele-rossi", "kind": "person", "label": "Michele Rossi", "url": "https://arxiv.org/abs/2210.01625", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:andrea-zanella", "kind": "person", "label": "Andrea Zanella", "url": "https://arxiv.org/abs/2210.01625", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2304.00897", "kind": "paper", "label": "Accuracy is not the only Metric that matters: Estimating the Energy Consumption of Deep Learning Models", "url": "https://arxiv.org/abs/2304.00897", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:johannes-getzner", "kind": "person", "label": "Johannes Getzner", "url": "https://arxiv.org/abs/2304.00897", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:bertrand-charpentier", "kind": "person", "label": "Bertrand Charpentier", "url": "https://arxiv.org/abs/2304.00897", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:stephan-g-nnemann", "kind": "person", "label": "Stephan G\u00fcnnemann", "url": "https://arxiv.org/abs/2304.00897", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:1906.04278", "kind": "paper", "label": "Performance Analysis and Characterization of Training Deep Learning Models on Mobile Devices", "url": "https://arxiv.org/abs/1906.04278", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:jiawen-liu", "kind": "person", "label": "Jiawen Liu", "url": "https://arxiv.org/abs/1906.04278", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:wan-du", "kind": "person", "label": "Wan Du", "url": "https://arxiv.org/abs/1906.04278", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2411.14421", "kind": "paper", "label": "From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption", "url": "https://arxiv.org/abs/2411.14421", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:shourya-bose", "kind": "person", "label": "Shourya Bose", "url": "https://arxiv.org/abs/2411.14421", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yijiang-li", "kind": "person", "label": "Yijiang Li", "url": "https://arxiv.org/abs/2411.14421", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:amy-van-sant", "kind": "person", "label": "Amy Van Sant", "url": "https://arxiv.org/abs/2411.14421", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:kibaek-kim", "kind": "person", "label": "Kibaek Kim", "url": "https://arxiv.org/abs/2411.14421", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2310.06522", "kind": "paper", "label": "Watt For What: Rethinking Deep Learning's Energy-Performance Relationship", "url": "https://arxiv.org/abs/2310.06522", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:shreyank-n-gowda", "kind": "person", "label": "Shreyank N Gowda", "url": "https://arxiv.org/abs/2310.06522", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:xinyue-hao", "kind": "person", "label": "Xinyue Hao", "url": "https://arxiv.org/abs/2310.06522", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:gen-li", "kind": "person", "label": "Gen Li", "url": "https://arxiv.org/abs/2310.06522", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:shashank-narayana-gowda", "kind": "person", "label": "Shashank Narayana Gowda", "url": "https://arxiv.org/abs/2310.06522", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:xiaobo-jin", "kind": "person", "label": "Xiaobo Jin", "url": "https://arxiv.org/abs/2310.06522", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:laura-sevilla-lara", "kind": "person", "label": "Laura Sevilla-Lara", "url": "https://arxiv.org/abs/2310.06522", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2403.08151", "kind": "paper", "label": "Measuring the Energy Consumption and Efficiency of Deep Neural Networks: An Empirical Analysis and Design Recommendations", "url": "https://arxiv.org/abs/2403.08151", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:charles-edison-tripp", "kind": "person", "label": "Charles Edison Tripp", "url": "https://arxiv.org/abs/2403.08151", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jordan-perr-sauer", "kind": "person", "label": "Jordan Perr-Sauer", "url": "https://arxiv.org/abs/2403.08151", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jamil-gafur", "kind": "person", "label": "Jamil Gafur", "url": "https://arxiv.org/abs/2403.08151", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:amabarish-nag", "kind": "person", "label": "Amabarish Nag", "url": "https://arxiv.org/abs/2403.08151", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:avi-purkayastha", "kind": "person", "label": "Avi Purkayastha", "url": "https://arxiv.org/abs/2403.08151", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sagi-zisman", "kind": "person", "label": "Sagi Zisman", "url": "https://arxiv.org/abs/2403.08151", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:erik-a-bensen", "kind": "person", "label": "Erik A. Bensen", "url": "https://arxiv.org/abs/2403.08151", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2406.16929", "kind": "paper", "label": "Modelling the 5G Energy Consumption using Real-world Data: Energy Fingerprint is All You Need", "url": "https://arxiv.org/abs/2406.16929", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:tingwei-chen", "kind": "person", "label": "Tingwei Chen", "url": "https://arxiv.org/abs/2406.16929", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yantao-wang", "kind": "person", "label": "Yantao Wang", "url": "https://arxiv.org/abs/2406.16929", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:hanzhi-chen", "kind": "person", "label": "Hanzhi Chen", "url": "https://arxiv.org/abs/2406.16929", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:zijian-zhao", "kind": "person", "label": "Zijian Zhao", "url": "https://arxiv.org/abs/2406.16929", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:nicola-piovesan", "kind": "person", "label": "Nicola Piovesan", "url": "https://arxiv.org/abs/2406.16929", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:qingjiang-shi", "kind": "person", "label": "Qingjiang Shi", "url": "https://arxiv.org/abs/2406.16929", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2007.03828", "kind": "paper", "label": "Deep Ensemble Analysis for Imaging X-ray Polarimetry", "url": "https://arxiv.org/abs/2007.03828", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:a-l-peirson", "kind": "person", "label": "A. L. Peirson", "url": "https://arxiv.org/abs/2007.03828", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:r-w-romani", "kind": "person", "label": "R. W. Romani", "url": "https://arxiv.org/abs/2007.03828", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:h-l-marshall", "kind": "person", "label": "H. L. Marshall", "url": "https://arxiv.org/abs/2007.03828", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:j-f-steiner", "kind": "person", "label": "J. F. Steiner", "url": "https://arxiv.org/abs/2007.03828", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:l-baldini", "kind": "person", "label": "L. Baldini", "url": "https://arxiv.org/abs/2007.03828", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2205.12961", "kind": "paper", "label": "Position: Tensor Networks are a Valuable Asset for Green AI", "url": "https://arxiv.org/abs/2205.12961", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:eva-memmel", "kind": "person", "label": "Eva Memmel", "url": "https://arxiv.org/abs/2205.12961", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:clara-menzen", "kind": "person", "label": "Clara Menzen", "url": "https://arxiv.org/abs/2205.12961", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jetze-schuurmans", "kind": "person", "label": "Jetze Schuurmans", "url": "https://arxiv.org/abs/2205.12961", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:frederiek-wesel", "kind": "person", "label": "Frederiek Wesel", "url": "https://arxiv.org/abs/2205.12961", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:kim-batselier", "kind": "person", "label": "Kim Batselier", "url": "https://arxiv.org/abs/2205.12961", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2506.12262", "kind": "paper", "label": "Energy-Efficient Green AI Architectures for Circular Economies Through Multi-Layered Sustainable Resource Optimization Framework", "url": "https://arxiv.org/abs/2506.12262", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ripal-ranpara", "kind": "person", "label": "Ripal Ranpara", "url": "https://arxiv.org/abs/2506.12262", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2303.13972", "kind": "paper", "label": "Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI", "url": "https://arxiv.org/abs/2303.13972", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:tim-yarally", "kind": "person", "label": "Tim Yarally", "url": "https://arxiv.org/abs/2303.13972", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:daniel-feitosa", "kind": "person", "label": "Daniel Feitosa", "url": "https://arxiv.org/abs/2303.13972", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:june-sallou", "kind": "person", "label": "June Sallou", "url": "https://arxiv.org/abs/2303.13972", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:arie-van-deursen", "kind": "person", "label": "Arie van Deursen", "url": "https://arxiv.org/abs/2303.13972", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2403.04736", "kind": "paper", "label": "Benchmarking News Recommendation in the Era of Green AI", "url": "https://arxiv.org/abs/2403.04736", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:qijiong-liu", "kind": "person", "label": "Qijiong Liu", "url": "https://arxiv.org/abs/2403.04736", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:xiao-ming-wu", "kind": "person", "label": "Xiao-Ming Wu", "url": "https://arxiv.org/abs/2403.04736", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2606.14707", "kind": "paper", "label": "Green AI Carbon Optimizer: Carbon-Efficient Training Location Recommendation and Global AI Energy Demand Forecasting", "url": "https://arxiv.org/abs/2606.14707", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:yuxin-chen", "kind": "person", "label": "Yuxin Chen", "url": "https://arxiv.org/abs/2606.14707", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:chujie-zou", "kind": "person", "label": "Chujie Zou", "url": "https://arxiv.org/abs/2606.14707", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2505.07317", "kind": "paper", "label": "How Do Companies Manage the Environmental Sustainability of AI? An Interview Study About Green AI Efforts and Regulations", "url": "https://arxiv.org/abs/2505.07317", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ashmita-sampatsing", "kind": "person", "label": "Ashmita Sampatsing", "url": "https://arxiv.org/abs/2505.07317", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sophie-vos", "kind": "person", "label": "Sophie Vos", "url": "https://arxiv.org/abs/2505.07317", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:emma-beauxis-aussalet", "kind": "person", "label": "Emma Beauxis-Aussalet", "url": "https://arxiv.org/abs/2505.07317", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2309.13192", "kind": "paper", "label": "Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation", "url": "https://arxiv.org/abs/2309.13192", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:kai-huang", "kind": "person", "label": "Kai Huang", "url": "https://arxiv.org/abs/2309.13192", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:hanyun-yin", "kind": "person", "label": "Hanyun Yin", "url": "https://arxiv.org/abs/2309.13192", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:heng-huang", "kind": "person", "label": "Heng Huang", "url": "https://arxiv.org/abs/2309.13192", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:wei-gao", "kind": "person", "label": "Wei Gao", "url": "https://arxiv.org/abs/2309.13192", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2401.06195", "kind": "paper", "label": "NeuSpin: Design of a Reliable Edge Neuromorphic System Based on Spintronics for Green AI", "url": "https://arxiv.org/abs/2401.06195", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:soyed-tuhin-ahmed", "kind": "person", "label": "Soyed Tuhin Ahmed", "url": "https://arxiv.org/abs/2401.06195", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:kamal-danouchi", "kind": "person", "label": "Kamal Danouchi", "url": "https://arxiv.org/abs/2401.06195", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:guillaume-prenat", "kind": "person", "label": "Guillaume Prenat", "url": "https://arxiv.org/abs/2401.06195", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lorena-anghel", "kind": "person", "label": "Lorena Anghel", "url": "https://arxiv.org/abs/2401.06195", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mehdi-b-tahoori", "kind": "person", "label": "Mehdi B. Tahoori", "url": "https://arxiv.org/abs/2401.06195", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2204.02766", "kind": "paper", "label": "Data-Centric Green AI: An Exploratory Empirical Study", "url": "https://arxiv.org/abs/2204.02766", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:roberto-verdecchia", "kind": "person", "label": "Roberto Verdecchia", "url": "https://arxiv.org/abs/2204.02766", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:michelle-lin", "kind": "person", "label": "Michelle Lin", "url": "https://arxiv.org/abs/2204.02766", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:james-wickenden", "kind": "person", "label": "James Wickenden", "url": "https://arxiv.org/abs/2204.02766", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:estelle-hotellier", "kind": "person", "label": "Estelle Hotellier", "url": "https://arxiv.org/abs/2204.02766", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2405.17451", "kind": "paper", "label": "Green AI in Action: Strategic Model Selection for Ensembles in Production", "url": "https://arxiv.org/abs/2405.17451", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:nienke-nijkamp", "kind": "person", "label": "Nienke Nijkamp", "url": "https://arxiv.org/abs/2405.17451", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:niels-van-der-heijden", "kind": "person", "label": "Niels van der Heijden", "url": "https://arxiv.org/abs/2405.17451", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2408.01752", "kind": "paper", "label": "Advancing Green AI: Efficient and Accurate Lightweight CNNs for Rice Leaf Disease Identification", "url": "https://arxiv.org/abs/2408.01752", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:khairun-saddami", "kind": "person", "label": "Khairun Saddami", "url": "https://arxiv.org/abs/2408.01752", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yudha-nurdin", "kind": "person", "label": "Yudha Nurdin", "url": "https://arxiv.org/abs/2408.01752", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:mutia-zahramita", "kind": "person", "label": "Mutia Zahramita", "url": "https://arxiv.org/abs/2408.01752", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:muhammad-shahreeza-safiruz", "kind": "person", "label": "Muhammad Shahreeza Safiruz", "url": "https://arxiv.org/abs/2408.01752", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2307.09964", "kind": "paper", "label": "Towards green AI-based software systems: an architecture-centric approach (GAISSA)", "url": "https://arxiv.org/abs/2307.09964", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:francisco-dur-n", "kind": "person", "label": "Francisco Dur\u00e1n", "url": "https://arxiv.org/abs/2307.09964", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2509.02250", "kind": "paper", "label": "TREE:Token-Responsive Energy Efficiency Framework For Green AI-Integrated 6G Networks", "url": "https://arxiv.org/abs/2509.02250", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:kaixuan-huang", "kind": "person", "label": "Kaixuan Huang", "url": "https://arxiv.org/abs/2509.02250", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:tengsheng-wang", "kind": "person", "label": "Tengsheng Wang", "url": "https://arxiv.org/abs/2509.02250", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jihong-li", "kind": "person", "label": "Jihong Li", "url": "https://arxiv.org/abs/2509.02250", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:shunqing-zhang", "kind": "person", "label": "Shunqing Zhang", "url": "https://arxiv.org/abs/2509.02250", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:shuangfeng-han", "kind": "person", "label": "Shuangfeng Han", "url": "https://arxiv.org/abs/2509.02250", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:xiaoyun-wang", "kind": "person", "label": "Xiaoyun Wang", "url": "https://arxiv.org/abs/2509.02250", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:qunsong-zeng", "kind": "person", "label": "Qunsong Zeng", "url": "https://arxiv.org/abs/2509.02250", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2411.08069", "kind": "paper", "label": "Intelligent Green Efficiency for Intrusion Detection", "url": "https://arxiv.org/abs/2411.08069", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:pedro-pereira", "kind": "person", "label": "Pedro Pereira", "url": "https://arxiv.org/abs/2411.08069", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:paulo-mendes", "kind": "person", "label": "Paulo Mendes", "url": "https://arxiv.org/abs/2411.08069", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jo-o-vitorino", "kind": "person", "label": "Jo\u00e3o Vitorino", "url": "https://arxiv.org/abs/2411.08069", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:eva-maia", "kind": "person", "label": "Eva Maia", "url": "https://arxiv.org/abs/2411.08069", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2103.15429", "kind": "paper", "label": "Efficient Explanations from Empirical Explainers", "url": "https://arxiv.org/abs/2103.15429", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:robert-schwarzenberg", "kind": "person", "label": "Robert Schwarzenberg", "url": "https://arxiv.org/abs/2103.15429", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:nils-feldhus", "kind": "person", "label": "Nils Feldhus", "url": "https://arxiv.org/abs/2103.15429", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sebastian-m-ller", "kind": "person", "label": "Sebastian M\u00f6ller", "url": "https://arxiv.org/abs/2103.15429", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2407.02914", "kind": "paper", "label": "The More the Merrier? Navigating Accuracy vs. Energy Efficiency Design Trade-Offs in Ensemble Learning Systems", "url": "https://arxiv.org/abs/2407.02914", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:rafiullah-omar", "kind": "person", "label": "Rafiullah Omar", "url": "https://arxiv.org/abs/2407.02914", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:henry-muccini", "kind": "person", "label": "Henry Muccini", "url": "https://arxiv.org/abs/2407.02914", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:patricia-lago", "kind": "person", "label": "Patricia Lago", "url": "https://arxiv.org/abs/2407.02914", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2508.00924", "kind": "paper", "label": "XAutoLM: Efficient Fine-Tuning of Language Models via Meta-Learning and AutoML", "url": "https://arxiv.org/abs/2508.00924", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ernesto-l-estevanell-valladares", "kind": "person", "label": "Ernesto L. Estevanell-Valladares", "url": "https://arxiv.org/abs/2508.00924", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:suilan-estevez-velarde", "kind": "person", "label": "Suilan Estevez-Velarde", "url": "https://arxiv.org/abs/2508.00924", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yoan-guti-rrez", "kind": "person", "label": "Yoan Guti\u00e9rrez", "url": "https://arxiv.org/abs/2508.00924", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:andr-s-montoyo", "kind": "person", "label": "Andr\u00e9s Montoyo", "url": "https://arxiv.org/abs/2508.00924", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ruslan-mitkov", "kind": "person", "label": "Ruslan Mitkov", "url": "https://arxiv.org/abs/2508.00924", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2402.12010", "kind": "paper", "label": "Training Green AI Models Using Elite Samples", "url": "https://arxiv.org/abs/2402.12010", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:mohammed-alswaitti", "kind": "person", "label": "Mohammed Alswaitti", "url": "https://arxiv.org/abs/2402.12010", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:gr-goire-danoy", "kind": "person", "label": "Gr\u00e9goire Danoy", "url": "https://arxiv.org/abs/2402.12010", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:pascal-bouvry", "kind": "person", "label": "Pascal Bouvry", "url": "https://arxiv.org/abs/2402.12010", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:johnatan-pecero", "kind": "person", "label": "Johnatan Pecero", "url": "https://arxiv.org/abs/2402.12010", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2512.07001", "kind": "paper", "label": "Synergies between AI Computing and Power Systems: Metrics, Scheduling, and Resilience", "url": "https://arxiv.org/abs/2512.07001", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:farzaneh-pourahmadi", "kind": "person", "label": "Farzaneh Pourahmadi", "url": "https://arxiv.org/abs/2512.07001", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:olivier-corradi", "kind": "person", "label": "Olivier Corradi", "url": "https://arxiv.org/abs/2512.07001", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:pierre-pinson", "kind": "person", "label": "Pierre Pinson", "url": "https://arxiv.org/abs/2512.07001", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2602.00240", "kind": "paper", "label": "Green-NAS: A Global-Scale Multi-Objective Neural Architecture Search for Robust and Efficient Edge-Native Weather Forecasting", "url": "https://arxiv.org/abs/2602.00240", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:md-muhtasim-munif-fahim", "kind": "person", "label": "Md Muhtasim Munif Fahim", "url": "https://arxiv.org/abs/2602.00240", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:soyda-humyra-yesmin", "kind": "person", "label": "Soyda Humyra Yesmin", "url": "https://arxiv.org/abs/2602.00240", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:saiful-islam", "kind": "person", "label": "Saiful Islam", "url": "https://arxiv.org/abs/2602.00240", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:md-palash-bin-faruque", "kind": "person", "label": "Md. Palash Bin Faruque", "url": "https://arxiv.org/abs/2602.00240", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:md-a-salam", "kind": "person", "label": "Md. A. Salam", "url": "https://arxiv.org/abs/2602.00240", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:md-mahfuz-uddin", "kind": "person", "label": "Md. Mahfuz Uddin", "url": "https://arxiv.org/abs/2602.00240", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:samiul-islam", "kind": "person", "label": "Samiul Islam", "url": "https://arxiv.org/abs/2602.00240", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:tofayel-ahmed", "kind": "person", "label": "Tofayel Ahmed", "url": "https://arxiv.org/abs/2602.00240", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2603.21418", "kind": "paper", "label": "Efficient Fine-Tuning Methods for Portuguese Question Answering: A Comparative Study of PEFT on BERTimbau and Exploratory Evaluation of Generative LLMs", "url": "https://arxiv.org/abs/2603.21418", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:mariela-m-nina", "kind": "person", "label": "Mariela M. Nina", "url": "https://arxiv.org/abs/2603.21418", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:caio-veloso-costa", "kind": "person", "label": "Caio Veloso Costa", "url": "https://arxiv.org/abs/2603.21418", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:lilian-berton", "kind": "person", "label": "Lilian Berton", "url": "https://arxiv.org/abs/2603.21418", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:didier-a-vega-oliveros", "kind": "person", "label": "Didier A. Vega-Oliveros", "url": "https://arxiv.org/abs/2603.21418", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2510.02810", "kind": "paper", "label": "Dissecting Transformers: A CLEAR Perspective towards Green AI", "url": "https://arxiv.org/abs/2510.02810", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:shailender-goyal", "kind": "person", "label": "Shailender Goyal", "url": "https://arxiv.org/abs/2510.02810", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:divyansh-pandey", "kind": "person", "label": "Divyansh Pandey", "url": "https://arxiv.org/abs/2510.02810", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2307.11434", "kind": "paper", "label": "Batching for Green AI -- An Exploratory Study on Inference", "url": "https://arxiv.org/abs/2307.11434", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:paper:2312.05795", "kind": "paper", "label": "Large Multimodal Model Compression via Efficient Pruning and Distillation at AntGroup", "url": "https://arxiv.org/abs/2312.05795", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:maolin-wang", "kind": "person", "label": "Maolin Wang", "url": "https://arxiv.org/abs/2312.05795", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yao-zhao", "kind": "person", "label": "Yao Zhao", "url": "https://arxiv.org/abs/2312.05795", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jiajia-liu", "kind": "person", "label": "Jiajia Liu", "url": "https://arxiv.org/abs/2312.05795", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jingdong-chen", "kind": "person", "label": "Jingdong Chen", "url": "https://arxiv.org/abs/2312.05795", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:chenyi-zhuang", "kind": "person", "label": "Chenyi Zhuang", "url": "https://arxiv.org/abs/2312.05795", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jinjie-gu", "kind": "person", "label": "Jinjie Gu", "url": "https://arxiv.org/abs/2312.05795", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ruocheng-guo", "kind": "person", "label": "Ruocheng Guo", "url": "https://arxiv.org/abs/2312.05795", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:xiangyu-zhao", "kind": "person", "label": "Xiangyu Zhao", "url": "https://arxiv.org/abs/2312.05795", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2305.08197", "kind": "paper", "label": "A Dataset Fusion Algorithm for Generalised Anomaly Detection in Homogeneous Periodic Time Series Datasets", "url": "https://arxiv.org/abs/2305.08197", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:ayman-elhalwagy", "kind": "person", "label": "Ayman Elhalwagy", "url": "https://arxiv.org/abs/2305.08197", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:tatiana-kalganova", "kind": "person", "label": "Tatiana Kalganova", "url": "https://arxiv.org/abs/2305.08197", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2106.07597", "kind": "paper", "label": "MLPerf Tiny Benchmark", "url": "https://arxiv.org/abs/2106.07597", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:peter-torelli", "kind": "person", "label": "Peter Torelli", "url": "https://arxiv.org/abs/2106.07597", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jeremy-holleman", "kind": "person", "label": "Jeremy Holleman", "url": "https://arxiv.org/abs/2106.07597", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:nat-jeffries", "kind": "person", "label": "Nat Jeffries", "url": "https://arxiv.org/abs/2106.07597", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:csaba-kiraly", "kind": "person", "label": "Csaba Kiraly", "url": "https://arxiv.org/abs/2106.07597", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:pietro-montino", "kind": "person", "label": "Pietro Montino", "url": "https://arxiv.org/abs/2106.07597", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:david-kanter", "kind": "person", "label": "David Kanter", "url": "https://arxiv.org/abs/2106.07597", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2410.12032", "kind": "paper", "label": "MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI", "url": "https://arxiv.org/abs/2410.12032", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:arya-tschand", "kind": "person", "label": "Arya Tschand", "url": "https://arxiv.org/abs/2410.12032", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:arun-tejusve-raghunath-rajan", "kind": "person", "label": "Arun Tejusve Raghunath Rajan", "url": "https://arxiv.org/abs/2410.12032", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sachin-idgunji", "kind": "person", "label": "Sachin Idgunji", "url": "https://arxiv.org/abs/2410.12032", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:anirban-ghosh", "kind": "person", "label": "Anirban Ghosh", "url": "https://arxiv.org/abs/2410.12032", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:pawan-ambalkar", "kind": "person", "label": "Pawan Ambalkar", "url": "https://arxiv.org/abs/2410.12032", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:ritika-borkar", "kind": "person", "label": "Ritika Borkar", "url": "https://arxiv.org/abs/2410.12032", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:1911.02549", "kind": "paper", "label": "MLPerf Inference Benchmark", "url": "https://arxiv.org/abs/1911.02549", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:christine-cheng", "kind": "person", "label": "Christine Cheng", "url": "https://arxiv.org/abs/1911.02549", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:peter-mattson", "kind": "person", "label": "Peter Mattson", "url": "https://arxiv.org/abs/1911.02549", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:guenther-schmuelling", "kind": "person", "label": "Guenther Schmuelling", "url": "https://arxiv.org/abs/1911.02549", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:brian-anderson", "kind": "person", "label": "Brian Anderson", "url": "https://arxiv.org/abs/1911.02549", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:maximilien-breughe", "kind": "person", "label": "Maximilien Breughe", "url": "https://arxiv.org/abs/1911.02549", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2406.16791", "kind": "paper", "label": "Enabling more efficient and cost-effective AI/ML systems with Collective Mind, virtualized MLOps, MLPerf, Collective Knowledge Playground and reproducible optimization tournaments", "url": "https://arxiv.org/abs/2406.16791", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:grigori-fursin", "kind": "person", "label": "Grigori Fursin", "url": "https://arxiv.org/abs/2406.16791", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2606.27704", "kind": "paper", "label": "AdvScan: Black-Box Adversarial Example Detection at Runtime through Power Analysis", "url": "https://arxiv.org/abs/2606.27704", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:robi-paul", "kind": "person", "label": "Robi Paul", "url": "https://arxiv.org/abs/2606.27704", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:michael-zuzak", "kind": "person", "label": "Michael Zuzak", "url": "https://arxiv.org/abs/2606.27704", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2206.00302", "kind": "paper", "label": "Multi-Complexity-Loss DNAS for Energy-Efficient and Memory-Constrained Deep Neural Networks", "url": "https://arxiv.org/abs/2206.00302", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:matteo-risso", "kind": "person", "label": "Matteo Risso", "url": "https://arxiv.org/abs/2206.00302", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:luca-benini", "kind": "person", "label": "Luca Benini", "url": "https://arxiv.org/abs/2206.00302", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2008.07141", "kind": "paper", "label": "AIPerf: Automated machine learning as an AI-HPC benchmark", "url": "https://arxiv.org/abs/2008.07141", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:zhixiang-ren", "kind": "person", "label": "Zhixiang Ren", "url": "https://arxiv.org/abs/2008.07141", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yongheng-liu", "kind": "person", "label": "Yongheng Liu", "url": "https://arxiv.org/abs/2008.07141", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:tianhui-shi", "kind": "person", "label": "Tianhui Shi", "url": "https://arxiv.org/abs/2008.07141", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:jidong-zhai", "kind": "person", "label": "Jidong Zhai", "url": "https://arxiv.org/abs/2008.07141", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:youhui-zhang", "kind": "person", "label": "Youhui Zhang", "url": "https://arxiv.org/abs/2008.07141", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:yunquan-zhang", "kind": "person", "label": "Yunquan Zhang", "url": "https://arxiv.org/abs/2008.07141", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2105.09187", "kind": "paper", "label": "High performance and energy efficient inference for deep learning on ARM processors", "url": "https://arxiv.org/abs/2105.09187", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:adri-n-castell", "kind": "person", "label": "Adri\u00e1n Castell\u00f3", "url": "https://arxiv.org/abs/2105.09187", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:sergio-barrachina", "kind": "person", "label": "Sergio Barrachina", "url": "https://arxiv.org/abs/2105.09187", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:manuel-f-dolz", "kind": "person", "label": "Manuel F. Dolz", "url": "https://arxiv.org/abs/2105.09187", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:enrique-s-quintana-ort", "kind": "person", "label": "Enrique S. Quintana-Ort\u00ed", "url": "https://arxiv.org/abs/2105.09187", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:person:pau-san-juan", "kind": "person", "label": "Pau San Juan", "url": "https://arxiv.org/abs/2105.09187", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2310.07217", "kind": "paper", "label": "Enhancing Neural Architecture Search with Multiple Hardware Constraints for Deep Learning Model Deployment on Tiny IoT Devices", "url": "https://arxiv.org/abs/2310.07217", "source": "arxiv", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:person:beatrice-alessandra-motetti", "kind": "person", "label": "Beatrice Alessandra Motetti", "url": "https://arxiv.org/abs/2310.07217", "source": "arxiv-author", "axis": "energy", "layer": 0}
{"type": "node", "id": "p2:paper:2207.08536", "kind": "paper", "label": "UniFusion: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird's-Eye-View", "url": "https://arxiv.org/abs/2207.08536", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zequn-qin", "kind": "person", "label": "Zequn Qin", "url": "https://arxiv.org/abs/2207.08536", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jingyu-chen", "kind": "person", "label": "Jingyu Chen", "url": "https://arxiv.org/abs/2207.08536", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chao-chen", "kind": "person", "label": "Chao Chen", "url": "https://arxiv.org/abs/2207.08536", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaozhi-chen", "kind": "person", "label": "Xiaozhi Chen", "url": "https://arxiv.org/abs/2207.08536", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xi-li", "kind": "person", "label": "Xi Li", "url": "https://arxiv.org/abs/2207.08536", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2309.05257", "kind": "paper", "label": "FusionFormer: A Multi-sensory Fusion in Bird's-Eye-View and Temporal Consistent Transformer for 3D Object Detection", "url": "https://arxiv.org/abs/2309.05257", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chunyong-hu", "kind": "person", "label": "Chunyong Hu", "url": "https://arxiv.org/abs/2309.05257", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hang-zheng", "kind": "person", "label": "Hang Zheng", "url": "https://arxiv.org/abs/2309.05257", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:kun-li", "kind": "person", "label": "Kun Li", "url": "https://arxiv.org/abs/2309.05257", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jianyun-xu", "kind": "person", "label": "Jianyun Xu", "url": "https://arxiv.org/abs/2309.05257", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:weibo-mao", "kind": "person", "label": "Weibo Mao", "url": "https://arxiv.org/abs/2309.05257", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:maochun-luo", "kind": "person", "label": "Maochun Luo", "url": "https://arxiv.org/abs/2309.05257", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lingxuan-wang", "kind": "person", "label": "Lingxuan Wang", "url": "https://arxiv.org/abs/2309.05257", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:mingxia-chen", "kind": "person", "label": "Mingxia Chen", "url": "https://arxiv.org/abs/2309.05257", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2309.15465", "kind": "paper", "label": "Cross-Dataset Experimental Study of Radar-Camera Fusion in Bird's-Eye View", "url": "https://arxiv.org/abs/2309.15465", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lukas-st-cker", "kind": "person", "label": "Lukas St\u00e4cker", "url": "https://arxiv.org/abs/2309.15465", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:philipp-heidenreich", "kind": "person", "label": "Philipp Heidenreich", "url": "https://arxiv.org/abs/2309.15465", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jason-rambach", "kind": "person", "label": "Jason Rambach", "url": "https://arxiv.org/abs/2309.15465", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:didier-stricker", "kind": "person", "label": "Didier Stricker", "url": "https://arxiv.org/abs/2309.15465", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2603.05623", "kind": "paper", "label": "Post Fusion Bird's Eye View Feature Stabilization for Robust Multimodal 3D Detection", "url": "https://arxiv.org/abs/2603.05623", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:trung-tien-dong", "kind": "person", "label": "Trung Tien Dong", "url": "https://arxiv.org/abs/2603.05623", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:dev-thakkar", "kind": "person", "label": "Dev Thakkar", "url": "https://arxiv.org/abs/2603.05623", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:arman-sargolzaei", "kind": "person", "label": "Arman Sargolzaei", "url": "https://arxiv.org/abs/2603.05623", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaomin-lin", "kind": "person", "label": "Xiaomin Lin", "url": "https://arxiv.org/abs/2603.05623", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2310.06008", "kind": "paper", "label": "CoBEVFusion: Cooperative Perception with LiDAR-Camera Bird's-Eye View Fusion", "url": "https://arxiv.org/abs/2310.06008", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:donghao-qiao", "kind": "person", "label": "Donghao Qiao", "url": "https://arxiv.org/abs/2310.06008", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:farhana-zulkernine", "kind": "person", "label": "Farhana Zulkernine", "url": "https://arxiv.org/abs/2310.06008", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2507.03381", "kind": "paper", "label": "Evaluation of an Uncertainty-Aware Late Fusion Algorithm for Multi-Source Bird's Eye View Detections Under Controlled Noise", "url": "https://arxiv.org/abs/2507.03381", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:maryem-fadili", "kind": "person", "label": "Maryem Fadili", "url": "https://arxiv.org/abs/2507.03381", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:louis-lecrosnier", "kind": "person", "label": "Louis Lecrosnier", "url": "https://arxiv.org/abs/2507.03381", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:steve-pechberti", "kind": "person", "label": "Steve Pechberti", "url": "https://arxiv.org/abs/2507.03381", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:redouane-khemmar", "kind": "person", "label": "Redouane Khemmar", "url": "https://arxiv.org/abs/2507.03381", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2303.17099", "kind": "paper", "label": "BEVFusion4D: Learning LiDAR-Camera Fusion Under Bird's-Eye-View via Cross-Modality Guidance and Temporal Aggregation", "url": "https://arxiv.org/abs/2303.17099", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hongxiang-cai", "kind": "person", "label": "Hongxiang Cai", "url": "https://arxiv.org/abs/2303.17099", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zeyuan-zhang", "kind": "person", "label": "Zeyuan Zhang", "url": "https://arxiv.org/abs/2303.17099", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhenyu-zhou", "kind": "person", "label": "Zhenyu Zhou", "url": "https://arxiv.org/abs/2303.17099", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ziyin-li", "kind": "person", "label": "Ziyin Li", "url": "https://arxiv.org/abs/2303.17099", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wenbo-ding", "kind": "person", "label": "Wenbo Ding", "url": "https://arxiv.org/abs/2303.17099", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiuhua-zhao", "kind": "person", "label": "Jiuhua Zhao", "url": "https://arxiv.org/abs/2303.17099", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2306.04540", "kind": "paper", "label": "NeMO: Neural Map Growing System for Spatiotemporal Fusion in Bird's-Eye-View and BDD-Map Benchmark", "url": "https://arxiv.org/abs/2306.04540", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xi-zhu", "kind": "person", "label": "Xi Zhu", "url": "https://arxiv.org/abs/2306.04540", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiya-cao", "kind": "person", "label": "Xiya Cao", "url": "https://arxiv.org/abs/2306.04540", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhiwei-dong", "kind": "person", "label": "Zhiwei Dong", "url": "https://arxiv.org/abs/2306.04540", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:caifa-zhou", "kind": "person", "label": "Caifa Zhou", "url": "https://arxiv.org/abs/2306.04540", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:qiangbo-liu", "kind": "person", "label": "Qiangbo Liu", "url": "https://arxiv.org/abs/2306.04540", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wei-li", "kind": "person", "label": "Wei Li", "url": "https://arxiv.org/abs/2306.04540", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yongliang-wang", "kind": "person", "label": "Yongliang Wang", "url": "https://arxiv.org/abs/2306.04540", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2402.00637", "kind": "paper", "label": "Fisheye Camera and Ultrasonic Sensor Fusion For Near-Field Obstacle Perception in Bird's-Eye-View", "url": "https://arxiv.org/abs/2402.00637", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:arindam-das", "kind": "person", "label": "Arindam Das", "url": "https://arxiv.org/abs/2402.00637", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:sudarshan-paul", "kind": "person", "label": "Sudarshan Paul", "url": "https://arxiv.org/abs/2402.00637", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:niko-scholz", "kind": "person", "label": "Niko Scholz", "url": "https://arxiv.org/abs/2402.00637", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:akhilesh-kumar-malviya", "kind": "person", "label": "Akhilesh Kumar Malviya", "url": "https://arxiv.org/abs/2402.00637", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ganesh-sistu", "kind": "person", "label": "Ganesh Sistu", "url": "https://arxiv.org/abs/2402.00637", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ujjwal-bhattacharya", "kind": "person", "label": "Ujjwal Bhattacharya", "url": "https://arxiv.org/abs/2402.00637", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ciar-n-eising", "kind": "person", "label": "Ciar\u00e1n Eising", "url": "https://arxiv.org/abs/2402.00637", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2104.10490", "kind": "paper", "label": "FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Cameras", "url": "https://arxiv.org/abs/2104.10490", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:anthony-hu", "kind": "person", "label": "Anthony Hu", "url": "https://arxiv.org/abs/2104.10490", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zak-murez", "kind": "person", "label": "Zak Murez", "url": "https://arxiv.org/abs/2104.10490", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:nikhil-mohan", "kind": "person", "label": "Nikhil Mohan", "url": "https://arxiv.org/abs/2104.10490", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:sof-a-dudas", "kind": "person", "label": "Sof\u00eda Dudas", "url": "https://arxiv.org/abs/2104.10490", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jeffrey-hawke", "kind": "person", "label": "Jeffrey Hawke", "url": "https://arxiv.org/abs/2104.10490", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:vijay-badrinarayanan", "kind": "person", "label": "Vijay Badrinarayanan", "url": "https://arxiv.org/abs/2104.10490", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:roberto-cipolla", "kind": "person", "label": "Roberto Cipolla", "url": "https://arxiv.org/abs/2104.10490", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:alex-kendall", "kind": "person", "label": "Alex Kendall", "url": "https://arxiv.org/abs/2104.10490", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2205.13542", "kind": "paper", "label": "BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation", "url": "https://arxiv.org/abs/2205.13542", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhijian-liu", "kind": "person", "label": "Zhijian Liu", "url": "https://arxiv.org/abs/2205.13542", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:haotian-tang", "kind": "person", "label": "Haotian Tang", "url": "https://arxiv.org/abs/2205.13542", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:alexander-amini", "kind": "person", "label": "Alexander Amini", "url": "https://arxiv.org/abs/2205.13542", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xinyu-yang", "kind": "person", "label": "Xinyu Yang", "url": "https://arxiv.org/abs/2205.13542", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:huizi-mao", "kind": "person", "label": "Huizi Mao", "url": "https://arxiv.org/abs/2205.13542", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:daniela-rus", "kind": "person", "label": "Daniela Rus", "url": "https://arxiv.org/abs/2205.13542", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:song-han", "kind": "person", "label": "Song Han", "url": "https://arxiv.org/abs/2205.13542", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2309.11119", "kind": "paper", "label": "BroadBEV: Collaborative LiDAR-camera Fusion for Broad-sighted Bird's Eye View Map Construction", "url": "https://arxiv.org/abs/2309.11119", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:minsu-kim", "kind": "person", "label": "Minsu Kim", "url": "https://arxiv.org/abs/2309.11119", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:giseop-kim", "kind": "person", "label": "Giseop Kim", "url": "https://arxiv.org/abs/2309.11119", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:kyong-hwan-jin", "kind": "person", "label": "Kyong Hwan Jin", "url": "https://arxiv.org/abs/2309.11119", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:sunwook-choi", "kind": "person", "label": "Sunwook Choi", "url": "https://arxiv.org/abs/2309.11119", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2305.15883", "kind": "paper", "label": "RC-BEVFusion: A Plug-In Module for Radar-Camera Bird's Eye View Feature Fusion", "url": "https://arxiv.org/abs/2305.15883", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shashank-mishra", "kind": "person", "label": "Shashank Mishra", "url": "https://arxiv.org/abs/2305.15883", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2510.24688", "kind": "paper", "label": "MIC-BEV: Multi-Infrastructure Camera Bird's-Eye-View Transformer with Relation-Aware Fusion for 3D Object Detection", "url": "https://arxiv.org/abs/2510.24688", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yun-zhang", "kind": "person", "label": "Yun Zhang", "url": "https://arxiv.org/abs/2510.24688", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhaoliang-zheng", "kind": "person", "label": "Zhaoliang Zheng", "url": "https://arxiv.org/abs/2510.24688", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:johnson-liu", "kind": "person", "label": "Johnson Liu", "url": "https://arxiv.org/abs/2510.24688", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhiyu-huang", "kind": "person", "label": "Zhiyu Huang", "url": "https://arxiv.org/abs/2510.24688", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zewei-zhou", "kind": "person", "label": "Zewei Zhou", "url": "https://arxiv.org/abs/2510.24688", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zonglin-meng", "kind": "person", "label": "Zonglin Meng", "url": "https://arxiv.org/abs/2510.24688", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tianhui-cai", "kind": "person", "label": "Tianhui Cai", "url": "https://arxiv.org/abs/2510.24688", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiaqi-ma", "kind": "person", "label": "Jiaqi Ma", "url": "https://arxiv.org/abs/2510.24688", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2308.06530", "kind": "paper", "label": "BEV-DG: Cross-Modal Learning under Bird's-Eye View for Domain Generalization of 3D Semantic Segmentation", "url": "https://arxiv.org/abs/2308.06530", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:miaoyu-li", "kind": "person", "label": "Miaoyu Li", "url": "https://arxiv.org/abs/2308.06530", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yachao-zhang", "kind": "person", "label": "Yachao Zhang", "url": "https://arxiv.org/abs/2308.06530", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xu-ma", "kind": "person", "label": "Xu MA", "url": "https://arxiv.org/abs/2308.06530", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yanyun-qu", "kind": "person", "label": "Yanyun Qu", "url": "https://arxiv.org/abs/2308.06530", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yun-fu", "kind": "person", "label": "Yun Fu", "url": "https://arxiv.org/abs/2308.06530", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2410.07268", "kind": "paper", "label": "Learning Content-Aware Multi-Modal Joint Input Pruning via Bird's-Eye-View Representation", "url": "https://arxiv.org/abs/2410.07268", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yuxin-li", "kind": "person", "label": "Yuxin Li", "url": "https://arxiv.org/abs/2410.07268", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yiheng-li", "kind": "person", "label": "Yiheng Li", "url": "https://arxiv.org/abs/2410.07268", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xulei-yang", "kind": "person", "label": "Xulei Yang", "url": "https://arxiv.org/abs/2410.07268", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:mengying-yu", "kind": "person", "label": "Mengying Yu", "url": "https://arxiv.org/abs/2410.07268", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zihang-huang", "kind": "person", "label": "Zihang Huang", "url": "https://arxiv.org/abs/2410.07268", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaojun-wu", "kind": "person", "label": "Xiaojun Wu", "url": "https://arxiv.org/abs/2410.07268", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chai-kiat-yeo", "kind": "person", "label": "Chai Kiat Yeo", "url": "https://arxiv.org/abs/2410.07268", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2206.13294", "kind": "paper", "label": "LaRa: Latents and Rays for Multi-Camera Bird's-Eye-View Semantic Segmentation", "url": "https://arxiv.org/abs/2206.13294", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:florent-bartoccioni", "kind": "person", "label": "Florent Bartoccioni", "url": "https://arxiv.org/abs/2206.13294", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:loi-zablocki", "kind": "person", "label": "\u00c9loi Zablocki", "url": "https://arxiv.org/abs/2206.13294", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:andrei-bursuc", "kind": "person", "label": "Andrei Bursuc", "url": "https://arxiv.org/abs/2206.13294", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:patrick-p-rez", "kind": "person", "label": "Patrick P\u00e9rez", "url": "https://arxiv.org/abs/2206.13294", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:matthieu-cord", "kind": "person", "label": "Matthieu Cord", "url": "https://arxiv.org/abs/2206.13294", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:karteek-alahari", "kind": "person", "label": "Karteek Alahari", "url": "https://arxiv.org/abs/2206.13294", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2310.13350", "kind": "paper", "label": "EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye View", "url": "https://arxiv.org/abs/2310.13350", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:torben-teepe", "kind": "person", "label": "Torben Teepe", "url": "https://arxiv.org/abs/2310.13350", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:philipp-wolters", "kind": "person", "label": "Philipp Wolters", "url": "https://arxiv.org/abs/2310.13350", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:johannes-gilg", "kind": "person", "label": "Johannes Gilg", "url": "https://arxiv.org/abs/2310.13350", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:fabian-herzog", "kind": "person", "label": "Fabian Herzog", "url": "https://arxiv.org/abs/2310.13350", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:gerhard-rigoll", "kind": "person", "label": "Gerhard Rigoll", "url": "https://arxiv.org/abs/2310.13350", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2209.05324", "kind": "paper", "label": "Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe", "url": "https://arxiv.org/abs/2209.05324", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hongyang-li", "kind": "person", "label": "Hongyang Li", "url": "https://arxiv.org/abs/2209.05324", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chonghao-sima", "kind": "person", "label": "Chonghao Sima", "url": "https://arxiv.org/abs/2209.05324", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jifeng-dai", "kind": "person", "label": "Jifeng Dai", "url": "https://arxiv.org/abs/2209.05324", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wenhai-wang", "kind": "person", "label": "Wenhai Wang", "url": "https://arxiv.org/abs/2209.05324", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lewei-lu", "kind": "person", "label": "Lewei Lu", "url": "https://arxiv.org/abs/2209.05324", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:huijie-wang", "kind": "person", "label": "Huijie Wang", "url": "https://arxiv.org/abs/2209.05324", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jia-zeng", "kind": "person", "label": "Jia Zeng", "url": "https://arxiv.org/abs/2209.05324", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhiqi-li", "kind": "person", "label": "Zhiqi Li", "url": "https://arxiv.org/abs/2209.05324", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2403.15241", "kind": "paper", "label": "IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection", "url": "https://arxiv.org/abs/2403.15241", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:junbo-yin", "kind": "person", "label": "Junbo Yin", "url": "https://arxiv.org/abs/2403.15241", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jianbing-shen", "kind": "person", "label": "Jianbing Shen", "url": "https://arxiv.org/abs/2403.15241", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:runnan-chen", "kind": "person", "label": "Runnan Chen", "url": "https://arxiv.org/abs/2403.15241", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ruigang-yang", "kind": "person", "label": "Ruigang Yang", "url": "https://arxiv.org/abs/2403.15241", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:pascal-frossard", "kind": "person", "label": "Pascal Frossard", "url": "https://arxiv.org/abs/2403.15241", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wenguan-wang", "kind": "person", "label": "Wenguan Wang", "url": "https://arxiv.org/abs/2403.15241", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2512.19082", "kind": "paper", "label": "BEVCooper: Accurate and Communication-Efficient Bird's-Eye-View Perception in Vehicular Networks", "url": "https://arxiv.org/abs/2512.19082", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiawei-hou", "kind": "person", "label": "Jiawei Hou", "url": "https://arxiv.org/abs/2512.19082", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:peng-yang", "kind": "person", "label": "Peng Yang", "url": "https://arxiv.org/abs/2512.19082", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiangxiang-dai", "kind": "person", "label": "Xiangxiang Dai", "url": "https://arxiv.org/abs/2512.19082", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:mingliu-liu", "kind": "person", "label": "Mingliu Liu", "url": "https://arxiv.org/abs/2512.19082", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2411.13311", "kind": "paper", "label": "A Resource Efficient Fusion Network for Object Detection in Bird's-Eye View using Camera and Raw Radar Data", "url": "https://arxiv.org/abs/2411.13311", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:kavin-chandrasekaran", "kind": "person", "label": "Kavin Chandrasekaran", "url": "https://arxiv.org/abs/2411.13311", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:sorin-grigorescu", "kind": "person", "label": "Sorin Grigorescu", "url": "https://arxiv.org/abs/2411.13311", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:gijs-dubbelman", "kind": "person", "label": "Gijs Dubbelman", "url": "https://arxiv.org/abs/2411.13311", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:pavol-jancura", "kind": "person", "label": "Pavol Jancura", "url": "https://arxiv.org/abs/2411.13311", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2309.08180", "kind": "paper", "label": "AVM-SLAM: Semantic Visual SLAM with Multi-Sensor Fusion in a Bird's Eye View for Automated Valet Parking", "url": "https://arxiv.org/abs/2309.08180", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ye-li", "kind": "person", "label": "Ye Li", "url": "https://arxiv.org/abs/2309.08180", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wenchao-yang", "kind": "person", "label": "Wenchao Yang", "url": "https://arxiv.org/abs/2309.08180", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:dekun-lin", "kind": "person", "label": "Dekun Lin", "url": "https://arxiv.org/abs/2309.08180", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:qianlei-wang", "kind": "person", "label": "Qianlei Wang", "url": "https://arxiv.org/abs/2309.08180", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhe-cui", "kind": "person", "label": "Zhe Cui", "url": "https://arxiv.org/abs/2309.08180", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaolin-qin", "kind": "person", "label": "Xiaolin Qin", "url": "https://arxiv.org/abs/2309.08180", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2405.10577", "kind": "paper", "label": "DuoSpaceNet: Leveraging Both Bird's-Eye-View and Perspective View Representations for 3D Object Detection", "url": "https://arxiv.org/abs/2405.10577", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhe-huang", "kind": "person", "label": "Zhe Huang", "url": "https://arxiv.org/abs/2405.10577", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yizhe-zhao", "kind": "person", "label": "Yizhe Zhao", "url": "https://arxiv.org/abs/2405.10577", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hao-xiao", "kind": "person", "label": "Hao Xiao", "url": "https://arxiv.org/abs/2405.10577", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chenyan-wu", "kind": "person", "label": "Chenyan Wu", "url": "https://arxiv.org/abs/2405.10577", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lingting-ge", "kind": "person", "label": "Lingting Ge", "url": "https://arxiv.org/abs/2405.10577", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2306.03810", "kind": "paper", "label": "X-Align++: cross-modal cross-view alignment for Bird's-eye-view segmentation", "url": "https://arxiv.org/abs/2306.03810", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shubhankar-borse", "kind": "person", "label": "Shubhankar Borse", "url": "https://arxiv.org/abs/2306.03810", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:senthil-yogamani", "kind": "person", "label": "Senthil Yogamani", "url": "https://arxiv.org/abs/2306.03810", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:marvin-klingner", "kind": "person", "label": "Marvin Klingner", "url": "https://arxiv.org/abs/2306.03810", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:varun-ravi", "kind": "person", "label": "Varun Ravi", "url": "https://arxiv.org/abs/2306.03810", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:abdulaziz-almuzairee", "kind": "person", "label": "Abdulaziz Almuzairee", "url": "https://arxiv.org/abs/2306.03810", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:fatih-porikli", "kind": "person", "label": "Fatih Porikli", "url": "https://arxiv.org/abs/2306.03810", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2507.08644", "kind": "paper", "label": "OnlineBEV: Recurrent Temporal Fusion in Bird's Eye View Representations for Multi-Camera 3D Perception", "url": "https://arxiv.org/abs/2507.08644", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:junho-koh", "kind": "person", "label": "Junho Koh", "url": "https://arxiv.org/abs/2507.08644", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:youngwoo-lee", "kind": "person", "label": "Youngwoo Lee", "url": "https://arxiv.org/abs/2507.08644", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jungho-kim", "kind": "person", "label": "Jungho Kim", "url": "https://arxiv.org/abs/2507.08644", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:dongyoung-lee", "kind": "person", "label": "Dongyoung Lee", "url": "https://arxiv.org/abs/2507.08644", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jun-won-choi", "kind": "person", "label": "Jun Won Choi", "url": "https://arxiv.org/abs/2507.08644", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2210.06778", "kind": "paper", "label": "X-Align: Cross-Modal Cross-View Alignment for Bird's-Eye-View Segmentation", "url": "https://arxiv.org/abs/2210.06778", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:varun-ravi-kumar", "kind": "person", "label": "Varun Ravi Kumar", "url": "https://arxiv.org/abs/2210.06778", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2411.09077", "kind": "paper", "label": "Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data", "url": "https://arxiv.org/abs/2411.09077", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:mariusz-wisniewski", "kind": "person", "label": "Mariusz Wisniewski", "url": "https://arxiv.org/abs/2411.09077", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:zeeshan-a-rana", "kind": "person", "label": "Zeeshan A. Rana", "url": "https://arxiv.org/abs/2411.09077", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:ivan-petrunin", "kind": "person", "label": "Ivan Petrunin", "url": "https://arxiv.org/abs/2411.09077", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:alan-holt", "kind": "person", "label": "Alan Holt", "url": "https://arxiv.org/abs/2411.09077", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:stephen-harman", "kind": "person", "label": "Stephen Harman", "url": "https://arxiv.org/abs/2411.09077", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2212.01436", "kind": "paper", "label": "Unauthorized Drone Detection: Experiments and Prototypes", "url": "https://arxiv.org/abs/2212.01436", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:muhammad-asif-khan", "kind": "person", "label": "Muhammad Asif Khan", "url": "https://arxiv.org/abs/2212.01436", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:hamid-menouar", "kind": "person", "label": "Hamid Menouar", "url": "https://arxiv.org/abs/2212.01436", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:osama-muhammad-khalid", "kind": "person", "label": "Osama Muhammad Khalid", "url": "https://arxiv.org/abs/2212.01436", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:adnan-abu-dayya", "kind": "person", "label": "Adnan Abu-Dayya", "url": "https://arxiv.org/abs/2212.01436", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2007.07396", "kind": "paper", "label": "Real-Time Drone Detection and Tracking With Visible, Thermal and Acoustic Sensors", "url": "https://arxiv.org/abs/2007.07396", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:fredrik-svanstrom", "kind": "person", "label": "Fredrik Svanstrom", "url": "https://arxiv.org/abs/2007.07396", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:cristofer-englund", "kind": "person", "label": "Cristofer Englund", "url": "https://arxiv.org/abs/2007.07396", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:fernando-alonso-fernandez", "kind": "person", "label": "Fernando Alonso-Fernandez", "url": "https://arxiv.org/abs/2007.07396", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2111.12389", "kind": "paper", "label": "Track Boosting and Synthetic Data Aided Drone Detection", "url": "https://arxiv.org/abs/2111.12389", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:fatih-cagatay-akyon", "kind": "person", "label": "Fatih Cagatay Akyon", "url": "https://arxiv.org/abs/2111.12389", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:ogulcan-eryuksel", "kind": "person", "label": "Ogulcan Eryuksel", "url": "https://arxiv.org/abs/2111.12389", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:kamil-anil-ozfuttu", "kind": "person", "label": "Kamil Anil Ozfuttu", "url": "https://arxiv.org/abs/2111.12389", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:sinan-onur-altinuc", "kind": "person", "label": "Sinan Onur Altinuc", "url": "https://arxiv.org/abs/2111.12389", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2402.07259", "kind": "paper", "label": "RIS-Augmented Millimeter-Wave MIMO Systems for Passive Drone Detection", "url": "https://arxiv.org/abs/2402.07259", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:jiguang-he", "kind": "person", "label": "Jiguang He", "url": "https://arxiv.org/abs/2402.07259", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:aymen-fakhreddine", "kind": "person", "label": "Aymen Fakhreddine", "url": "https://arxiv.org/abs/2402.07259", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:george-c-alexandropoulos", "kind": "person", "label": "George C. Alexandropoulos", "url": "https://arxiv.org/abs/2402.07259", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2306.06797", "kind": "paper", "label": "VBSF-TLD: Validation-Based Approach for Soft Computing-Inspired Transfer Learning in Drone Detection", "url": "https://arxiv.org/abs/2306.06797", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:jaskaran-singh", "kind": "person", "label": "Jaskaran Singh", "url": "https://arxiv.org/abs/2306.06797", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2406.18624", "kind": "paper", "label": "Robust Low-Cost Drone Detection and Classification in Low SNR Environments", "url": "https://arxiv.org/abs/2406.18624", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:stefan-gl-ge", "kind": "person", "label": "Stefan Gl\u00fcge", "url": "https://arxiv.org/abs/2406.18624", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:matthias-nyfeler", "kind": "person", "label": "Matthias Nyfeler", "url": "https://arxiv.org/abs/2406.18624", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:ahmad-aghaebrahimian", "kind": "person", "label": "Ahmad Aghaebrahimian", "url": "https://arxiv.org/abs/2406.18624", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:nicola-ramagnano", "kind": "person", "label": "Nicola Ramagnano", "url": "https://arxiv.org/abs/2406.18624", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:christof-sch-pbach", "kind": "person", "label": "Christof Sch\u00fcpbach", "url": "https://arxiv.org/abs/2406.18624", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2603.06265", "kind": "paper", "label": "ODD-SEC: Onboard Drone Detection with a Spinning Event Camera", "url": "https://arxiv.org/abs/2603.06265", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:kuan-dai", "kind": "person", "label": "Kuan Dai", "url": "https://arxiv.org/abs/2603.06265", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:hongxin-zhang", "kind": "person", "label": "Hongxin Zhang", "url": "https://arxiv.org/abs/2603.06265", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:sheng-zhong", "kind": "person", "label": "Sheng Zhong", "url": "https://arxiv.org/abs/2603.06265", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:yi-zhou", "kind": "person", "label": "Yi Zhou", "url": "https://arxiv.org/abs/2603.06265", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2411.05633", "kind": "paper", "label": "SynDroneVision: A Synthetic Dataset for Image-Based Drone Detection", "url": "https://arxiv.org/abs/2411.05633", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:tamara-r-lenhard", "kind": "person", "label": "Tamara R. Lenhard", "url": "https://arxiv.org/abs/2411.05633", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:andreas-weinmann", "kind": "person", "label": "Andreas Weinmann", "url": "https://arxiv.org/abs/2411.05633", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:kai-franke", "kind": "person", "label": "Kai Franke", "url": "https://arxiv.org/abs/2411.05633", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:tobias-koch", "kind": "person", "label": "Tobias Koch", "url": "https://arxiv.org/abs/2411.05633", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2409.16099", "kind": "paper", "label": "Neuromorphic Drone Detection: an Event-RGB Multimodal Approach", "url": "https://arxiv.org/abs/2409.16099", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:gabriele-magrini", "kind": "person", "label": "Gabriele Magrini", "url": "https://arxiv.org/abs/2409.16099", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:federico-becattini", "kind": "person", "label": "Federico Becattini", "url": "https://arxiv.org/abs/2409.16099", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:pietro-pala", "kind": "person", "label": "Pietro Pala", "url": "https://arxiv.org/abs/2409.16099", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:alberto-del-bimbo", "kind": "person", "label": "Alberto Del Bimbo", "url": "https://arxiv.org/abs/2409.16099", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:antonio-porta", "kind": "person", "label": "Antonio Porta", "url": "https://arxiv.org/abs/2409.16099", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2307.10326", "kind": "paper", "label": "Introduction to Drone Detection Radar with Emphasis on Automatic Target Recognition (ATR) technology", "url": "https://arxiv.org/abs/2307.10326", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:jiangkun-gong", "kind": "person", "label": "Jiangkun Gong", "url": "https://arxiv.org/abs/2307.10326", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:deyong-kong", "kind": "person", "label": "Deyong Kong", "url": "https://arxiv.org/abs/2307.10326", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:deren-li", "kind": "person", "label": "Deren Li", "url": "https://arxiv.org/abs/2307.10326", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2508.03331", "kind": "paper", "label": "LRDDv2: Enhanced Long-Range Drone Detection Dataset with Range Information and Comprehensive Real-World Challenges", "url": "https://arxiv.org/abs/2508.03331", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:amirreza-rouhi", "kind": "person", "label": "Amirreza Rouhi", "url": "https://arxiv.org/abs/2508.03331", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:sneh-patel", "kind": "person", "label": "Sneh Patel", "url": "https://arxiv.org/abs/2508.03331", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:noah-mccarthy", "kind": "person", "label": "Noah McCarthy", "url": "https://arxiv.org/abs/2508.03331", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:siddiqa-khan", "kind": "person", "label": "Siddiqa Khan", "url": "https://arxiv.org/abs/2508.03331", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:hadi-khorsand", "kind": "person", "label": "Hadi Khorsand", "url": "https://arxiv.org/abs/2508.03331", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:kaleb-lefkowitz", "kind": "person", "label": "Kaleb Lefkowitz", "url": "https://arxiv.org/abs/2508.03331", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:david-k-han", "kind": "person", "label": "David K. Han", "url": "https://arxiv.org/abs/2508.03331", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2406.11641", "kind": "paper", "label": "YOLO-FEDER FusionNet: A Novel Deep Learning Architecture for Drone Detection", "url": "https://arxiv.org/abs/2406.11641", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:stefan-j-ger", "kind": "person", "label": "Stefan J\u00e4ger", "url": "https://arxiv.org/abs/2406.11641", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2202.09097", "kind": "paper", "label": "Lightweight Multi-Drone Detection and 3D-Localization via YOLO", "url": "https://arxiv.org/abs/2202.09097", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:aryan-sharma", "kind": "person", "label": "Aryan Sharma", "url": "https://arxiv.org/abs/2202.09097", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:nitik-jain", "kind": "person", "label": "Nitik Jain", "url": "https://arxiv.org/abs/2202.09097", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:mangal-kothari", "kind": "person", "label": "Mangal Kothari", "url": "https://arxiv.org/abs/2202.09097", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2111.01888", "kind": "paper", "label": "A dataset for multi-sensor drone detection", "url": "https://arxiv.org/abs/2111.01888", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:fredrik-svanstr-m", "kind": "person", "label": "Fredrik Svanstr\u00f6m", "url": "https://arxiv.org/abs/2111.01888", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2509.19119", "kind": "paper", "label": "Enabling Drone Detection with SWARM Repeater-Assisted MIMO ISAC", "url": "https://arxiv.org/abs/2509.19119", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:palatip-jopanya", "kind": "person", "label": "Palatip Jopanya", "url": "https://arxiv.org/abs/2509.19119", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:diana-p-m-osorio", "kind": "person", "label": "Diana P. M. Osorio", "url": "https://arxiv.org/abs/2509.19119", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2503.07115", "kind": "paper", "label": "YOLOMG: Vision-based Drone-to-Drone Detection with Appearance and Pixel-Level Motion Fusion", "url": "https://arxiv.org/abs/2503.07115", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:hanqing-guo", "kind": "person", "label": "Hanqing Guo", "url": "https://arxiv.org/abs/2503.07115", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:xiuxiu-lin", "kind": "person", "label": "Xiuxiu Lin", "url": "https://arxiv.org/abs/2503.07115", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:shiyu-zhao", "kind": "person", "label": "Shiyu Zhao", "url": "https://arxiv.org/abs/2503.07115", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2512.06998", "kind": "paper", "label": "Cell-free ISAC for Drone Detection Considering Coverage and Age of Sensing", "url": "https://arxiv.org/abs/2512.06998", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:zinat-behdad", "kind": "person", "label": "Zinat Behdad", "url": "https://arxiv.org/abs/2512.06998", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:ozan-alp-topal", "kind": "person", "label": "Ozan Alp Topal", "url": "https://arxiv.org/abs/2512.06998", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:cicek-cavdar", "kind": "person", "label": "Cicek Cavdar", "url": "https://arxiv.org/abs/2512.06998", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2405.04477", "kind": "paper", "label": "Designing an Objective-Driven Test Method for the Comparative Performance Evaluation of Commercial DTI Solutions for Counter UAS systems", "url": "https://arxiv.org/abs/2405.04477", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:ali-mohamoud", "kind": "person", "label": "Ali Mohamoud", "url": "https://arxiv.org/abs/2405.04477", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:johan-van-de-pol", "kind": "person", "label": "Johan van de Pol", "url": "https://arxiv.org/abs/2405.04477", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:hanno-hildmann", "kind": "person", "label": "Hanno Hildmann", "url": "https://arxiv.org/abs/2405.04477", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:rob-van-heijster", "kind": "person", "label": "Rob van Heijster", "url": "https://arxiv.org/abs/2405.04477", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:beatrice-masini", "kind": "person", "label": "Beatrice Masini", "url": "https://arxiv.org/abs/2405.04477", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:martijn-van-den-heuvel", "kind": "person", "label": "Martijn van den Heuvel", "url": "https://arxiv.org/abs/2405.04477", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:amber-van-keeken", "kind": "person", "label": "Amber van Keeken", "url": "https://arxiv.org/abs/2405.04477", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:1808.00259", "kind": "paper", "label": "Drone Detection Using Depth Maps", "url": "https://arxiv.org/abs/1808.00259", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:adrian-carrio", "kind": "person", "label": "Adrian Carrio", "url": "https://arxiv.org/abs/1808.00259", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:sai-vemprala", "kind": "person", "label": "Sai Vemprala", "url": "https://arxiv.org/abs/1808.00259", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:andres-ripoll", "kind": "person", "label": "Andres Ripoll", "url": "https://arxiv.org/abs/1808.00259", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:srikanth-saripalli", "kind": "person", "label": "Srikanth Saripalli", "url": "https://arxiv.org/abs/1808.00259", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:pascual-campoy", "kind": "person", "label": "Pascual Campoy", "url": "https://arxiv.org/abs/1808.00259", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2508.17831", "kind": "paper", "label": "CubeDN: Real-time Drone Detection in 3D Space from Dual mmWave Radar Cubes", "url": "https://arxiv.org/abs/2508.17831", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:yuan-fang", "kind": "person", "label": "Yuan Fang", "url": "https://arxiv.org/abs/2508.17831", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:fangzhan-shi", "kind": "person", "label": "Fangzhan Shi", "url": "https://arxiv.org/abs/2508.17831", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:xijia-wei", "kind": "person", "label": "Xijia Wei", "url": "https://arxiv.org/abs/2508.17831", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:qingchao-chen", "kind": "person", "label": "Qingchao Chen", "url": "https://arxiv.org/abs/2508.17831", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:kevin-chetty", "kind": "person", "label": "Kevin Chetty", "url": "https://arxiv.org/abs/2508.17831", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:simon-julier", "kind": "person", "label": "Simon Julier", "url": "https://arxiv.org/abs/2508.17831", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2601.08319", "kind": "paper", "label": "YOLOBirDrone: Dataset for Bird vs Drone Detection and Classification and a YOLO based enhanced learning architecture", "url": "https://arxiv.org/abs/2601.08319", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:dapinder-kaur", "kind": "person", "label": "Dapinder Kaur", "url": "https://arxiv.org/abs/2601.08319", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:neeraj-battish", "kind": "person", "label": "Neeraj Battish", "url": "https://arxiv.org/abs/2601.08319", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:arnav-bhavsar", "kind": "person", "label": "Arnav Bhavsar", "url": "https://arxiv.org/abs/2601.08319", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:shashi-poddar", "kind": "person", "label": "Shashi Poddar", "url": "https://arxiv.org/abs/2601.08319", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2508.04564", "kind": "paper", "label": "Drone Detection with Event Cameras", "url": "https://arxiv.org/abs/2508.04564", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:lorenzo-berlincioni", "kind": "person", "label": "Lorenzo Berlincioni", "url": "https://arxiv.org/abs/2508.04564", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:luca-cultrera", "kind": "person", "label": "Luca Cultrera", "url": "https://arxiv.org/abs/2508.04564", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2308.09899", "kind": "paper", "label": "Towards a High-Performance Object Detector: Insights from Drone Detection Using ViT and CNN-based Deep Learning Models", "url": "https://arxiv.org/abs/2308.09899", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:junyang-zhang", "kind": "person", "label": "Junyang Zhang", "url": "https://arxiv.org/abs/2308.09899", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2605.25942", "kind": "paper", "label": "LRDDv3: High-Resolution Long-Range Drone Detection Dataset with Range Information and Thermal Data", "url": "https://arxiv.org/abs/2605.25942", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:knut-peterson", "kind": "person", "label": "Knut Peterson", "url": "https://arxiv.org/abs/2605.25942", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:zaid-mayers", "kind": "person", "label": "Zaid Mayers", "url": "https://arxiv.org/abs/2605.25942", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:azmain-yousuf", "kind": "person", "label": "Azmain Yousuf", "url": "https://arxiv.org/abs/2605.25942", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:priontu-chowdhury", "kind": "person", "label": "Priontu Chowdhury", "url": "https://arxiv.org/abs/2605.25942", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:asher-zaczepinski", "kind": "person", "label": "Asher Zaczepinski", "url": "https://arxiv.org/abs/2605.25942", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:solmaz-arezoomandan", "kind": "person", "label": "Solmaz Arezoomandan", "url": "https://arxiv.org/abs/2605.25942", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:reihaneh-maarefdoust", "kind": "person", "label": "Reihaneh Maarefdoust", "url": "https://arxiv.org/abs/2605.25942", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:david-han", "kind": "person", "label": "David Han", "url": "https://arxiv.org/abs/2605.25942", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:1805.05138", "kind": "paper", "label": "Rogue Drone Detection: A Machine Learning Approach", "url": "https://arxiv.org/abs/1805.05138", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:henrik-ryd-n", "kind": "person", "label": "Henrik Ryd\u00e9n", "url": "https://arxiv.org/abs/1805.05138", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:sakib-bin-redhwan", "kind": "person", "label": "Sakib Bin Redhwan", "url": "https://arxiv.org/abs/1805.05138", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:xingqin-lin", "kind": "person", "label": "Xingqin Lin", "url": "https://arxiv.org/abs/1805.05138", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2407.00830", "kind": "paper", "label": "DroBoost: An Intelligent Score and Model Boosting Method for Drone Detection", "url": "https://arxiv.org/abs/2407.00830", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:kadir-sahin", "kind": "person", "label": "Kadir Sahin", "url": "https://arxiv.org/abs/2407.00830", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:efe-buyukborekci", "kind": "person", "label": "Efe Buyukborekci", "url": "https://arxiv.org/abs/2407.00830", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:devrim-cavusoglu", "kind": "person", "label": "Devrim Cavusoglu", "url": "https://arxiv.org/abs/2407.00830", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:sinan-altinuc", "kind": "person", "label": "Sinan Altinuc", "url": "https://arxiv.org/abs/2407.00830", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2210.08423", "kind": "paper", "label": "TransVisDrone: Spatio-Temporal Transformer for Vision-based Drone-to-Drone Detection in Aerial Videos", "url": "https://arxiv.org/abs/2210.08423", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:tushar-sangam", "kind": "person", "label": "Tushar Sangam", "url": "https://arxiv.org/abs/2210.08423", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:ishan-rajendrakumar-dave", "kind": "person", "label": "Ishan Rajendrakumar Dave", "url": "https://arxiv.org/abs/2210.08423", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:waqas-sultani", "kind": "person", "label": "Waqas Sultani", "url": "https://arxiv.org/abs/2210.08423", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:mubarak-shah", "kind": "person", "label": "Mubarak Shah", "url": "https://arxiv.org/abs/2210.08423", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2502.05292", "kind": "paper", "label": "Drone Detection and Tracking with YOLO and a Rule-based Method", "url": "https://arxiv.org/abs/2502.05292", "source": "arxiv", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:purbaditya-bhattacharya", "kind": "person", "label": "Purbaditya Bhattacharya", "url": "https://arxiv.org/abs/2502.05292", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:person:patrick-nowak", "kind": "person", "label": "Patrick Nowak", "url": "https://arxiv.org/abs/2502.05292", "source": "arxiv-author", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:paper:2311.03742", "kind": "paper", "label": "3DifFusionDet: Diffusion Model for 3D Object Detection with Robust LiDAR-Camera Fusion", "url": "https://arxiv.org/abs/2311.03742", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xinhao-xiang", "kind": "person", "label": "Xinhao Xiang", "url": "https://arxiv.org/abs/2311.03742", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:simon-dr-ger", "kind": "person", "label": "Simon Dr\u00e4ger", "url": "https://arxiv.org/abs/2311.03742", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiawei-zhang", "kind": "person", "label": "Jiawei Zhang", "url": "https://arxiv.org/abs/2311.03742", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2203.11496", "kind": "paper", "label": "TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers", "url": "https://arxiv.org/abs/2203.11496", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xuyang-bai", "kind": "person", "label": "Xuyang Bai", "url": "https://arxiv.org/abs/2203.11496", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zeyu-hu", "kind": "person", "label": "Zeyu Hu", "url": "https://arxiv.org/abs/2203.11496", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xinge-zhu", "kind": "person", "label": "Xinge Zhu", "url": "https://arxiv.org/abs/2203.11496", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:qingqiu-huang", "kind": "person", "label": "Qingqiu Huang", "url": "https://arxiv.org/abs/2203.11496", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yilun-chen", "kind": "person", "label": "Yilun Chen", "url": "https://arxiv.org/abs/2203.11496", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hongbo-fu", "kind": "person", "label": "Hongbo Fu", "url": "https://arxiv.org/abs/2203.11496", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chiew-lan-tai", "kind": "person", "label": "Chiew-Lan Tai", "url": "https://arxiv.org/abs/2203.11496", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2309.07084", "kind": "paper", "label": "SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection", "url": "https://arxiv.org/abs/2309.07084", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yiran-qin", "kind": "person", "label": "Yiran Qin", "url": "https://arxiv.org/abs/2309.07084", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chaoqun-wang", "kind": "person", "label": "Chaoqun Wang", "url": "https://arxiv.org/abs/2309.07084", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zijian-kang", "kind": "person", "label": "Zijian Kang", "url": "https://arxiv.org/abs/2309.07084", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ningning-ma", "kind": "person", "label": "Ningning Ma", "url": "https://arxiv.org/abs/2309.07084", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhen-li", "kind": "person", "label": "Zhen Li", "url": "https://arxiv.org/abs/2309.07084", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ruimao-zhang", "kind": "person", "label": "Ruimao Zhang", "url": "https://arxiv.org/abs/2309.07084", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2309.11804", "kind": "paper", "label": "FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object Detection", "url": "https://arxiv.org/abs/2309.11804", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zixuan-yin", "kind": "person", "label": "Zixuan Yin", "url": "https://arxiv.org/abs/2309.11804", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:han-sun", "kind": "person", "label": "Han Sun", "url": "https://arxiv.org/abs/2309.11804", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ningzhong-liu", "kind": "person", "label": "Ningzhong Liu", "url": "https://arxiv.org/abs/2309.11804", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:huiyu-zhou", "kind": "person", "label": "Huiyu Zhou", "url": "https://arxiv.org/abs/2309.11804", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiaquan-shen", "kind": "person", "label": "Jiaquan Shen", "url": "https://arxiv.org/abs/2309.11804", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2312.01468", "kind": "paper", "label": "Exploring Adversarial Robustness of LiDAR-Camera Fusion Model in Autonomous Driving", "url": "https://arxiv.org/abs/2312.01468", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:bo-yang", "kind": "person", "label": "Bo Yang", "url": "https://arxiv.org/abs/2312.01468", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaoyu-ji", "kind": "person", "label": "Xiaoyu Ji", "url": "https://arxiv.org/abs/2312.01468", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zizhi-jin", "kind": "person", "label": "Zizhi Jin", "url": "https://arxiv.org/abs/2312.01468", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yushi-cheng", "kind": "person", "label": "Yushi Cheng", "url": "https://arxiv.org/abs/2312.01468", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wenyuan-xu", "kind": "person", "label": "Wenyuan Xu", "url": "https://arxiv.org/abs/2312.01468", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2402.02738", "kind": "paper", "label": "Improving Robustness of LiDAR-Camera Fusion Model against Weather Corruption from Fusion Strategy Perspective", "url": "https://arxiv.org/abs/2402.02738", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yihao-huang", "kind": "person", "label": "Yihao Huang", "url": "https://arxiv.org/abs/2402.02738", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:kaiyuan-yu", "kind": "person", "label": "Kaiyuan Yu", "url": "https://arxiv.org/abs/2402.02738", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:qing-guo", "kind": "person", "label": "Qing Guo", "url": "https://arxiv.org/abs/2402.02738", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:felix-juefei-xu", "kind": "person", "label": "Felix Juefei-Xu", "url": "https://arxiv.org/abs/2402.02738", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaojun-jia", "kind": "person", "label": "Xiaojun Jia", "url": "https://arxiv.org/abs/2402.02738", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:geguang-pu", "kind": "person", "label": "Geguang Pu", "url": "https://arxiv.org/abs/2402.02738", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2405.03884", "kind": "paper", "label": "BadFusion: 2D-Oriented Backdoor Attacks against 3D Object Detection", "url": "https://arxiv.org/abs/2405.03884", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:saket-s-chaturvedi", "kind": "person", "label": "Saket S. Chaturvedi", "url": "https://arxiv.org/abs/2405.03884", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lan-zhang", "kind": "person", "label": "Lan Zhang", "url": "https://arxiv.org/abs/2405.03884", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wenbin-zhang", "kind": "person", "label": "Wenbin Zhang", "url": "https://arxiv.org/abs/2405.03884", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:pan-he", "kind": "person", "label": "Pan He", "url": "https://arxiv.org/abs/2405.03884", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaoyong-yuan", "kind": "person", "label": "Xiaoyong Yuan", "url": "https://arxiv.org/abs/2405.03884", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2509.08374", "kind": "paper", "label": "InsFusion: Rethink Instance-level LiDAR-Camera Fusion for 3D Object Detection", "url": "https://arxiv.org/abs/2509.08374", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhongyu-xia", "kind": "person", "label": "Zhongyu Xia", "url": "https://arxiv.org/abs/2509.08374", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hansong-yang", "kind": "person", "label": "Hansong Yang", "url": "https://arxiv.org/abs/2509.08374", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yongtao-wang", "kind": "person", "label": "Yongtao Wang", "url": "https://arxiv.org/abs/2509.08374", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2011.00652", "kind": "paper", "label": "Multi-View Adaptive Fusion Network for 3D Object Detection", "url": "https://arxiv.org/abs/2011.00652", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:guojun-wang", "kind": "person", "label": "Guojun Wang", "url": "https://arxiv.org/abs/2011.00652", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:bin-tian", "kind": "person", "label": "Bin Tian", "url": "https://arxiv.org/abs/2011.00652", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yachen-zhang", "kind": "person", "label": "Yachen Zhang", "url": "https://arxiv.org/abs/2011.00652", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:long-chen", "kind": "person", "label": "Long Chen", "url": "https://arxiv.org/abs/2011.00652", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:dongpu-cao", "kind": "person", "label": "Dongpu Cao", "url": "https://arxiv.org/abs/2011.00652", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jian-wu", "kind": "person", "label": "Jian Wu", "url": "https://arxiv.org/abs/2011.00652", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2303.11040", "kind": "paper", "label": "Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving", "url": "https://arxiv.org/abs/2303.11040", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yinpeng-dong", "kind": "person", "label": "Yinpeng Dong", "url": "https://arxiv.org/abs/2303.11040", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:caixin-kang", "kind": "person", "label": "Caixin Kang", "url": "https://arxiv.org/abs/2303.11040", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jinlai-zhang", "kind": "person", "label": "Jinlai Zhang", "url": "https://arxiv.org/abs/2303.11040", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zijian-zhu", "kind": "person", "label": "Zijian Zhu", "url": "https://arxiv.org/abs/2303.11040", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yikai-wang", "kind": "person", "label": "Yikai Wang", "url": "https://arxiv.org/abs/2303.11040", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hang-su", "kind": "person", "label": "Hang Su", "url": "https://arxiv.org/abs/2303.11040", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xingxing-wei", "kind": "person", "label": "Xingxing Wei", "url": "https://arxiv.org/abs/2303.11040", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2401.02702", "kind": "paper", "label": "VoxelNextFusion: A Simple, Unified and Effective Voxel Fusion Framework for Multi-Modal 3D Object Detection", "url": "https://arxiv.org/abs/2401.02702", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ziying-song", "kind": "person", "label": "Ziying Song", "url": "https://arxiv.org/abs/2401.02702", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:guoxin-zhang", "kind": "person", "label": "Guoxin Zhang", "url": "https://arxiv.org/abs/2401.02702", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jun-xie", "kind": "person", "label": "Jun Xie", "url": "https://arxiv.org/abs/2401.02702", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lin-liu", "kind": "person", "label": "Lin Liu", "url": "https://arxiv.org/abs/2401.02702", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:caiyan-jia", "kind": "person", "label": "Caiyan Jia", "url": "https://arxiv.org/abs/2401.02702", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shaoqing-xu", "kind": "person", "label": "Shaoqing Xu", "url": "https://arxiv.org/abs/2401.02702", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhepeng-wang", "kind": "person", "label": "Zhepeng Wang", "url": "https://arxiv.org/abs/2401.02702", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2311.07152", "kind": "paper", "label": "Detecting As Labeling: Rethinking LiDAR-camera Fusion in 3D Object Detection", "url": "https://arxiv.org/abs/2311.07152", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:junjie-huang", "kind": "person", "label": "Junjie Huang", "url": "https://arxiv.org/abs/2311.07152", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yun-ye", "kind": "person", "label": "Yun Ye", "url": "https://arxiv.org/abs/2311.07152", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhujin-liang", "kind": "person", "label": "Zhujin Liang", "url": "https://arxiv.org/abs/2311.07152", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yi-shan", "kind": "person", "label": "Yi Shan", "url": "https://arxiv.org/abs/2311.07152", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:dalong-du", "kind": "person", "label": "Dalong Du", "url": "https://arxiv.org/abs/2311.07152", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2403.07284", "kind": "paper", "label": "SparseLIF: High-Performance Sparse LiDAR-Camera Fusion for 3D Object Detection", "url": "https://arxiv.org/abs/2403.07284", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hongcheng-zhang", "kind": "person", "label": "Hongcheng Zhang", "url": "https://arxiv.org/abs/2403.07284", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:liu-liang", "kind": "person", "label": "Liu Liang", "url": "https://arxiv.org/abs/2403.07284", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:pengxin-zeng", "kind": "person", "label": "Pengxin Zeng", "url": "https://arxiv.org/abs/2403.07284", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiao-song", "kind": "person", "label": "Xiao Song", "url": "https://arxiv.org/abs/2403.07284", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2303.03595", "kind": "paper", "label": "LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion", "url": "https://arxiv.org/abs/2303.03595", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xin-li", "kind": "person", "label": "Xin Li", "url": "https://arxiv.org/abs/2303.03595", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tao-ma", "kind": "person", "label": "Tao Ma", "url": "https://arxiv.org/abs/2303.03595", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yuenan-hou", "kind": "person", "label": "Yuenan Hou", "url": "https://arxiv.org/abs/2303.03595", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:botian-shi", "kind": "person", "label": "Botian Shi", "url": "https://arxiv.org/abs/2303.03595", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:youquan-liu", "kind": "person", "label": "Youquan Liu", "url": "https://arxiv.org/abs/2303.03595", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xingjiao-wu", "kind": "person", "label": "Xingjiao Wu", "url": "https://arxiv.org/abs/2303.03595", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:qin-chen", "kind": "person", "label": "Qin Chen", "url": "https://arxiv.org/abs/2303.03595", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2508.01562", "kind": "paper", "label": "Adaptive LiDAR Scanning: Harnessing Temporal Cues for Efficient 3D Object Detection via Multi-Modal Fusion", "url": "https://arxiv.org/abs/2508.01562", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:sara-shoouri", "kind": "person", "label": "Sara Shoouri", "url": "https://arxiv.org/abs/2508.01562", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:morteza-tavakoli-taba", "kind": "person", "label": "Morteza Tavakoli Taba", "url": "https://arxiv.org/abs/2508.01562", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hun-seok-kim", "kind": "person", "label": "Hun-Seok Kim", "url": "https://arxiv.org/abs/2508.01562", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2209.10733", "kind": "paper", "label": "FusionRCNN: LiDAR-Camera Fusion for Two-stage 3D Object Detection", "url": "https://arxiv.org/abs/2209.10733", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xinli-xu", "kind": "person", "label": "Xinli Xu", "url": "https://arxiv.org/abs/2209.10733", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shaocong-dong", "kind": "person", "label": "Shaocong Dong", "url": "https://arxiv.org/abs/2209.10733", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lihe-ding", "kind": "person", "label": "Lihe Ding", "url": "https://arxiv.org/abs/2209.10733", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jie-wang", "kind": "person", "label": "Jie Wang", "url": "https://arxiv.org/abs/2209.10733", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tingfa-xu", "kind": "person", "label": "Tingfa Xu", "url": "https://arxiv.org/abs/2209.10733", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jianan-li", "kind": "person", "label": "Jianan Li", "url": "https://arxiv.org/abs/2209.10733", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2504.13647", "kind": "paper", "label": "An Efficient LiDAR-Camera Fusion Network for Multi-Class 3D Dynamic Object Detection and Trajectory Prediction", "url": "https://arxiv.org/abs/2504.13647", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yushen-he", "kind": "person", "label": "Yushen He", "url": "https://arxiv.org/abs/2504.13647", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lei-zhao", "kind": "person", "label": "Lei Zhao", "url": "https://arxiv.org/abs/2504.13647", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tianchen-deng", "kind": "person", "label": "Tianchen Deng", "url": "https://arxiv.org/abs/2504.13647", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zipeng-fang", "kind": "person", "label": "Zipeng Fang", "url": "https://arxiv.org/abs/2504.13647", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:weidong-chen", "kind": "person", "label": "Weidong Chen", "url": "https://arxiv.org/abs/2504.13647", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2303.16818", "kind": "paper", "label": "SimDistill: Simulated Multi-modal Distillation for BEV 3D Object Detection", "url": "https://arxiv.org/abs/2303.16818", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:haimei-zhao", "kind": "person", "label": "Haimei Zhao", "url": "https://arxiv.org/abs/2303.16818", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:qiming-zhang", "kind": "person", "label": "Qiming Zhang", "url": "https://arxiv.org/abs/2303.16818", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shanshan-zhao", "kind": "person", "label": "Shanshan Zhao", "url": "https://arxiv.org/abs/2303.16818", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhe-chen", "kind": "person", "label": "Zhe Chen", "url": "https://arxiv.org/abs/2303.16818", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:dacheng-tao", "kind": "person", "label": "Dacheng Tao", "url": "https://arxiv.org/abs/2303.16818", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2507.16224", "kind": "paper", "label": "LDRFusion: A LiDAR-Dominant multimodal refinement framework for 3D object detection", "url": "https://arxiv.org/abs/2507.16224", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jijun-wang", "kind": "person", "label": "Jijun Wang", "url": "https://arxiv.org/abs/2507.16224", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yan-wu", "kind": "person", "label": "Yan Wu", "url": "https://arxiv.org/abs/2507.16224", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yujian-mo", "kind": "person", "label": "Yujian Mo", "url": "https://arxiv.org/abs/2507.16224", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:junqiao-zhao", "kind": "person", "label": "Junqiao Zhao", "url": "https://arxiv.org/abs/2507.16224", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yinghao-hu", "kind": "person", "label": "Yinghao Hu", "url": "https://arxiv.org/abs/2507.16224", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2212.07560", "kind": "paper", "label": "Multi-level and multi-modal feature fusion for accurate 3D object detection in Connected and Automated Vehicles", "url": "https://arxiv.org/abs/2212.07560", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yiming-hou", "kind": "person", "label": "Yiming Hou", "url": "https://arxiv.org/abs/2212.07560", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:mahdi-rezaei", "kind": "person", "label": "Mahdi Rezaei", "url": "https://arxiv.org/abs/2212.07560", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:richard-romano", "kind": "person", "label": "Richard Romano", "url": "https://arxiv.org/abs/2212.07560", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2402.11677", "kind": "paper", "label": "MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection", "url": "https://arxiv.org/abs/2402.11677", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:till-beemelmanns", "kind": "person", "label": "Till Beemelmanns", "url": "https://arxiv.org/abs/2402.11677", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:quan-zhang", "kind": "person", "label": "Quan Zhang", "url": "https://arxiv.org/abs/2402.11677", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:christian-geller", "kind": "person", "label": "Christian Geller", "url": "https://arxiv.org/abs/2402.11677", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lutz-eckstein", "kind": "person", "label": "Lutz Eckstein", "url": "https://arxiv.org/abs/2402.11677", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2508.20530", "kind": "paper", "label": "Enhancing Pseudo-Boxes via Data-Level LiDAR-Camera Fusion for Unsupervised 3D Object Detection", "url": "https://arxiv.org/abs/2508.20530", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:mingqian-ji", "kind": "person", "label": "Mingqian Ji", "url": "https://arxiv.org/abs/2508.20530", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jian-yang", "kind": "person", "label": "Jian Yang", "url": "https://arxiv.org/abs/2508.20530", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shanshan-zhang", "kind": "person", "label": "Shanshan Zhang", "url": "https://arxiv.org/abs/2508.20530", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2509.18613", "kind": "paper", "label": "MLF-4DRCNet: Multi-Level Fusion with 4D Radar and Camera for 3D Object Detection in Autonomous Driving", "url": "https://arxiv.org/abs/2509.18613", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yuzhi-wu", "kind": "person", "label": "Yuzhi Wu", "url": "https://arxiv.org/abs/2509.18613", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:li-xiao", "kind": "person", "label": "Li Xiao", "url": "https://arxiv.org/abs/2509.18613", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:guangfeng-jiang", "kind": "person", "label": "Guangfeng Jiang", "url": "https://arxiv.org/abs/2509.18613", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xianggen-xia", "kind": "person", "label": "XiangGen Xia", "url": "https://arxiv.org/abs/2509.18613", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2302.14522", "kind": "paper", "label": "AdaptiveShape: Solving Shape Variability for 3D Object Detection with Geometry Aware Anchor Distributions", "url": "https://arxiv.org/abs/2302.14522", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:benjamin-sick", "kind": "person", "label": "Benjamin Sick", "url": "https://arxiv.org/abs/2302.14522", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:michael-walter", "kind": "person", "label": "Michael Walter", "url": "https://arxiv.org/abs/2302.14522", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jochen-abhau", "kind": "person", "label": "Jochen Abhau", "url": "https://arxiv.org/abs/2302.14522", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:1806.06261", "kind": "paper", "label": "Comparative survey: People detection, tracking and multi-sensor Fusion in a video sequence", "url": "https://arxiv.org/abs/1806.06261", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hiliwi-leake-kidane", "kind": "person", "label": "Hiliwi Leake Kidane", "url": "https://arxiv.org/abs/1806.06261", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2210.15316", "kind": "paper", "label": "MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer for Autonomous Driving", "url": "https://arxiv.org/abs/2210.15316", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:gopi-krishna-erabati", "kind": "person", "label": "Gopi Krishna Erabati", "url": "https://arxiv.org/abs/2210.15316", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:helder-araujo", "kind": "person", "label": "Helder Araujo", "url": "https://arxiv.org/abs/2210.15316", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2409.19972", "kind": "paper", "label": "DAOcc: 3D Object Detection Assisted Multi-Sensor Fusion for 3D Occupancy Prediction", "url": "https://arxiv.org/abs/2409.19972", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yanpeng-dong", "kind": "person", "label": "Yanpeng Dong", "url": "https://arxiv.org/abs/2409.19972", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiayu-wang", "kind": "person", "label": "Jiayu Wang", "url": "https://arxiv.org/abs/2409.19972", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:heng-wang", "kind": "person", "label": "Heng Wang", "url": "https://arxiv.org/abs/2409.19972", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lichao-ma", "kind": "person", "label": "Lichao Ma", "url": "https://arxiv.org/abs/2409.19972", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zijian-cui", "kind": "person", "label": "Zijian Cui", "url": "https://arxiv.org/abs/2409.19972", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:haoran-pei", "kind": "person", "label": "Haoran Pei", "url": "https://arxiv.org/abs/2409.19972", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2409.12426", "kind": "paper", "label": "UniMSF: A Unified Multi-Sensor Fusion Framework for Intelligent Transportation System Global Localization", "url": "https://arxiv.org/abs/2409.12426", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiaqi-zhu", "kind": "person", "label": "Jiaqi Zhu", "url": "https://arxiv.org/abs/2409.12426", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:guirong-zhuo", "kind": "person", "label": "Guirong Zhuo", "url": "https://arxiv.org/abs/2409.12426", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wufei-fu", "kind": "person", "label": "Wufei Fu", "url": "https://arxiv.org/abs/2409.12426", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yishi-lu", "kind": "person", "label": "Yishi Lu", "url": "https://arxiv.org/abs/2409.12426", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:min-hua", "kind": "person", "label": "Min Hua", "url": "https://arxiv.org/abs/2409.12426", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:feng-qiao", "kind": "person", "label": "Feng Qiao", "url": "https://arxiv.org/abs/2409.12426", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2508.18025", "kind": "paper", "label": "Adaptive Quantized Planetary Crater Detection System for Autonomous Space Exploration", "url": "https://arxiv.org/abs/2508.18025", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:aditri-paul", "kind": "person", "label": "Aditri Paul", "url": "https://arxiv.org/abs/2508.18025", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:archan-paul", "kind": "person", "label": "Archan Paul", "url": "https://arxiv.org/abs/2508.18025", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2202.09124", "kind": "paper", "label": "Multi-view and Multi-modal Event Detection Utilizing Transformer-based Multi-sensor fusion", "url": "https://arxiv.org/abs/2202.09124", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:masahiro-yasuda", "kind": "person", "label": "Masahiro Yasuda", "url": "https://arxiv.org/abs/2202.09124", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yasunori-ohishi", "kind": "person", "label": "Yasunori Ohishi", "url": "https://arxiv.org/abs/2202.09124", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shoichiro-saito", "kind": "person", "label": "Shoichiro Saito", "url": "https://arxiv.org/abs/2202.09124", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:noboru-harada", "kind": "person", "label": "Noboru Harada", "url": "https://arxiv.org/abs/2202.09124", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2404.04629", "kind": "paper", "label": "DifFUSER: Diffusion Model for Robust Multi-Sensor Fusion in 3D Object Detection and BEV Segmentation", "url": "https://arxiv.org/abs/2404.04629", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:duy-tho-le", "kind": "person", "label": "Duy-Tho Le", "url": "https://arxiv.org/abs/2404.04629", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hengcan-shi", "kind": "person", "label": "Hengcan Shi", "url": "https://arxiv.org/abs/2404.04629", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jianfei-cai", "kind": "person", "label": "Jianfei Cai", "url": "https://arxiv.org/abs/2404.04629", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hamid-rezatofighi", "kind": "person", "label": "Hamid Rezatofighi", "url": "https://arxiv.org/abs/2404.04629", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2109.06404", "kind": "paper", "label": "Detecting Multi-Sensor Fusion Errors in Advanced Driver-Assistance Systems", "url": "https://arxiv.org/abs/2109.06404", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ziyuan-zhong", "kind": "person", "label": "Ziyuan Zhong", "url": "https://arxiv.org/abs/2109.06404", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhisheng-hu", "kind": "person", "label": "Zhisheng Hu", "url": "https://arxiv.org/abs/2109.06404", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shengjian-guo", "kind": "person", "label": "Shengjian Guo", "url": "https://arxiv.org/abs/2109.06404", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xinyang-zhang", "kind": "person", "label": "Xinyang Zhang", "url": "https://arxiv.org/abs/2109.06404", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhenyu-zhong", "kind": "person", "label": "Zhenyu Zhong", "url": "https://arxiv.org/abs/2109.06404", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:baishakhi-ray", "kind": "person", "label": "Baishakhi Ray", "url": "https://arxiv.org/abs/2109.06404", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2404.14780", "kind": "paper", "label": "ContextualFusion: Context-Based Multi-Sensor Fusion for 3D Object Detection in Adverse Operating Conditions", "url": "https://arxiv.org/abs/2404.14780", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shounak-sural", "kind": "person", "label": "Shounak Sural", "url": "https://arxiv.org/abs/2404.14780", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:nishad-sahu", "kind": "person", "label": "Nishad Sahu", "url": "https://arxiv.org/abs/2404.14780", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ragunathan-rajkumar", "kind": "person", "label": "Ragunathan Rajkumar", "url": "https://arxiv.org/abs/2404.14780", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2501.05997", "kind": "paper", "label": "Minimizing Occlusion Effect on Multi-View Camera Perception in BEV with Multi-Sensor Fusion", "url": "https://arxiv.org/abs/2501.05997", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:sanjay-kumar", "kind": "person", "label": "Sanjay Kumar", "url": "https://arxiv.org/abs/2501.05997", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hiep-truong", "kind": "person", "label": "Hiep Truong", "url": "https://arxiv.org/abs/2501.05997", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:sushil-sharma", "kind": "person", "label": "Sushil Sharma", "url": "https://arxiv.org/abs/2501.05997", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tony-scanlan", "kind": "person", "label": "Tony Scanlan", "url": "https://arxiv.org/abs/2501.05997", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:eoin-grua", "kind": "person", "label": "Eoin Grua", "url": "https://arxiv.org/abs/2501.05997", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2403.02329", "kind": "paper", "label": "COMMIT: Certifying Robustness of Multi-Sensor Fusion Systems against Semantic Attacks", "url": "https://arxiv.org/abs/2403.02329", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zijian-huang", "kind": "person", "label": "Zijian Huang", "url": "https://arxiv.org/abs/2403.02329", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wenda-chu", "kind": "person", "label": "Wenda Chu", "url": "https://arxiv.org/abs/2403.02329", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:linyi-li", "kind": "person", "label": "Linyi Li", "url": "https://arxiv.org/abs/2403.02329", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chejian-xu", "kind": "person", "label": "Chejian Xu", "url": "https://arxiv.org/abs/2403.02329", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2607.03915", "kind": "paper", "label": "NavEYE: Vision-Centered Multi-Sensor Fusion-Based Situational Awareness System for Intelligent Surface Vehicles", "url": "https://arxiv.org/abs/2607.03915", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ryan-wen-liua", "kind": "person", "label": "Ryan Wen Liua", "url": "https://arxiv.org/abs/2607.03915", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:junxiong-lianga", "kind": "person", "label": "Junxiong Lianga", "url": "https://arxiv.org/abs/2607.03915", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:haoyu-wanga", "kind": "person", "label": "Haoyu Wanga", "url": "https://arxiv.org/abs/2607.03915", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:mengwei-baoa", "kind": "person", "label": "Mengwei Baoa", "url": "https://arxiv.org/abs/2607.03915", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2603.29126", "kind": "paper", "label": "A Multi-Sensor Fusion Parking Barrier System with Lightweight Vision on Edge", "url": "https://arxiv.org/abs/2603.29126", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yuwen-zhu", "kind": "person", "label": "Yuwen Zhu", "url": "https://arxiv.org/abs/2603.29126", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:feiyang-qi", "kind": "person", "label": "Feiyang Qi", "url": "https://arxiv.org/abs/2603.29126", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhengzhe-xiang", "kind": "person", "label": "Zhengzhe Xiang", "url": "https://arxiv.org/abs/2603.29126", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2401.14314", "kind": "paper", "label": "MultiTest: Physical-Aware Object Insertion for Testing Multi-sensor Fusion Perception Systems", "url": "https://arxiv.org/abs/2401.14314", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xinyu-gao", "kind": "person", "label": "Xinyu Gao", "url": "https://arxiv.org/abs/2401.14314", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhijie-wang", "kind": "person", "label": "Zhijie Wang", "url": "https://arxiv.org/abs/2401.14314", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yang-feng", "kind": "person", "label": "Yang Feng", "url": "https://arxiv.org/abs/2401.14314", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lei-ma", "kind": "person", "label": "Lei Ma", "url": "https://arxiv.org/abs/2401.14314", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhenyu-chen", "kind": "person", "label": "Zhenyu Chen", "url": "https://arxiv.org/abs/2401.14314", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:baowen-xu", "kind": "person", "label": "Baowen Xu", "url": "https://arxiv.org/abs/2401.14314", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2510.23003", "kind": "paper", "label": "An Intelligent Water-Saving Irrigation System Based on Multi-Sensor Fusion and Visual Servoing Control", "url": "https://arxiv.org/abs/2510.23003", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhengkai-huang", "kind": "person", "label": "ZhengKai Huang", "url": "https://arxiv.org/abs/2510.23003", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yikun-wang", "kind": "person", "label": "YiKun Wang", "url": "https://arxiv.org/abs/2510.23003", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chenyu-hui", "kind": "person", "label": "ChenYu Hui", "url": "https://arxiv.org/abs/2510.23003", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaocheng", "kind": "person", "label": "XiaoCheng", "url": "https://arxiv.org/abs/2510.23003", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2604.21841", "kind": "paper", "label": "Cross-Modal Phantom: Coordinated Camera-LiDAR Spoofing Against Multi-Sensor Fusion in Autonomous Vehicles", "url": "https://arxiv.org/abs/2604.21841", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shahriar-rahman-khan", "kind": "person", "label": "Shahriar Rahman Khan", "url": "https://arxiv.org/abs/2604.21841", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:raiful-hasan", "kind": "person", "label": "Raiful Hasan", "url": "https://arxiv.org/abs/2604.21841", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2306.03454", "kind": "paper", "label": "Benchmarking Robustness of AI-Enabled Multi-sensor Fusion Systems: Challenges and Opportunities", "url": "https://arxiv.org/abs/2306.03454", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2506.19769", "kind": "paper", "label": "A Survey of Multi-sensor Fusion Perception for Embodied AI: Background, Methods, Challenges and Prospects", "url": "https://arxiv.org/abs/2506.19769", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shulan-ruan", "kind": "person", "label": "Shulan Ruan", "url": "https://arxiv.org/abs/2506.19769", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:rongwei-wang", "kind": "person", "label": "Rongwei Wang", "url": "https://arxiv.org/abs/2506.19769", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xuchen-shen", "kind": "person", "label": "Xuchen Shen", "url": "https://arxiv.org/abs/2506.19769", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:huijie-liu", "kind": "person", "label": "Huijie Liu", "url": "https://arxiv.org/abs/2506.19769", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:baihui-xiao", "kind": "person", "label": "Baihui Xiao", "url": "https://arxiv.org/abs/2506.19769", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jun-shi", "kind": "person", "label": "Jun Shi", "url": "https://arxiv.org/abs/2506.19769", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:kun-zhang", "kind": "person", "label": "Kun Zhang", "url": "https://arxiv.org/abs/2506.19769", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhenya-huang", "kind": "person", "label": "Zhenya Huang", "url": "https://arxiv.org/abs/2506.19769", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2510.22947", "kind": "paper", "label": "Intelligent Multimodal Multi-Sensor Fusion-Based UAV Identification, Localization, and Countermeasures for Safeguarding Low-Altitude Economy", "url": "https://arxiv.org/abs/2510.22947", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yi-tao", "kind": "person", "label": "Yi Tao", "url": "https://arxiv.org/abs/2510.22947", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhen-gao", "kind": "person", "label": "Zhen Gao", "url": "https://arxiv.org/abs/2510.22947", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:fangquan-ye", "kind": "person", "label": "Fangquan Ye", "url": "https://arxiv.org/abs/2510.22947", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jingbo-xu", "kind": "person", "label": "Jingbo Xu", "url": "https://arxiv.org/abs/2510.22947", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tao-song", "kind": "person", "label": "Tao Song", "url": "https://arxiv.org/abs/2510.22947", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:weidong-li", "kind": "person", "label": "Weidong Li", "url": "https://arxiv.org/abs/2510.22947", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yu-su", "kind": "person", "label": "Yu Su", "url": "https://arxiv.org/abs/2510.22947", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lu-peng", "kind": "person", "label": "Lu Peng", "url": "https://arxiv.org/abs/2510.22947", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2504.13420", "kind": "paper", "label": "Testing the Fault-Tolerance of Multi-Sensor Fusion Perception in Autonomous Driving Systems", "url": "https://arxiv.org/abs/2504.13420", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:haoxiang-tian", "kind": "person", "label": "Haoxiang Tian", "url": "https://arxiv.org/abs/2504.13420", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wenqiang-ding", "kind": "person", "label": "Wenqiang Ding", "url": "https://arxiv.org/abs/2504.13420", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xingshuo-han", "kind": "person", "label": "Xingshuo Han", "url": "https://arxiv.org/abs/2504.13420", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:guoquan-wu", "kind": "person", "label": "Guoquan Wu", "url": "https://arxiv.org/abs/2504.13420", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:an-guo", "kind": "person", "label": "An Guo", "url": "https://arxiv.org/abs/2504.13420", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:junqi-zhang-wei-chen", "kind": "person", "label": "Junqi Zhang. Wei Chen", "url": "https://arxiv.org/abs/2504.13420", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jun-wei", "kind": "person", "label": "Jun Wei", "url": "https://arxiv.org/abs/2504.13420", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tianwei-zhang", "kind": "person", "label": "Tianwei Zhang", "url": "https://arxiv.org/abs/2504.13420", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2106.09249", "kind": "paper", "label": "Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks", "url": "https://arxiv.org/abs/2106.09249", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yulong-cao", "kind": "person", "label": "Yulong Cao*", "url": "https://arxiv.org/abs/2106.09249", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ningfei-wang", "kind": "person", "label": "Ningfei Wang*", "url": "https://arxiv.org/abs/2106.09249", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chaowei-xiao", "kind": "person", "label": "Chaowei Xiao*", "url": "https://arxiv.org/abs/2106.09249", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:dawei-yang", "kind": "person", "label": "Dawei Yang*", "url": "https://arxiv.org/abs/2106.09249", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jin-fang", "kind": "person", "label": "Jin Fang", "url": "https://arxiv.org/abs/2106.09249", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:qi-alfred-chen", "kind": "person", "label": "Qi Alfred Chen", "url": "https://arxiv.org/abs/2106.09249", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:mingyan-liu", "kind": "person", "label": "Mingyan Liu", "url": "https://arxiv.org/abs/2106.09249", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2012.12397", "kind": "paper", "label": "Multi-Task Multi-Sensor Fusion for 3D Object Detection", "url": "https://arxiv.org/abs/2012.12397", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ming-liang", "kind": "person", "label": "Ming Liang", "url": "https://arxiv.org/abs/2012.12397", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:bin-yang", "kind": "person", "label": "Bin Yang", "url": "https://arxiv.org/abs/2012.12397", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yun-chen", "kind": "person", "label": "Yun Chen", "url": "https://arxiv.org/abs/2012.12397", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:rui-hu", "kind": "person", "label": "Rui Hu", "url": "https://arxiv.org/abs/2012.12397", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:raquel-urtasun", "kind": "person", "label": "Raquel Urtasun", "url": "https://arxiv.org/abs/2012.12397", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2010.04837", "kind": "paper", "label": "CurbScan: Curb Detection and Tracking Using Multi-Sensor Fusion", "url": "https://arxiv.org/abs/2010.04837", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:iljoo-baek", "kind": "person", "label": "Iljoo Baek", "url": "https://arxiv.org/abs/2010.04837", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tzu-chieh-tai", "kind": "person", "label": "Tzu-Chieh Tai", "url": "https://arxiv.org/abs/2010.04837", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:manoj-bhat", "kind": "person", "label": "Manoj Bhat", "url": "https://arxiv.org/abs/2010.04837", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:karun-ellango", "kind": "person", "label": "Karun Ellango", "url": "https://arxiv.org/abs/2010.04837", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tarang-shah", "kind": "person", "label": "Tarang Shah", "url": "https://arxiv.org/abs/2010.04837", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:kamal-fuseini", "kind": "person", "label": "Kamal Fuseini", "url": "https://arxiv.org/abs/2010.04837", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ragunathan", "kind": "person", "label": "Ragunathan", "url": "https://arxiv.org/abs/2010.04837", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:rajkumar", "kind": "person", "label": "Rajkumar", "url": "https://arxiv.org/abs/2010.04837", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2204.01146", "kind": "paper", "label": "Proactive Anomaly Detection for Robot Navigation with Multi-Sensor Fusion", "url": "https://arxiv.org/abs/2204.01146", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tianchen-ji", "kind": "person", "label": "Tianchen Ji", "url": "https://arxiv.org/abs/2204.01146", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:arun-narenthiran-sivakumar", "kind": "person", "label": "Arun Narenthiran Sivakumar", "url": "https://arxiv.org/abs/2204.01146", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:girish-chowdhary", "kind": "person", "label": "Girish Chowdhary", "url": "https://arxiv.org/abs/2204.01146", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:katherine-driggs-campbell", "kind": "person", "label": "Katherine Driggs-Campbell", "url": "https://arxiv.org/abs/2204.01146", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2504.03171", "kind": "paper", "label": "Real-Time Roadway Obstacle Detection for Electric Scooters Using Deep Learning and Multi-Sensor Fusion", "url": "https://arxiv.org/abs/2504.03171", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zeyang-zheng", "kind": "person", "label": "Zeyang Zheng", "url": "https://arxiv.org/abs/2504.03171", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:arman-hosseini", "kind": "person", "label": "Arman Hosseini", "url": "https://arxiv.org/abs/2504.03171", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:omid-shoghli", "kind": "person", "label": "Omid Shoghli", "url": "https://arxiv.org/abs/2504.03171", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:arsalan-heydarian", "kind": "person", "label": "Arsalan Heydarian", "url": "https://arxiv.org/abs/2504.03171", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2412.14592", "kind": "paper", "label": "Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties", "url": "https://arxiv.org/abs/2412.14592", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wenqiao-li", "kind": "person", "label": "Wenqiao Li", "url": "https://arxiv.org/abs/2412.14592", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:bozhong-zheng", "kind": "person", "label": "Bozhong Zheng", "url": "https://arxiv.org/abs/2412.14592", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaohao-xu", "kind": "person", "label": "Xiaohao Xu", "url": "https://arxiv.org/abs/2412.14592", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jinye-gan", "kind": "person", "label": "Jinye Gan", "url": "https://arxiv.org/abs/2412.14592", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:fading-lu", "kind": "person", "label": "Fading Lu", "url": "https://arxiv.org/abs/2412.14592", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:na-ni", "kind": "person", "label": "Na Ni", "url": "https://arxiv.org/abs/2412.14592", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zheng-tian", "kind": "person", "label": "Zheng Tian", "url": "https://arxiv.org/abs/2412.14592", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2602.01974", "kind": "paper", "label": "Obstacle Detection at Level Crossings under Adverse Weather Conditions -- A Survey", "url": "https://arxiv.org/abs/2602.01974", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chenyang-yan", "kind": "person", "label": "Chenyang Yan", "url": "https://arxiv.org/abs/2602.01974", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:mats-bengtsson", "kind": "person", "label": "Mats Bengtsson", "url": "https://arxiv.org/abs/2602.01974", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2304.13390", "kind": "paper", "label": "Group Equivariant BEV for 3D Object Detection", "url": "https://arxiv.org/abs/2304.13390", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hongwei-liu", "kind": "person", "label": "Hongwei Liu", "url": "https://arxiv.org/abs/2304.13390", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jianfeng-zhang", "kind": "person", "label": "Jianfeng Zhang", "url": "https://arxiv.org/abs/2304.13390", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:dongheng-shao", "kind": "person", "label": "Dongheng Shao", "url": "https://arxiv.org/abs/2304.13390", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jielong-guo", "kind": "person", "label": "Jielong Guo", "url": "https://arxiv.org/abs/2304.13390", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shaobo-li", "kind": "person", "label": "Shaobo Li", "url": "https://arxiv.org/abs/2304.13390", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xuan-tang", "kind": "person", "label": "Xuan Tang", "url": "https://arxiv.org/abs/2304.13390", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xian-wei", "kind": "person", "label": "Xian Wei", "url": "https://arxiv.org/abs/2304.13390", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2409.04979", "kind": "paper", "label": "RCBEVDet++: Toward High-accuracy Radar-Camera Fusion 3D Perception Network", "url": "https://arxiv.org/abs/2409.04979", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhiwei-lin", "kind": "person", "label": "Zhiwei Lin", "url": "https://arxiv.org/abs/2409.04979", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhe-liu", "kind": "person", "label": "Zhe Liu", "url": "https://arxiv.org/abs/2409.04979", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:le-zhang", "kind": "person", "label": "Le Zhang", "url": "https://arxiv.org/abs/2409.04979", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ce-zhu", "kind": "person", "label": "Ce Zhu", "url": "https://arxiv.org/abs/2409.04979", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2103.07825", "kind": "paper", "label": "Radar Camera Fusion via Representation Learning in Autonomous Driving", "url": "https://arxiv.org/abs/2103.07825", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:binnan-zhuang", "kind": "person", "label": "Binnan Zhuang", "url": "https://arxiv.org/abs/2103.07825", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yunxiang-mao", "kind": "person", "label": "Yunxiang Mao", "url": "https://arxiv.org/abs/2103.07825", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:langechuan-liu", "kind": "person", "label": "Langechuan Liu", "url": "https://arxiv.org/abs/2103.07825", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2404.06165", "kind": "paper", "label": "Enhanced Radar Perception via Multi-Task Learning: Towards Refined Data for Sensor Fusion Applications", "url": "https://arxiv.org/abs/2404.06165", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:huawei-sun", "kind": "person", "label": "Huawei Sun", "url": "https://arxiv.org/abs/2404.06165", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hao-feng", "kind": "person", "label": "Hao Feng", "url": "https://arxiv.org/abs/2404.06165", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:gianfranco-mauro", "kind": "person", "label": "Gianfranco Mauro", "url": "https://arxiv.org/abs/2404.06165", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:julius-ott", "kind": "person", "label": "Julius Ott", "url": "https://arxiv.org/abs/2404.06165", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:georg-stettinger", "kind": "person", "label": "Georg Stettinger", "url": "https://arxiv.org/abs/2404.06165", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lorenzo-servadei", "kind": "person", "label": "Lorenzo Servadei", "url": "https://arxiv.org/abs/2404.06165", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:robert-wille", "kind": "person", "label": "Robert Wille", "url": "https://arxiv.org/abs/2404.06165", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2304.10410", "kind": "paper", "label": "Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review", "url": "https://arxiv.org/abs/2304.10410", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:shanliang-yao", "kind": "person", "label": "Shanliang Yao", "url": "https://arxiv.org/abs/2304.10410", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:runwei-guan", "kind": "person", "label": "Runwei Guan", "url": "https://arxiv.org/abs/2304.10410", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaoyu-huang", "kind": "person", "label": "Xiaoyu Huang", "url": "https://arxiv.org/abs/2304.10410", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhuoxiao-li", "kind": "person", "label": "Zhuoxiao Li", "url": "https://arxiv.org/abs/2304.10410", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiangyu-sha", "kind": "person", "label": "Xiangyu Sha", "url": "https://arxiv.org/abs/2304.10410", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yong-yue", "kind": "person", "label": "Yong Yue", "url": "https://arxiv.org/abs/2304.10410", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:eng-gee-lim", "kind": "person", "label": "Eng Gee Lim", "url": "https://arxiv.org/abs/2304.10410", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hyungjoon-seo", "kind": "person", "label": "Hyungjoon Seo", "url": "https://arxiv.org/abs/2304.10410", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2603.06670", "kind": "paper", "label": "calibfusion: Transformer-Based Differentiable Calibration for Radar-Camera Fusion Detection in Water-Surface Environments", "url": "https://arxiv.org/abs/2603.06670", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yuting-wan", "kind": "person", "label": "Yuting Wan", "url": "https://arxiv.org/abs/2603.06670", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:liguo-sun", "kind": "person", "label": "Liguo Sun", "url": "https://arxiv.org/abs/2603.06670", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiuwu-hao", "kind": "person", "label": "Jiuwu Hao", "url": "https://arxiv.org/abs/2603.06670", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:pin-lv", "kind": "person", "label": "Pin LV", "url": "https://arxiv.org/abs/2603.06670", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2606.31096", "kind": "paper", "label": "Horizon3D: Sparse Radar-Camera Fusion for Long-Range 3D Perception in Autonomous Driving", "url": "https://arxiv.org/abs/2606.31096", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:geonho-bang", "kind": "person", "label": "Geonho Bang", "url": "https://arxiv.org/abs/2606.31096", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:geunju-baek", "kind": "person", "label": "Geunju Baek", "url": "https://arxiv.org/abs/2606.31096", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wonjun-jeong", "kind": "person", "label": "Wonjun Jeong", "url": "https://arxiv.org/abs/2606.31096", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2307.06505", "kind": "paper", "label": "WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces", "url": "https://arxiv.org/abs/2307.06505", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhaodong-wu", "kind": "person", "label": "Zhaodong Wu", "url": "https://arxiv.org/abs/2307.06505", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yi-ni", "kind": "person", "label": "Yi Ni", "url": "https://arxiv.org/abs/2307.06505", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zile-huang", "kind": "person", "label": "Zile Huang", "url": "https://arxiv.org/abs/2307.06505", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ryan-wen-liu", "kind": "person", "label": "Ryan Wen Liu", "url": "https://arxiv.org/abs/2307.06505", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:weiping-ding", "kind": "person", "label": "Weiping Ding", "url": "https://arxiv.org/abs/2307.06505", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2107.05150", "kind": "paper", "label": "CFTrack: Center-based Radar and Camera Fusion for 3D Multi-Object Tracking", "url": "https://arxiv.org/abs/2107.05150", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ramin-nabati", "kind": "person", "label": "Ramin Nabati", "url": "https://arxiv.org/abs/2107.05150", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:landon-harris", "kind": "person", "label": "Landon Harris", "url": "https://arxiv.org/abs/2107.05150", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hairong-qi", "kind": "person", "label": "Hairong Qi", "url": "https://arxiv.org/abs/2107.05150", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2412.12725", "kind": "paper", "label": "RaCFormer: Towards High-Quality 3D Object Detection via Query-based Radar-Camera Fusion", "url": "https://arxiv.org/abs/2412.12725", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaomeng-chu", "kind": "person", "label": "Xiaomeng Chu", "url": "https://arxiv.org/abs/2412.12725", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiajun-deng", "kind": "person", "label": "Jiajun Deng", "url": "https://arxiv.org/abs/2412.12725", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:guoliang-you", "kind": "person", "label": "Guoliang You", "url": "https://arxiv.org/abs/2412.12725", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yifan-duan", "kind": "person", "label": "Yifan Duan", "url": "https://arxiv.org/abs/2412.12725", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:houqiang-li", "kind": "person", "label": "Houqiang Li", "url": "https://arxiv.org/abs/2412.12725", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yanyong-zhang", "kind": "person", "label": "Yanyong Zhang", "url": "https://arxiv.org/abs/2412.12725", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2412.11489", "kind": "paper", "label": "HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detection", "url": "https://arxiv.org/abs/2412.11489", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zijian-gu", "kind": "person", "label": "Zijian Gu", "url": "https://arxiv.org/abs/2412.11489", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jianwei-ma", "kind": "person", "label": "Jianwei Ma", "url": "https://arxiv.org/abs/2412.11489", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yan-huang", "kind": "person", "label": "Yan Huang", "url": "https://arxiv.org/abs/2412.11489", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:honghao-wei", "kind": "person", "label": "Honghao Wei", "url": "https://arxiv.org/abs/2412.11489", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhanye-chen", "kind": "person", "label": "Zhanye Chen", "url": "https://arxiv.org/abs/2412.11489", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hui-zhang", "kind": "person", "label": "Hui Zhang", "url": "https://arxiv.org/abs/2412.11489", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wei-hong", "kind": "person", "label": "Wei Hong", "url": "https://arxiv.org/abs/2412.11489", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2607.04098", "kind": "paper", "label": "Sparse4D-Radar: An Efficient and Robust Framework for Surround-View 3D Object Detection via 4D Radar-Camera Fusion", "url": "https://arxiv.org/abs/2607.04098", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:fuyuan-ai", "kind": "person", "label": "Fuyuan Ai", "url": "https://arxiv.org/abs/2607.04098", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yuchen-tan", "kind": "person", "label": "Yuchen Tan", "url": "https://arxiv.org/abs/2607.04098", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiehui-chen", "kind": "person", "label": "Jiehui Chen", "url": "https://arxiv.org/abs/2607.04098", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhiwei-xu", "kind": "person", "label": "Zhiwei Xu", "url": "https://arxiv.org/abs/2607.04098", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chunyi-song", "kind": "person", "label": "Chunyi Song", "url": "https://arxiv.org/abs/2607.04098", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2411.15016", "kind": "paper", "label": "MSSF: A 4D Radar and Camera Fusion Framework With Multi-Stage Sampling for 3D Object Detection in Autonomous Driving", "url": "https://arxiv.org/abs/2411.15016", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hongsi-liu", "kind": "person", "label": "Hongsi Liu", "url": "https://arxiv.org/abs/2411.15016", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xin-jin", "kind": "person", "label": "Xin Jin", "url": "https://arxiv.org/abs/2411.15016", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2303.04302", "kind": "paper", "label": "Camera-Radar Perception for Autonomous Vehicles and ADAS: Concepts, Datasets and Metrics", "url": "https://arxiv.org/abs/2303.04302", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:felipe-manfio-barbosa", "kind": "person", "label": "Felipe Manfio Barbosa", "url": "https://arxiv.org/abs/2303.04302", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:fernando-santos-os-rio", "kind": "person", "label": "Fernando Santos Os\u00f3rio", "url": "https://arxiv.org/abs/2303.04302", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2604.12918", "kind": "paper", "label": "Radar-Camera BEV Multi-Task Learning with Cross-Task Attention Bridge for Joint 3D Detection and Segmentation", "url": "https://arxiv.org/abs/2604.12918", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ahmet-i-nan", "kind": "person", "label": "Ahmet \u0130nan\u00e7", "url": "https://arxiv.org/abs/2604.12918", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zg-r-erkent", "kind": "person", "label": "\u00d6zg\u00fcr Erkent", "url": "https://arxiv.org/abs/2604.12918", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2504.16368", "kind": "paper", "label": "Revisiting Radar Camera Alignment by Contrastive Learning for 3D Object Detection", "url": "https://arxiv.org/abs/2504.16368", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:linhua-kong", "kind": "person", "label": "Linhua Kong", "url": "https://arxiv.org/abs/2504.16368", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:dongxia-chang", "kind": "person", "label": "Dongxia Chang", "url": "https://arxiv.org/abs/2504.16368", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lian-liu", "kind": "person", "label": "Lian Liu", "url": "https://arxiv.org/abs/2504.16368", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zisen-kong", "kind": "person", "label": "Zisen Kong", "url": "https://arxiv.org/abs/2504.16368", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:pengyuan-li", "kind": "person", "label": "Pengyuan Li", "url": "https://arxiv.org/abs/2504.16368", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2208.03849", "kind": "paper", "label": "RadSegNet: A Reliable Approach to Radar Camera Fusion", "url": "https://arxiv.org/abs/2208.03849", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:kshitiz-bansal", "kind": "person", "label": "Kshitiz Bansal", "url": "https://arxiv.org/abs/2208.03849", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:keshav-rungta", "kind": "person", "label": "Keshav Rungta", "url": "https://arxiv.org/abs/2208.03849", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:dinesh-bharadia", "kind": "person", "label": "Dinesh Bharadia", "url": "https://arxiv.org/abs/2208.03849", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2009.08428", "kind": "paper", "label": "Radar-Camera Sensor Fusion for Joint Object Detection and Distance Estimation in Autonomous Vehicles", "url": "https://arxiv.org/abs/2009.08428", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2411.19860", "kind": "paper", "label": "SpaRC: Sparse Radar-Camera Fusion for 3D Object Detection", "url": "https://arxiv.org/abs/2411.19860", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:felix-fent", "kind": "person", "label": "Felix Fent", "url": "https://arxiv.org/abs/2411.19860", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2601.19314", "kind": "paper", "label": "Instance-Guided Radar Depth Estimation for 3D Object Detection", "url": "https://arxiv.org/abs/2601.19314", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:chen-chou-lo", "kind": "person", "label": "Chen-Chou Lo", "url": "https://arxiv.org/abs/2601.19314", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:patrick-vandewalle", "kind": "person", "label": "Patrick Vandewalle", "url": "https://arxiv.org/abs/2601.19314", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2603.21987", "kind": "paper", "label": "LRC-WeatherNet: LiDAR, RADAR, and Camera Fusion Network for Real-time Weather-type Classification in Autonomous Driving", "url": "https://arxiv.org/abs/2603.21987", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:nour-alhuda-albashir", "kind": "person", "label": "Nour Alhuda Albashir", "url": "https://arxiv.org/abs/2603.21987", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lars-pernickel", "kind": "person", "label": "Lars Pernickel", "url": "https://arxiv.org/abs/2603.21987", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:danial-hamoud", "kind": "person", "label": "Danial Hamoud", "url": "https://arxiv.org/abs/2603.21987", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:idriss-gouigah", "kind": "person", "label": "Idriss Gouigah", "url": "https://arxiv.org/abs/2603.21987", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:eren-erdal-aksoy", "kind": "person", "label": "Eren Erdal Aksoy", "url": "https://arxiv.org/abs/2603.21987", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2602.20632", "kind": "paper", "label": "Boosting Instance Awareness via Cross-View Correlation with 4D Radar and Camera for 3D Object Detection", "url": "https://arxiv.org/abs/2602.20632", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaokai-bai", "kind": "person", "label": "Xiaokai Bai", "url": "https://arxiv.org/abs/2602.20632", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:lianqing-zheng", "kind": "person", "label": "Lianqing Zheng", "url": "https://arxiv.org/abs/2602.20632", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:si-yuan-cao", "kind": "person", "label": "Si-Yuan Cao", "url": "https://arxiv.org/abs/2602.20632", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xiaohan-zhang", "kind": "person", "label": "Xiaohan Zhang", "url": "https://arxiv.org/abs/2602.20632", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:zhe-wu", "kind": "person", "label": "Zhe Wu", "url": "https://arxiv.org/abs/2602.20632", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:beinan-yu", "kind": "person", "label": "Beinan Yu", "url": "https://arxiv.org/abs/2602.20632", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:fang-wang", "kind": "person", "label": "Fang Wang", "url": "https://arxiv.org/abs/2602.20632", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jie-bai", "kind": "person", "label": "Jie Bai", "url": "https://arxiv.org/abs/2602.20632", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2604.08074", "kind": "paper", "label": "DinoRADE: Full Spectral Radar-Camera Fusion with Vision Foundation Model Features for Multi-class Object Detection in Adverse Weather", "url": "https://arxiv.org/abs/2604.08074", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:christof-leitgeb", "kind": "person", "label": "Christof Leitgeb", "url": "https://arxiv.org/abs/2604.08074", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:thomas-puchleitner", "kind": "person", "label": "Thomas Puchleitner", "url": "https://arxiv.org/abs/2604.08074", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:max-peter-ronecker", "kind": "person", "label": "Max Peter Ronecker", "url": "https://arxiv.org/abs/2604.08074", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:daniel-watzenig", "kind": "person", "label": "Daniel Watzenig", "url": "https://arxiv.org/abs/2604.08074", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2407.13937", "kind": "paper", "label": "Boosting Online 3D Multi-Object Tracking through Camera-Radar Cross Check", "url": "https://arxiv.org/abs/2407.13937", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:sheng-yao-kuan", "kind": "person", "label": "Sheng-Yao Kuan", "url": "https://arxiv.org/abs/2407.13937", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jen-hao-cheng", "kind": "person", "label": "Jen-Hao Cheng", "url": "https://arxiv.org/abs/2407.13937", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hsiang-wei-huang", "kind": "person", "label": "Hsiang-Wei Huang", "url": "https://arxiv.org/abs/2407.13937", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wenhao-chai", "kind": "person", "label": "Wenhao Chai", "url": "https://arxiv.org/abs/2407.13937", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:cheng-yen-yang", "kind": "person", "label": "Cheng-Yen Yang", "url": "https://arxiv.org/abs/2407.13937", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:hugo-latapie", "kind": "person", "label": "Hugo Latapie", "url": "https://arxiv.org/abs/2407.13937", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:bing-fei-wu", "kind": "person", "label": "Bing-Fei Wu", "url": "https://arxiv.org/abs/2407.13937", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2508.10567", "kind": "paper", "label": "SpaRC-AD: A Baseline for Radar-Camera Fusion in End-to-End Autonomous Driving", "url": "https://arxiv.org/abs/2508.10567", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2601.22054", "kind": "paper", "label": "MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources", "url": "https://arxiv.org/abs/2601.22054", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:baorui-ma", "kind": "person", "label": "Baorui Ma", "url": "https://arxiv.org/abs/2601.22054", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jiahui-yang", "kind": "person", "label": "Jiahui Yang", "url": "https://arxiv.org/abs/2601.22054", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:donglin-di", "kind": "person", "label": "Donglin Di", "url": "https://arxiv.org/abs/2601.22054", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:xuancheng-zhang", "kind": "person", "label": "Xuancheng Zhang", "url": "https://arxiv.org/abs/2601.22054", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jianxun-cui", "kind": "person", "label": "Jianxun Cui", "url": "https://arxiv.org/abs/2601.22054", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:yan-xie", "kind": "person", "label": "Yan Xie", "url": "https://arxiv.org/abs/2601.22054", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:wei-chen", "kind": "person", "label": "Wei Chen", "url": "https://arxiv.org/abs/2601.22054", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2604.13571", "kind": "paper", "label": "Radar-Informed 3D Multi-Object Tracking under Adverse Conditions", "url": "https://arxiv.org/abs/2604.13571", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:bingxue-xu", "kind": "person", "label": "Bingxue Xu", "url": "https://arxiv.org/abs/2604.13571", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:emil-hedemalm", "kind": "person", "label": "Emil Hedemalm", "url": "https://arxiv.org/abs/2604.13571", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ajinkya-khoche", "kind": "person", "label": "Ajinkya Khoche", "url": "https://arxiv.org/abs/2604.13571", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:patric-jensfelt", "kind": "person", "label": "Patric Jensfelt", "url": "https://arxiv.org/abs/2604.13571", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2104.14682", "kind": "paper", "label": "EagerMOT: 3D Multi-Object Tracking via Sensor Fusion", "url": "https://arxiv.org/abs/2104.14682", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:aleksandr-kim", "kind": "person", "label": "Aleksandr Kim", "url": "https://arxiv.org/abs/2104.14682", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:aljo-a-o-ep", "kind": "person", "label": "Aljo\u0161a O\u0161ep", "url": "https://arxiv.org/abs/2104.14682", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:laura-leal-taix", "kind": "person", "label": "Laura Leal-Taix\u00e9", "url": "https://arxiv.org/abs/2104.14682", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2408.13689", "kind": "paper", "label": "Decentralised Variational Inference Frameworks for Multi-object Tracking on Sensor Networks: Additional Notes", "url": "https://arxiv.org/abs/2408.13689", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:qing-li", "kind": "person", "label": "Qing Li", "url": "https://arxiv.org/abs/2408.13689", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:runze-gan", "kind": "person", "label": "Runze Gan", "url": "https://arxiv.org/abs/2408.13689", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:simon-godsill", "kind": "person", "label": "Simon Godsill", "url": "https://arxiv.org/abs/2408.13689", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2310.02532", "kind": "paper", "label": "ShaSTA-Fuse: Camera-LiDAR Sensor Fusion to Model Shape and Spatio-Temporal Affinities for 3D Multi-Object Tracking", "url": "https://arxiv.org/abs/2310.02532", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tara-sadjadpour", "kind": "person", "label": "Tara Sadjadpour", "url": "https://arxiv.org/abs/2310.02532", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:rares-ambrus", "kind": "person", "label": "Rares Ambrus", "url": "https://arxiv.org/abs/2310.02532", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jeannette-bohg", "kind": "person", "label": "Jeannette Bohg", "url": "https://arxiv.org/abs/2310.02532", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2302.14807", "kind": "paper", "label": "DFR-FastMOT: Detection Failure Resistant Tracker for Fast Multi-Object Tracking Based on Sensor Fusion", "url": "https://arxiv.org/abs/2302.14807", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:mohamed-nagy", "kind": "person", "label": "Mohamed Nagy", "url": "https://arxiv.org/abs/2302.14807", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:majid-khonji", "kind": "person", "label": "Majid Khonji", "url": "https://arxiv.org/abs/2302.14807", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:jorge-dias", "kind": "person", "label": "Jorge Dias", "url": "https://arxiv.org/abs/2302.14807", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:sajid-javed", "kind": "person", "label": "Sajid Javed", "url": "https://arxiv.org/abs/2302.14807", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2411.03702", "kind": "paper", "label": "Graph-Based Multi-Modal Sensor Fusion for Autonomous Driving", "url": "https://arxiv.org/abs/2411.03702", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:depanshu-sani", "kind": "person", "label": "Depanshu Sani", "url": "https://arxiv.org/abs/2411.03702", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:saket-anand", "kind": "person", "label": "Saket Anand", "url": "https://arxiv.org/abs/2411.03702", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2604.14013", "kind": "paper", "label": "Towards Multi-Object-Tracking with Radar on a Fast Moving Vehicle: On the Potential of Processing Radar in the Frequency Domain", "url": "https://arxiv.org/abs/2604.14013", "source": "arxiv", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:tim-hansen", "kind": "person", "label": "Tim Hansen", "url": "https://arxiv.org/abs/2604.14013", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:arturo-gomez-chavez", "kind": "person", "label": "Arturo Gomez-Chavez", "url": "https://arxiv.org/abs/2604.14013", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:ilya-shimchik", "kind": "person", "label": "Ilya Shimchik", "url": "https://arxiv.org/abs/2604.14013", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:person:andreas-birk", "kind": "person", "label": "Andreas Birk", "url": "https://arxiv.org/abs/2604.14013", "source": "arxiv-author", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2103.08049", "kind": "paper", "label": "Toward a Union-Find decoder for quantum LDPC codes", "url": "https://arxiv.org/abs/2103.08049", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:nicolas-delfosse", "kind": "person", "label": "Nicolas Delfosse", "url": "https://arxiv.org/abs/2103.08049", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:vivien-londe", "kind": "person", "label": "Vivien Londe", "url": "https://arxiv.org/abs/2103.08049", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:michael-beverland", "kind": "person", "label": "Michael Beverland", "url": "https://arxiv.org/abs/2103.08049", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2512.07057", "kind": "paper", "label": "Beam search decoder for quantum LDPC codes", "url": "https://arxiv.org/abs/2512.07057", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:min-ye", "kind": "person", "label": "Min Ye", "url": "https://arxiv.org/abs/2512.07057", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:dave-wecker", "kind": "person", "label": "Dave Wecker", "url": "https://arxiv.org/abs/2512.07057", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2412.08817", "kind": "paper", "label": "Cluster Decomposition for Improved Erasure Decoding of Quantum LDPC Codes", "url": "https://arxiv.org/abs/2412.08817", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:hanwen-yao", "kind": "person", "label": "Hanwen Yao", "url": "https://arxiv.org/abs/2412.08817", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:mert-g-kduman", "kind": "person", "label": "Mert G\u00f6kduman", "url": "https://arxiv.org/abs/2412.08817", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:henry-d-pfister", "kind": "person", "label": "Henry D. Pfister", "url": "https://arxiv.org/abs/2412.08817", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2504.05080", "kind": "paper", "label": "Online Gaussian elimination for quantum LDPC decoding", "url": "https://arxiv.org/abs/2504.05080", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:sam-j-griffiths", "kind": "person", "label": "Sam J. Griffiths", "url": "https://arxiv.org/abs/2504.05080", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:asmae-benhemou", "kind": "person", "label": "Asmae Benhemou", "url": "https://arxiv.org/abs/2504.05080", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:dan-e-browne", "kind": "person", "label": "Dan E. Browne", "url": "https://arxiv.org/abs/2504.05080", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1204.4223", "kind": "paper", "label": "Improved Quantum LDPC Decoding Strategies For The Misidentified Quantum Depolarizing Channel", "url": "https://arxiv.org/abs/1204.4223", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:yixuan-xie", "kind": "person", "label": "Yixuan Xie", "url": "https://arxiv.org/abs/1204.4223", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jun-li", "kind": "person", "label": "Jun Li", "url": "https://arxiv.org/abs/1204.4223", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:robert-malaney", "kind": "person", "label": "Robert Malaney", "url": "https://arxiv.org/abs/1204.4223", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jinhong-yuan", "kind": "person", "label": "Jinhong Yuan", "url": "https://arxiv.org/abs/1204.4223", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2205.06125", "kind": "paper", "label": "Stabilizer Inactivation for Message-Passing Decoding of Quantum LDPC Codes", "url": "https://arxiv.org/abs/2205.06125", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:julien-du-crest", "kind": "person", "label": "Julien du Crest", "url": "https://arxiv.org/abs/2205.06125", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:mehdi-mhalla", "kind": "person", "label": "Mehdi Mhalla", "url": "https://arxiv.org/abs/2205.06125", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:valentin-savin", "kind": "person", "label": "Valentin Savin", "url": "https://arxiv.org/abs/2205.06125", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2411.08177", "kind": "paper", "label": "Erasure Decoding for Quantum LDPC Codes via Belief Propagation with Guided Decimation", "url": "https://arxiv.org/abs/2411.08177", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2605.01035", "kind": "paper", "label": "A Scalable FPGA Architecture for Real-Time Decoding of Quantum LDPC Codes Using GARI", "url": "https://arxiv.org/abs/2605.01035", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:daniel-b-scones", "kind": "person", "label": "Daniel B\u00e1scones", "url": "https://arxiv.org/abs/2605.01035", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:arshpreet-singh-maan", "kind": "person", "label": "Arshpreet Singh Maan", "url": "https://arxiv.org/abs/2605.01035", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:francisco-garcia-herrero", "kind": "person", "label": "Francisco Garcia-Herrero", "url": "https://arxiv.org/abs/2605.01035", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2308.13377", "kind": "paper", "label": "Layered Decoding of Quantum LDPC Codes", "url": "https://arxiv.org/abs/2308.13377", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:javier-valls", "kind": "person", "label": "Javier Valls", "url": "https://arxiv.org/abs/2308.13377", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2508.04769", "kind": "paper", "label": "Power and Limitations of Linear Programming Decoder for Quantum LDPC Codes", "url": "https://arxiv.org/abs/2508.04769", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:shouzhen-gu", "kind": "person", "label": "Shouzhen Gu", "url": "https://arxiv.org/abs/2508.04769", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:mehdi-soleimanifar", "kind": "person", "label": "Mehdi Soleimanifar", "url": "https://arxiv.org/abs/2508.04769", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2310.17758", "kind": "paper", "label": "Graph Neural Networks for Enhanced Decoding of Quantum LDPC Codes", "url": "https://arxiv.org/abs/2310.17758", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:anqi-gong", "kind": "person", "label": "Anqi Gong", "url": "https://arxiv.org/abs/2310.17758", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:sebastian-cammerer", "kind": "person", "label": "Sebastian Cammerer", "url": "https://arxiv.org/abs/2310.17758", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:joseph-m-renes", "kind": "person", "label": "Joseph M. Renes", "url": "https://arxiv.org/abs/2310.17758", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2510.14060", "kind": "paper", "label": "Decoding Correlated Errors in Quantum LDPC Codes", "url": "https://arxiv.org/abs/2510.14060", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:alexandru-paler", "kind": "person", "label": "Alexandru Paler", "url": "https://arxiv.org/abs/2510.14060", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2005.07016", "kind": "paper", "label": "Decoding Across the Quantum LDPC Code Landscape", "url": "https://arxiv.org/abs/2005.07016", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:joschka-roffe", "kind": "person", "label": "Joschka Roffe", "url": "https://arxiv.org/abs/2005.07016", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:david-r-white", "kind": "person", "label": "David R. White", "url": "https://arxiv.org/abs/2005.07016", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:simon-burton", "kind": "person", "label": "Simon Burton", "url": "https://arxiv.org/abs/2005.07016", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:earl-t-campbell", "kind": "person", "label": "Earl T. Campbell", "url": "https://arxiv.org/abs/2005.07016", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2004.07935", "kind": "paper", "label": "Decodable quantum LDPC codes beyond the $\\sqrt{n}$ distance barrier using high dimensional expanders", "url": "https://arxiv.org/abs/2004.07935", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:shai-evra", "kind": "person", "label": "Shai Evra", "url": "https://arxiv.org/abs/2004.07935", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:tali-kaufman", "kind": "person", "label": "Tali Kaufman", "url": "https://arxiv.org/abs/2004.07935", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:gilles-z-mor", "kind": "person", "label": "Gilles Z\u00e9mor", "url": "https://arxiv.org/abs/2004.07935", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2507.00254", "kind": "paper", "label": "Fully Parallelized BP Decoding for Quantum LDPC Codes Can Outperform BP-OSD", "url": "https://arxiv.org/abs/2507.00254", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:ang-li", "kind": "person", "label": "Ang Li", "url": "https://arxiv.org/abs/2507.00254", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:frank-mueller", "kind": "person", "label": "Frank Mueller", "url": "https://arxiv.org/abs/2507.00254", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2310.07868", "kind": "paper", "label": "Viderman's algorithm for quantum LDPC codes", "url": "https://arxiv.org/abs/2310.07868", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:anirudh-krishna", "kind": "person", "label": "Anirudh Krishna", "url": "https://arxiv.org/abs/2310.07868", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:inbal-livni-navon", "kind": "person", "label": "Inbal Livni Navon", "url": "https://arxiv.org/abs/2310.07868", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:mary-wootters", "kind": "person", "label": "Mary Wootters", "url": "https://arxiv.org/abs/2310.07868", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1202.0357", "kind": "paper", "label": "Channel Identification and its Impact on Quantum LDPC Code Performance", "url": "https://arxiv.org/abs/1202.0357", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:1207.0732", "kind": "paper", "label": "Quantum LDPC Codes Constructed from Point-Line Subsets of the Finite Projective Plane", "url": "https://arxiv.org/abs/1207.0732", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:jacob-farinholt", "kind": "person", "label": "Jacob Farinholt", "url": "https://arxiv.org/abs/1207.0732", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2601.08824", "kind": "paper", "label": "Breaking the Orthogonality Barrier in Quantum LDPC Codes", "url": "https://arxiv.org/abs/2601.08824", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:kenta-kasai", "kind": "person", "label": "Kenta Kasai", "url": "https://arxiv.org/abs/2601.08824", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2308.08208", "kind": "paper", "label": "Quaternary Neural Belief Propagation Decoding of Quantum LDPC Codes with Overcomplete Check Matrices", "url": "https://arxiv.org/abs/2308.08208", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:sisi-miao", "kind": "person", "label": "Sisi Miao", "url": "https://arxiv.org/abs/2308.08208", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:alexander-schnerring", "kind": "person", "label": "Alexander Schnerring", "url": "https://arxiv.org/abs/2308.08208", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:haizheng-li", "kind": "person", "label": "Haizheng Li", "url": "https://arxiv.org/abs/2308.08208", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:laurent-schmalen", "kind": "person", "label": "Laurent Schmalen", "url": "https://arxiv.org/abs/2308.08208", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2606.17268", "kind": "paper", "label": "Breaking the bicycle frame: Coset-based quantum LDPC codes", "url": "https://arxiv.org/abs/2606.17268", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:arda-aydin", "kind": "person", "label": "Arda Aydin", "url": "https://arxiv.org/abs/2606.17268", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:itzhak-tamo", "kind": "person", "label": "Itzhak Tamo", "url": "https://arxiv.org/abs/2606.17268", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:alexander-barg", "kind": "person", "label": "Alexander Barg", "url": "https://arxiv.org/abs/2606.17268", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2511.04634", "kind": "paper", "label": "Random Construction of Quantum LDPC Codes", "url": "https://arxiv.org/abs/2511.04634", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:koki-okada", "kind": "person", "label": "Koki Okada", "url": "https://arxiv.org/abs/2511.04634", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1904.02703", "kind": "paper", "label": "Degenerate Quantum LDPC Codes With Good Finite Length Performance", "url": "https://arxiv.org/abs/1904.02703", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:pavel-panteleev", "kind": "person", "label": "Pavel Panteleev", "url": "https://arxiv.org/abs/1904.02703", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:gleb-kalachev", "kind": "person", "label": "Gleb Kalachev", "url": "https://arxiv.org/abs/1904.02703", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1712.08578", "kind": "paper", "label": "Golden codes: quantum LDPC codes built from regular tessellations of hyperbolic 4-manifolds", "url": "https://arxiv.org/abs/1712.08578", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:anthony-leverrier", "kind": "person", "label": "Anthony Leverrier", "url": "https://arxiv.org/abs/1712.08578", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:0712.4115", "kind": "paper", "label": "A Class of Quantum LDPC Codes Constructed From Finite Geometries", "url": "https://arxiv.org/abs/0712.4115", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:salah-a-aly", "kind": "person", "label": "Salah A. Aly", "url": "https://arxiv.org/abs/0712.4115", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2208.01002", "kind": "paper", "label": "Fast erasure decoder for hypergraph product codes", "url": "https://arxiv.org/abs/2208.01002", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:nicholas-connolly", "kind": "person", "label": "Nicholas Connolly", "url": "https://arxiv.org/abs/2208.01002", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2511.13281", "kind": "paper", "label": "Restart Belief: A General Quantum LDPC Decoder", "url": "https://arxiv.org/abs/2511.13281", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:lorenzo-valentini", "kind": "person", "label": "Lorenzo Valentini", "url": "https://arxiv.org/abs/2511.13281", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:diego-forlivesi", "kind": "person", "label": "Diego Forlivesi", "url": "https://arxiv.org/abs/2511.13281", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:andrea-talarico", "kind": "person", "label": "Andrea Talarico", "url": "https://arxiv.org/abs/2511.13281", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:marco-chiani", "kind": "person", "label": "Marco Chiani", "url": "https://arxiv.org/abs/2511.13281", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2402.01532", "kind": "paper", "label": "The closed-branch decoder for quantum LDPC codes", "url": "https://arxiv.org/abs/2402.01532", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:antonio-demarti-iolius", "kind": "person", "label": "Antonio deMarti iOlius", "url": "https://arxiv.org/abs/2402.01532", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:josu-etxezarreta-martinez", "kind": "person", "label": "Josu Etxezarreta Martinez", "url": "https://arxiv.org/abs/2402.01532", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2206.06557", "kind": "paper", "label": "An efficient decoder for a linear distance quantum LDPC code", "url": "https://arxiv.org/abs/2206.06557", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:christopher-a-pattison", "kind": "person", "label": "Christopher A. Pattison", "url": "https://arxiv.org/abs/2206.06557", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:eugene-tang", "kind": "person", "label": "Eugene Tang", "url": "https://arxiv.org/abs/2206.06557", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2503.01738", "kind": "paper", "label": "Automorphism Ensemble Decoding of Quantum LDPC Codes", "url": "https://arxiv.org/abs/2503.01738", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:stergios-koutsioumpas", "kind": "person", "label": "Stergios Koutsioumpas", "url": "https://arxiv.org/abs/2503.01738", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:hasan-sayginel", "kind": "person", "label": "Hasan Sayginel", "url": "https://arxiv.org/abs/2503.01738", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:mark-webster", "kind": "person", "label": "Mark Webster", "url": "https://arxiv.org/abs/2503.01738", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2311.11167", "kind": "paper", "label": "Benchmarking Machine Learning Models for Quantum Error Correction", "url": "https://arxiv.org/abs/2311.11167", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:yue-zhao", "kind": "person", "label": "Yue Zhao", "url": "https://arxiv.org/abs/2311.11167", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2110.10378", "kind": "paper", "label": "Machine Learning for Continuous Quantum Error Correction on Superconducting Qubits", "url": "https://arxiv.org/abs/2110.10378", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:ian-convy", "kind": "person", "label": "Ian Convy", "url": "https://arxiv.org/abs/2110.10378", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:haoran-liao", "kind": "person", "label": "Haoran Liao", "url": "https://arxiv.org/abs/2110.10378", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:song-zhang", "kind": "person", "label": "Song Zhang", "url": "https://arxiv.org/abs/2110.10378", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:sahil-patel", "kind": "person", "label": "Sahil Patel", "url": "https://arxiv.org/abs/2110.10378", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:william-p-livingston", "kind": "person", "label": "William P. Livingston", "url": "https://arxiv.org/abs/2110.10378", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:ho-nam-nguyen", "kind": "person", "label": "Ho Nam Nguyen", "url": "https://arxiv.org/abs/2110.10378", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:irfan-siddiqi", "kind": "person", "label": "Irfan Siddiqi", "url": "https://arxiv.org/abs/2110.10378", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:k-birgitta-whaley", "kind": "person", "label": "K. Birgitta Whaley", "url": "https://arxiv.org/abs/2110.10378", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2601.07223", "kind": "paper", "label": "Quantum Error Correction and Detection for Quantum Machine Learning", "url": "https://arxiv.org/abs/2601.07223", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:eromanga-adermann", "kind": "person", "label": "Eromanga Adermann", "url": "https://arxiv.org/abs/2601.07223", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:haiyue-kang", "kind": "person", "label": "Haiyue Kang", "url": "https://arxiv.org/abs/2601.07223", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:martin-sevior", "kind": "person", "label": "Martin Sevior", "url": "https://arxiv.org/abs/2601.07223", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:muhammad-usman", "kind": "person", "label": "Muhammad Usman", "url": "https://arxiv.org/abs/2601.07223", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2202.00555", "kind": "paper", "label": "Quantum Error Correction with Quantum Autoencoders", "url": "https://arxiv.org/abs/2202.00555", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:david-f-locher", "kind": "person", "label": "David F. Locher", "url": "https://arxiv.org/abs/2202.00555", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:lorenzo-cardarelli", "kind": "person", "label": "Lorenzo Cardarelli", "url": "https://arxiv.org/abs/2202.00555", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:markus-m-ller", "kind": "person", "label": "Markus M\u00fcller", "url": "https://arxiv.org/abs/2202.00555", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2506.11552", "kind": "paper", "label": "Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction", "url": "https://arxiv.org/abs/2506.11552", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:nico-meyer", "kind": "person", "label": "Nico Meyer", "url": "https://arxiv.org/abs/2506.11552", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:christopher-mutschler", "kind": "person", "label": "Christopher Mutschler", "url": "https://arxiv.org/abs/2506.11552", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:andreas-maier", "kind": "person", "label": "Andreas Maier", "url": "https://arxiv.org/abs/2506.11552", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:daniel-d-scherer", "kind": "person", "label": "Daniel D. Scherer", "url": "https://arxiv.org/abs/2506.11552", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2506.21707", "kind": "paper", "label": "Optimizing continuous-time quantum error correction for arbitrary noise", "url": "https://arxiv.org/abs/2506.21707", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:anirudh-lanka", "kind": "person", "label": "Anirudh Lanka", "url": "https://arxiv.org/abs/2506.21707", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:shashank-hegde", "kind": "person", "label": "Shashank Hegde", "url": "https://arxiv.org/abs/2506.21707", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:todd-a-brun", "kind": "person", "label": "Todd A. Brun", "url": "https://arxiv.org/abs/2506.21707", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2606.08592", "kind": "paper", "label": "Quantum Global Variational Learning for Quantum Error Correction", "url": "https://arxiv.org/abs/2606.08592", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:shun-ryuzaki", "kind": "person", "label": "Shun Ryuzaki", "url": "https://arxiv.org/abs/2606.08592", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:hideo-mukai", "kind": "person", "label": "Hideo Mukai", "url": "https://arxiv.org/abs/2606.08592", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2502.19971", "kind": "paper", "label": "Efficient and Universal Neural-Network Decoder for Stabilizer-Based Quantum Error Correction", "url": "https://arxiv.org/abs/2502.19971", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:gengyuan-hu", "kind": "person", "label": "Gengyuan Hu", "url": "https://arxiv.org/abs/2502.19971", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:wanli-ouyang", "kind": "person", "label": "Wanli Ouyang", "url": "https://arxiv.org/abs/2502.19971", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:chao-yang-lu", "kind": "person", "label": "Chao-Yang Lu", "url": "https://arxiv.org/abs/2502.19971", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:chen-lin", "kind": "person", "label": "Chen Lin", "url": "https://arxiv.org/abs/2502.19971", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:han-sen-zhong", "kind": "person", "label": "Han-Sen Zhong", "url": "https://arxiv.org/abs/2502.19971", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1812.08451", "kind": "paper", "label": "Optimizing Quantum Error Correction Codes with Reinforcement Learning", "url": "https://arxiv.org/abs/1812.08451", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:hendrik-poulsen-nautrup", "kind": "person", "label": "Hendrik Poulsen Nautrup", "url": "https://arxiv.org/abs/1812.08451", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:vedran-dunjko", "kind": "person", "label": "Vedran Dunjko", "url": "https://arxiv.org/abs/1812.08451", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:hans-j-briegel", "kind": "person", "label": "Hans J. Briegel", "url": "https://arxiv.org/abs/1812.08451", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:nicolai-friis", "kind": "person", "label": "Nicolai Friis", "url": "https://arxiv.org/abs/1812.08451", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1912.10063", "kind": "paper", "label": "Machine learning logical gates for quantum error correction", "url": "https://arxiv.org/abs/1912.10063", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:hongxiang-chen", "kind": "person", "label": "Hongxiang Chen", "url": "https://arxiv.org/abs/1912.10063", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:michael-vasmer", "kind": "person", "label": "Michael Vasmer", "url": "https://arxiv.org/abs/1912.10063", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:nikolas-p-breuckmann", "kind": "person", "label": "Nikolas P. Breuckmann", "url": "https://arxiv.org/abs/1912.10063", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:edward-grant", "kind": "person", "label": "Edward Grant", "url": "https://arxiv.org/abs/1912.10063", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1711.02249", "kind": "paper", "label": "QVECTOR: an algorithm for device-tailored quantum error correction", "url": "https://arxiv.org/abs/1711.02249", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:peter-d-johnson", "kind": "person", "label": "Peter D. Johnson", "url": "https://arxiv.org/abs/1711.02249", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jonathan-romero", "kind": "person", "label": "Jonathan Romero", "url": "https://arxiv.org/abs/1711.02249", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jonathan-olson", "kind": "person", "label": "Jonathan Olson", "url": "https://arxiv.org/abs/1711.02249", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yudong-cao", "kind": "person", "label": "Yudong Cao", "url": "https://arxiv.org/abs/1711.02249", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:al-n-aspuru-guzik", "kind": "person", "label": "Al\u00e1n Aspuru-Guzik", "url": "https://arxiv.org/abs/1711.02249", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2504.19651", "kind": "paper", "label": "Fooling the Decoder: An Adversarial Attack on Quantum Error Correction", "url": "https://arxiv.org/abs/2504.19651", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:jerome-lenssen", "kind": "person", "label": "Jerome Lenssen", "url": "https://arxiv.org/abs/2504.19651", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2511.12482", "kind": "paper", "label": "Discovering autonomous quantum error correction via deep reinforcement learning", "url": "https://arxiv.org/abs/2511.12482", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:yue-yin", "kind": "person", "label": "Yue Yin", "url": "https://arxiv.org/abs/2511.12482", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:tailong-xiao", "kind": "person", "label": "Tailong Xiao", "url": "https://arxiv.org/abs/2511.12482", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:xiaoyang-deng", "kind": "person", "label": "Xiaoyang Deng", "url": "https://arxiv.org/abs/2511.12482", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:ming-he", "kind": "person", "label": "Ming He", "url": "https://arxiv.org/abs/2511.12482", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jianping-fan", "kind": "person", "label": "Jianping Fan", "url": "https://arxiv.org/abs/2511.12482", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:guihua-zeng", "kind": "person", "label": "Guihua Zeng", "url": "https://arxiv.org/abs/2511.12482", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2507.12253", "kind": "paper", "label": "Design Automation in Quantum Error Correction", "url": "https://arxiv.org/abs/2507.12253", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:archisman-ghosh", "kind": "person", "label": "Archisman Ghosh", "url": "https://arxiv.org/abs/2507.12253", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:avimita-chatterjee", "kind": "person", "label": "Avimita Chatterjee", "url": "https://arxiv.org/abs/2507.12253", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:swaroop-ghosh", "kind": "person", "label": "Swaroop Ghosh", "url": "https://arxiv.org/abs/2507.12253", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2503.21374", "kind": "paper", "label": "Generative Decoding for Quantum Error-correcting Codes", "url": "https://arxiv.org/abs/2503.21374", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:hanyan-cao", "kind": "person", "label": "Hanyan Cao", "url": "https://arxiv.org/abs/2503.21374", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:feng-pan", "kind": "person", "label": "Feng Pan", "url": "https://arxiv.org/abs/2503.21374", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:dongyang-feng", "kind": "person", "label": "Dongyang Feng", "url": "https://arxiv.org/abs/2503.21374", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yijia-wang", "kind": "person", "label": "Yijia Wang", "url": "https://arxiv.org/abs/2503.21374", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:pan-zhang", "kind": "person", "label": "Pan Zhang", "url": "https://arxiv.org/abs/2503.21374", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2202.08600", "kind": "paper", "label": "Decoherence and Quantum Error Correction for Quantum Computing and Communications", "url": "https://arxiv.org/abs/2202.08600", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2311.16082", "kind": "paper", "label": "Transformer-QEC: Quantum Error Correction Code Decoding with Transferable Transformers", "url": "https://arxiv.org/abs/2311.16082", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:hanrui-wang", "kind": "person", "label": "Hanrui Wang", "url": "https://arxiv.org/abs/2311.16082", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:pengyu-liu", "kind": "person", "label": "Pengyu Liu", "url": "https://arxiv.org/abs/2311.16082", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:kevin-shao", "kind": "person", "label": "Kevin Shao", "url": "https://arxiv.org/abs/2311.16082", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:dantong-li", "kind": "person", "label": "Dantong Li", "url": "https://arxiv.org/abs/2311.16082", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jiaqi-gu", "kind": "person", "label": "Jiaqi Gu", "url": "https://arxiv.org/abs/2311.16082", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:david-z-pan", "kind": "person", "label": "David Z. Pan", "url": "https://arxiv.org/abs/2311.16082", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yongshan-ding", "kind": "person", "label": "Yongshan Ding", "url": "https://arxiv.org/abs/2311.16082", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2510.22724", "kind": "paper", "label": "Scalable Neural Decoders for Practical Real-Time Quantum Error Correction", "url": "https://arxiv.org/abs/2510.22724", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:changwon-lee", "kind": "person", "label": "Changwon Lee", "url": "https://arxiv.org/abs/2510.22724", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:tak-hur", "kind": "person", "label": "Tak Hur", "url": "https://arxiv.org/abs/2510.22724", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:daniel-k-park", "kind": "person", "label": "Daniel K. Park", "url": "https://arxiv.org/abs/2510.22724", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2412.20380", "kind": "paper", "label": "Artificial Intelligence for Quantum Error Correction: A Comprehensive Review", "url": "https://arxiv.org/abs/2412.20380", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:zihao-wang", "kind": "person", "label": "Zihao Wang", "url": "https://arxiv.org/abs/2412.20380", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2208.05879", "kind": "paper", "label": "Transmon qubit readout fidelity at the threshold for quantum error correction without a quantum-limited amplifier", "url": "https://arxiv.org/abs/2208.05879", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:hang-xi-li", "kind": "person", "label": "Hang-Xi Li", "url": "https://arxiv.org/abs/2208.05879", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yong-lu", "kind": "person", "label": "Yong Lu", "url": "https://arxiv.org/abs/2208.05879", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:christopher-w-warren", "kind": "person", "label": "Christopher W. Warren", "url": "https://arxiv.org/abs/2208.05879", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:christian-j-kri-an", "kind": "person", "label": "Christian J. Kri\u017ean", "url": "https://arxiv.org/abs/2208.05879", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:sandoko-kosen", "kind": "person", "label": "Sandoko Kosen", "url": "https://arxiv.org/abs/2208.05879", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:marcus-rommel", "kind": "person", "label": "Marcus Rommel", "url": "https://arxiv.org/abs/2208.05879", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:shahnawaz-ahmed", "kind": "person", "label": "Shahnawaz Ahmed", "url": "https://arxiv.org/abs/2208.05879", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2605.12046", "kind": "paper", "label": "Rethink the Role of Neural Decoders in Quantum Error Correction", "url": "https://arxiv.org/abs/2605.12046", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:ge-yan", "kind": "person", "label": "Ge Yan", "url": "https://arxiv.org/abs/2605.12046", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:shanchuan-li", "kind": "person", "label": "Shanchuan Li", "url": "https://arxiv.org/abs/2605.12046", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yuxuan-du", "kind": "person", "label": "Yuxuan Du", "url": "https://arxiv.org/abs/2605.12046", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2605.17230", "kind": "paper", "label": "Maximum Likelihood Decoding of Quantum Error Correction Codes", "url": "https://arxiv.org/abs/2605.17230", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:1810.03787", "kind": "paper", "label": "Quantum Convolutional Neural Networks", "url": "https://arxiv.org/abs/1810.03787", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:iris-cong", "kind": "person", "label": "Iris Cong", "url": "https://arxiv.org/abs/1810.03787", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:soonwon-choi", "kind": "person", "label": "Soonwon Choi", "url": "https://arxiv.org/abs/1810.03787", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:mikhail-d-lukin", "kind": "person", "label": "Mikhail D. Lukin", "url": "https://arxiv.org/abs/1810.03787", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2509.16242", "kind": "paper", "label": "Machine Learning for Quantum Noise Reduction", "url": "https://arxiv.org/abs/2509.16242", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:karan-kendre", "kind": "person", "label": "Karan Kendre", "url": "https://arxiv.org/abs/2509.16242", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2605.28162", "kind": "paper", "label": "Learning Logical Operations for Arbitrary Quantum Error Correction Codes", "url": "https://arxiv.org/abs/2605.28162", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:dominik-seu", "kind": "person", "label": "Dominik Seu\u00df", "url": "https://arxiv.org/abs/2605.28162", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2307.09463", "kind": "paper", "label": "A Cryogenic Memristive Neural Decoder for Fault-tolerant Quantum Error Correction", "url": "https://arxiv.org/abs/2307.09463", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:victor-yon", "kind": "person", "label": "Victor Yon", "url": "https://arxiv.org/abs/2307.09463", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:fr-d-ric-marcotte", "kind": "person", "label": "Fr\u00e9d\u00e9ric Marcotte", "url": "https://arxiv.org/abs/2307.09463", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:pierre-antoine-mouny", "kind": "person", "label": "Pierre-Antoine Mouny", "url": "https://arxiv.org/abs/2307.09463", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:gebremedhin-a-dagnew", "kind": "person", "label": "Gebremedhin A. Dagnew", "url": "https://arxiv.org/abs/2307.09463", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:bohdan-kulchytskyy", "kind": "person", "label": "Bohdan Kulchytskyy", "url": "https://arxiv.org/abs/2307.09463", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:sophie-rochette", "kind": "person", "label": "Sophie Rochette", "url": "https://arxiv.org/abs/2307.09463", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yann-beilliard", "kind": "person", "label": "Yann Beilliard", "url": "https://arxiv.org/abs/2307.09463", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:dominique-drouin", "kind": "person", "label": "Dominique Drouin", "url": "https://arxiv.org/abs/2307.09463", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2601.18562", "kind": "paper", "label": "Bayesian Optimization for Quantum Error-Correcting Code Discovery", "url": "https://arxiv.org/abs/2601.18562", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:yihua-chengyu", "kind": "person", "label": "Yihua Chengyu", "url": "https://arxiv.org/abs/2601.18562", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:richard-meister", "kind": "person", "label": "Richard Meister", "url": "https://arxiv.org/abs/2601.18562", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:conor-carty", "kind": "person", "label": "Conor Carty", "url": "https://arxiv.org/abs/2601.18562", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:sheng-ku-lin", "kind": "person", "label": "Sheng-Ku Lin", "url": "https://arxiv.org/abs/2601.18562", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:roberto-bondesan", "kind": "person", "label": "Roberto Bondesan", "url": "https://arxiv.org/abs/2601.18562", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1908.01092", "kind": "paper", "label": "Machine-learning based three-qubit gate for realization of a Toffoli gate with cQED-based transmon systems", "url": "https://arxiv.org/abs/1908.01092", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:sahar-daraeizadeh", "kind": "person", "label": "Sahar Daraeizadeh", "url": "https://arxiv.org/abs/1908.01092", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:shavindra-p-premaratne", "kind": "person", "label": "Shavindra P. Premaratne", "url": "https://arxiv.org/abs/1908.01092", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:xiaoyu-song", "kind": "person", "label": "Xiaoyu Song", "url": "https://arxiv.org/abs/1908.01092", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:marek-perkowski", "kind": "person", "label": "Marek Perkowski", "url": "https://arxiv.org/abs/1908.01092", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:anne-y-matsuura", "kind": "person", "label": "Anne Y. Matsuura", "url": "https://arxiv.org/abs/1908.01092", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2202.05741", "kind": "paper", "label": "Neural-Network Decoders for Quantum Error Correction using Surface Codes:A Space Exploration of the Hardware Cost-Performance Trade-Offs", "url": "https://arxiv.org/abs/2202.05741", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:ramon-overwater", "kind": "person", "label": "Ramon Overwater", "url": "https://arxiv.org/abs/2202.05741", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:masoud-babaie", "kind": "person", "label": "Masoud Babaie", "url": "https://arxiv.org/abs/2202.05741", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:fabio-sebastiano", "kind": "person", "label": "Fabio Sebastiano", "url": "https://arxiv.org/abs/2202.05741", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2606.08758", "kind": "paper", "label": "Neural network decoder confidence as a learned proxy for the logical gap", "url": "https://arxiv.org/abs/2606.08758", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:david-dentelski", "kind": "person", "label": "David Dentelski", "url": "https://arxiv.org/abs/2606.08758", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2601.09921", "kind": "paper", "label": "Learning to Decode in Parallel: Self-Coordinating Neural Network for Real-Time Quantum Error Correction", "url": "https://arxiv.org/abs/2601.09921", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:kai-zhang", "kind": "person", "label": "Kai Zhang", "url": "https://arxiv.org/abs/2601.09921", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:zhengzhong-yi", "kind": "person", "label": "Zhengzhong Yi", "url": "https://arxiv.org/abs/2601.09921", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:shaojun-guo", "kind": "person", "label": "Shaojun Guo", "url": "https://arxiv.org/abs/2601.09921", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:linghang-kong", "kind": "person", "label": "Linghang Kong", "url": "https://arxiv.org/abs/2601.09921", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:situ-wang", "kind": "person", "label": "Situ Wang", "url": "https://arxiv.org/abs/2601.09921", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:xiaoyu-zhan", "kind": "person", "label": "Xiaoyu Zhan", "url": "https://arxiv.org/abs/2601.09921", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:tan-he", "kind": "person", "label": "Tan He", "url": "https://arxiv.org/abs/2601.09921", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:weiping-lin", "kind": "person", "label": "Weiping Lin", "url": "https://arxiv.org/abs/2601.09921", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2505.22741", "kind": "paper", "label": "Importance sampling for data-driven decoding of quantum error-correcting codes", "url": "https://arxiv.org/abs/2505.22741", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:evan-peters", "kind": "person", "label": "Evan Peters", "url": "https://arxiv.org/abs/2505.22741", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1705.07855", "kind": "paper", "label": "Machine-learning-assisted correction of correlated qubit errors in a topological code", "url": "https://arxiv.org/abs/1705.07855", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:p-baireuther", "kind": "person", "label": "P. Baireuther", "url": "https://arxiv.org/abs/1705.07855", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:t-e-o-brien", "kind": "person", "label": "T. E. O'Brien", "url": "https://arxiv.org/abs/1705.07855", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:b-tarasinski", "kind": "person", "label": "B. Tarasinski", "url": "https://arxiv.org/abs/1705.07855", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:c-w-j-beenakker", "kind": "person", "label": "C. W. J. Beenakker", "url": "https://arxiv.org/abs/1705.07855", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1705.00857", "kind": "paper", "label": "Decoding Small Surface Codes with Feedforward Neural Networks", "url": "https://arxiv.org/abs/1705.00857", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:savvas-varsamopoulos", "kind": "person", "label": "Savvas Varsamopoulos", "url": "https://arxiv.org/abs/1705.00857", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:ben-criger", "kind": "person", "label": "Ben Criger", "url": "https://arxiv.org/abs/1705.00857", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:koen-bertels", "kind": "person", "label": "Koen Bertels", "url": "https://arxiv.org/abs/1705.00857", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2511.01741", "kind": "paper", "label": "HyperNQ: A Hypergraph Neural Network Decoder for Quantum LDPC Codes", "url": "https://arxiv.org/abs/2511.01741", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:ameya-s-bhave", "kind": "person", "label": "Ameya S. Bhave", "url": "https://arxiv.org/abs/2511.01741", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:navnil-choudhury", "kind": "person", "label": "Navnil Choudhury", "url": "https://arxiv.org/abs/2511.01741", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:kanad-basu", "kind": "person", "label": "Kanad Basu", "url": "https://arxiv.org/abs/2511.01741", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2502.20269", "kind": "paper", "label": "On the interpretability of neural network decoders", "url": "https://arxiv.org/abs/2502.20269", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:lukas-b-deker", "kind": "person", "label": "Lukas B\u00f6deker", "url": "https://arxiv.org/abs/2502.20269", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:luc-j-b-kusters", "kind": "person", "label": "Luc J. B. Kusters", "url": "https://arxiv.org/abs/2502.20269", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2606.22194", "kind": "paper", "label": "Machine Learning Optimal Quantum Error Correction Thresholds", "url": "https://arxiv.org/abs/2606.22194", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:dominik-seip", "kind": "person", "label": "Dominik Seip", "url": "https://arxiv.org/abs/2606.22194", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:luis-colmenarez", "kind": "person", "label": "Luis Colmenarez", "url": "https://arxiv.org/abs/2606.22194", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:markus-schmitt", "kind": "person", "label": "Markus Schmitt", "url": "https://arxiv.org/abs/2606.22194", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2509.03815", "kind": "paper", "label": "Learning Neural Decoding with Parallelism and Self-Coordination for Quantum Error Correction", "url": "https://arxiv.org/abs/2509.03815", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:fang-zhang", "kind": "person", "label": "Fang Zhang", "url": "https://arxiv.org/abs/2509.03815", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:zhengfeng-ji", "kind": "person", "label": "Zhengfeng Ji", "url": "https://arxiv.org/abs/2509.03815", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jianxin-chen", "kind": "person", "label": "Jianxin Chen", "url": "https://arxiv.org/abs/2509.03815", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2605.04892", "kind": "paper", "label": "Real-time Surface-Code Error Correction Using an FPGA-based Neural-Network Decoder", "url": "https://arxiv.org/abs/2605.04892", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:xiaohan-yang", "kind": "person", "label": "Xiaohan Yang", "url": "https://arxiv.org/abs/2605.04892", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:xuandong-sun", "kind": "person", "label": "Xuandong Sun", "url": "https://arxiv.org/abs/2605.04892", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:zhiyi-wu", "kind": "person", "label": "Zhiyi Wu", "url": "https://arxiv.org/abs/2605.04892", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:ji-jiang", "kind": "person", "label": "Ji Jiang", "url": "https://arxiv.org/abs/2605.04892", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:xiayu-linpeng", "kind": "person", "label": "Xiayu Linpeng", "url": "https://arxiv.org/abs/2605.04892", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yuxuan-zhou", "kind": "person", "label": "Yuxuan Zhou", "url": "https://arxiv.org/abs/2605.04892", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:ji-chu", "kind": "person", "label": "Ji Chu", "url": "https://arxiv.org/abs/2605.04892", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1710.09489", "kind": "paper", "label": "Scalable Neural Network Decoders for Higher Dimensional Quantum Codes", "url": "https://arxiv.org/abs/1710.09489", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:xiaotong-ni", "kind": "person", "label": "Xiaotong Ni", "url": "https://arxiv.org/abs/1710.09489", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2604.08358", "kind": "paper", "label": "Scalable Neural Decoders for Practical Fault-Tolerant Quantum Computation", "url": "https://arxiv.org/abs/2604.08358", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:andi-gu", "kind": "person", "label": "Andi Gu", "url": "https://arxiv.org/abs/2604.08358", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:j-pablo-bonilla-ataides", "kind": "person", "label": "J. Pablo Bonilla Ataides", "url": "https://arxiv.org/abs/2604.08358", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:susanne-f-yelin", "kind": "person", "label": "Susanne F. Yelin", "url": "https://arxiv.org/abs/2604.08358", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2506.16113", "kind": "paper", "label": "Fully convolutional 3D neural network decoders for surface codes with syndrome circuit noise", "url": "https://arxiv.org/abs/2506.16113", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:spiro-gicev", "kind": "person", "label": "Spiro Gicev", "url": "https://arxiv.org/abs/2506.16113", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:lloyd-c-l-hollenberg", "kind": "person", "label": "Lloyd C. L. Hollenberg", "url": "https://arxiv.org/abs/2506.16113", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2511.17460", "kind": "paper", "label": "Improved error correction with leakage reduction units built into qubit measurement in a superconducting quantum processor", "url": "https://arxiv.org/abs/2511.17460", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:yuejie-xin", "kind": "person", "label": "Yuejie Xin", "url": "https://arxiv.org/abs/2511.17460", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:sean-l-m-van-der-meer", "kind": "person", "label": "Sean L. M. van der Meer", "url": "https://arxiv.org/abs/2511.17460", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:marc-serra-peralta", "kind": "person", "label": "Marc Serra-Peralta", "url": "https://arxiv.org/abs/2511.17460", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:tim-h-f-vroomans", "kind": "person", "label": "Tim H. F. Vroomans", "url": "https://arxiv.org/abs/2511.17460", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:matvey-finkel", "kind": "person", "label": "Matvey Finkel", "url": "https://arxiv.org/abs/2511.17460", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:hendrik-m-veen", "kind": "person", "label": "Hendrik M. Veen", "url": "https://arxiv.org/abs/2511.17460", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:mark-w-beekman", "kind": "person", "label": "Mark W. Beekman", "url": "https://arxiv.org/abs/2511.17460", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:leonardo-dicarlo", "kind": "person", "label": "Leonardo DiCarlo", "url": "https://arxiv.org/abs/2511.17460", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2508.03783", "kind": "paper", "label": "Probing and Enhancing the Robustness of GNN-based QEC Decoders with Reinforcement Learning", "url": "https://arxiv.org/abs/2508.03783", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:ryota-ikeda", "kind": "person", "label": "Ryota Ikeda", "url": "https://arxiv.org/abs/2508.03783", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2607.01473", "kind": "paper", "label": "Surface code logical operations on a superconducting quantum processor", "url": "https://arxiv.org/abs/2607.01473", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:yuwei-ma", "kind": "person", "label": "Yuwei Ma", "url": "https://arxiv.org/abs/2607.01473", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jiahao-bei", "kind": "person", "label": "Jiahao Bei", "url": "https://arxiv.org/abs/2607.01473", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jianbin-cai", "kind": "person", "label": "Jianbin Cai", "url": "https://arxiv.org/abs/2607.01473", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:sirui-cao", "kind": "person", "label": "Sirui Cao", "url": "https://arxiv.org/abs/2607.01473", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2510.04526", "kind": "paper", "label": "Subsystem many-hypercube codes: High-rate concatenated codes with low-weight syndrome measurements", "url": "https://arxiv.org/abs/2510.04526", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:ryota-nakai", "kind": "person", "label": "Ryota Nakai", "url": "https://arxiv.org/abs/2510.04526", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:hayato-goto", "kind": "person", "label": "Hayato Goto", "url": "https://arxiv.org/abs/2510.04526", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1903.10254", "kind": "paper", "label": "Decoding quantum error correction with Ising model hardware", "url": "https://arxiv.org/abs/1903.10254", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:stefan-zohren", "kind": "person", "label": "Stefan Zohren", "url": "https://arxiv.org/abs/1903.10254", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:dominic-horsman", "kind": "person", "label": "Dominic Horsman", "url": "https://arxiv.org/abs/1903.10254", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:nicholas-chancellor", "kind": "person", "label": "Nicholas Chancellor", "url": "https://arxiv.org/abs/1903.10254", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2303.00054", "kind": "paper", "label": "Real-Time Decoding for Fault-Tolerant Quantum Computing: Progress, Challenges and Outlook", "url": "https://arxiv.org/abs/2303.00054", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:francesco-battistel", "kind": "person", "label": "Francesco Battistel", "url": "https://arxiv.org/abs/2303.00054", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:christopher-chamberland", "kind": "person", "label": "Christopher Chamberland", "url": "https://arxiv.org/abs/2303.00054", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:kauser-johar", "kind": "person", "label": "Kauser Johar", "url": "https://arxiv.org/abs/2303.00054", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:ramon-w-j-overwater", "kind": "person", "label": "Ramon W. J. Overwater", "url": "https://arxiv.org/abs/2303.00054", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:luka-skoric", "kind": "person", "label": "Luka Skoric", "url": "https://arxiv.org/abs/2303.00054", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yosuke-ueno", "kind": "person", "label": "Yosuke Ueno", "url": "https://arxiv.org/abs/2303.00054", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2605.30765", "kind": "paper", "label": "Real-Time Quantum Error Correction System Stack: Architecture, Algorithms, and Engineering Practice", "url": "https://arxiv.org/abs/2605.30765", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:yaojian-chen", "kind": "person", "label": "Yaojian Chen", "url": "https://arxiv.org/abs/2605.30765", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:chun-yang-luan", "kind": "person", "label": "Chun-Yang Luan", "url": "https://arxiv.org/abs/2605.30765", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:peilin-zheng", "kind": "person", "label": "Peilin Zheng", "url": "https://arxiv.org/abs/2605.30765", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:xianghong-zeng", "kind": "person", "label": "Xianghong Zeng", "url": "https://arxiv.org/abs/2605.30765", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jia-yi-hou", "kind": "person", "label": "Jia-Yi Hou", "url": "https://arxiv.org/abs/2605.30765", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:zhuo-fu", "kind": "person", "label": "Zhuo Fu", "url": "https://arxiv.org/abs/2605.30765", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yirong-jin", "kind": "person", "label": "Yirong Jin", "url": "https://arxiv.org/abs/2605.30765", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:fei-wang", "kind": "person", "label": "Fei Wang", "url": "https://arxiv.org/abs/2605.30765", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2410.05202", "kind": "paper", "label": "Demonstrating real-time and low-latency quantum error correction with superconducting qubits", "url": "https://arxiv.org/abs/2410.05202", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:laura-caune", "kind": "person", "label": "Laura Caune", "url": "https://arxiv.org/abs/2410.05202", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:nick-s-blunt", "kind": "person", "label": "Nick S. Blunt", "url": "https://arxiv.org/abs/2410.05202", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:archibald-ruban", "kind": "person", "label": "Archibald Ruban", "url": "https://arxiv.org/abs/2410.05202", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jimmy-mcdaniel", "kind": "person", "label": "Jimmy McDaniel", "url": "https://arxiv.org/abs/2410.05202", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:joseph-a-valery", "kind": "person", "label": "Joseph A. Valery", "url": "https://arxiv.org/abs/2410.05202", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:andrew-d-patterson", "kind": "person", "label": "Andrew D. Patterson", "url": "https://arxiv.org/abs/2410.05202", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:alexander-v-gramolin", "kind": "person", "label": "Alexander V. Gramolin", "url": "https://arxiv.org/abs/2410.05202", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2108.06569", "kind": "paper", "label": "LILLIPUT: A Lightweight Low-Latency Lookup-Table Based Decoder for Near-term Quantum Error Correction", "url": "https://arxiv.org/abs/2108.06569", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:poulami-das", "kind": "person", "label": "Poulami Das", "url": "https://arxiv.org/abs/2108.06569", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:aditya-locharla", "kind": "person", "label": "Aditya Locharla", "url": "https://arxiv.org/abs/2108.06569", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:cody-jones", "kind": "person", "label": "Cody Jones", "url": "https://arxiv.org/abs/2108.06569", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2404.03136", "kind": "paper", "label": "Promatch: Extending the Reach of Real-Time Quantum Error Correction with Adaptive Predecoding", "url": "https://arxiv.org/abs/2404.03136", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:narges-alavisamani", "kind": "person", "label": "Narges Alavisamani", "url": "https://arxiv.org/abs/2404.03136", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:suhas-vittal", "kind": "person", "label": "Suhas Vittal", "url": "https://arxiv.org/abs/2404.03136", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:ramin-ayanzadeh", "kind": "person", "label": "Ramin Ayanzadeh", "url": "https://arxiv.org/abs/2404.03136", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:moinuddin-qureshi", "kind": "person", "label": "Moinuddin Qureshi", "url": "https://arxiv.org/abs/2404.03136", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2601.16123", "kind": "paper", "label": "Calibration-Conditioned FiLM Decoders for Low-Latency Decoding of Quantum Error Correction Evaluated on IBM Repetition-Code Experiments", "url": "https://arxiv.org/abs/2601.16123", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:samuel-stein", "kind": "person", "label": "Samuel Stein", "url": "https://arxiv.org/abs/2601.16123", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:shuwen-kan", "kind": "person", "label": "Shuwen Kan", "url": "https://arxiv.org/abs/2601.16123", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:chenxu-liu", "kind": "person", "label": "Chenxu Liu", "url": "https://arxiv.org/abs/2601.16123", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:adrian-harkness", "kind": "person", "label": "Adrian Harkness", "url": "https://arxiv.org/abs/2601.16123", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:sean-garner", "kind": "person", "label": "Sean Garner", "url": "https://arxiv.org/abs/2601.16123", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:zefan-du", "kind": "person", "label": "Zefan Du", "url": "https://arxiv.org/abs/2601.16123", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yufei-ding", "kind": "person", "label": "Yufei Ding", "url": "https://arxiv.org/abs/2601.16123", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:ying-mao", "kind": "person", "label": "Ying Mao", "url": "https://arxiv.org/abs/2601.16123", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2408.13687", "kind": "paper", "label": "Quantum error correction below the surface code threshold", "url": "https://arxiv.org/abs/2408.13687", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:rajeev-acharya", "kind": "person", "label": "Rajeev Acharya", "url": "https://arxiv.org/abs/2408.13687", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:laleh-aghababaie-beni", "kind": "person", "label": "Laleh Aghababaie-Beni", "url": "https://arxiv.org/abs/2408.13687", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:igor-aleiner", "kind": "person", "label": "Igor Aleiner", "url": "https://arxiv.org/abs/2408.13687", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:trond-i-andersen", "kind": "person", "label": "Trond I. Andersen", "url": "https://arxiv.org/abs/2408.13687", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:markus-ansmann", "kind": "person", "label": "Markus Ansmann", "url": "https://arxiv.org/abs/2408.13687", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:frank-arute", "kind": "person", "label": "Frank Arute", "url": "https://arxiv.org/abs/2408.13687", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:kunal-arya", "kind": "person", "label": "Kunal Arya", "url": "https://arxiv.org/abs/2408.13687", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:abraham-asfaw", "kind": "person", "label": "Abraham Asfaw", "url": "https://arxiv.org/abs/2408.13687", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2510.25222", "kind": "paper", "label": "Decoder Switching: Breaking the Speed-Accuracy Tradeoff in Real-Time Quantum Error Correction", "url": "https://arxiv.org/abs/2510.25222", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:riki-toshio", "kind": "person", "label": "Riki Toshio", "url": "https://arxiv.org/abs/2510.25222", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:kaito-kishi", "kind": "person", "label": "Kaito Kishi", "url": "https://arxiv.org/abs/2510.25222", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jun-fujisaki", "kind": "person", "label": "Jun Fujisaki", "url": "https://arxiv.org/abs/2510.25222", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:hirotaka-oshima", "kind": "person", "label": "Hirotaka Oshima", "url": "https://arxiv.org/abs/2510.25222", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:shintaro-sato", "kind": "person", "label": "Shintaro Sato", "url": "https://arxiv.org/abs/2510.25222", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:keisuke-fujii", "kind": "person", "label": "Keisuke Fujii", "url": "https://arxiv.org/abs/2510.25222", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2605.03180", "kind": "paper", "label": "Mitigating Classical Resource Costs in Quantum Error Correction via Generalized qLDPC Predecoding", "url": "https://arxiv.org/abs/2605.03180", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:alexander-knapen", "kind": "person", "label": "Alexander Knapen", "url": "https://arxiv.org/abs/2605.03180", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:junyi-luo", "kind": "person", "label": "Junyi Luo", "url": "https://arxiv.org/abs/2605.03180", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:guanchen-tao", "kind": "person", "label": "Guanchen Tao", "url": "https://arxiv.org/abs/2605.03180", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:tomas-bruno", "kind": "person", "label": "Tomas Bruno", "url": "https://arxiv.org/abs/2605.03180", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:qirui-zhang", "kind": "person", "label": "Qirui Zhang", "url": "https://arxiv.org/abs/2605.03180", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:dennis-sylvester", "kind": "person", "label": "Dennis Sylvester", "url": "https://arxiv.org/abs/2605.03180", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:mehdi-saligane", "kind": "person", "label": "Mehdi Saligane", "url": "https://arxiv.org/abs/2605.03180", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2411.16228", "kind": "paper", "label": "Soft information decoding with superconducting qubits", "url": "https://arxiv.org/abs/2411.16228", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:maurice-d-hanisch", "kind": "person", "label": "Maurice D. Hanisch", "url": "https://arxiv.org/abs/2411.16228", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:bence-het-nyi", "kind": "person", "label": "Bence Het\u00e9nyi", "url": "https://arxiv.org/abs/2411.16228", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:james-r-wootton", "kind": "person", "label": "James R. Wootton", "url": "https://arxiv.org/abs/2411.16228", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2311.12503", "kind": "paper", "label": "Testing the Accuracy of Surface Code Decoders", "url": "https://arxiv.org/abs/2311.12503", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2107.07505", "kind": "paper", "label": "Realization of real-time fault-tolerant quantum error correction", "url": "https://arxiv.org/abs/2107.07505", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:c-ryan-anderson", "kind": "person", "label": "C. Ryan-Anderson", "url": "https://arxiv.org/abs/2107.07505", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:j-g-bohnet", "kind": "person", "label": "J. G. Bohnet", "url": "https://arxiv.org/abs/2107.07505", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:k-lee", "kind": "person", "label": "K. Lee", "url": "https://arxiv.org/abs/2107.07505", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:d-gresh", "kind": "person", "label": "D. Gresh", "url": "https://arxiv.org/abs/2107.07505", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:a-hankin", "kind": "person", "label": "A. Hankin", "url": "https://arxiv.org/abs/2107.07505", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:j-p-gaebler", "kind": "person", "label": "J. P. Gaebler", "url": "https://arxiv.org/abs/2107.07505", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:d-francois", "kind": "person", "label": "D. Francois", "url": "https://arxiv.org/abs/2107.07505", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:a-chernoguzov", "kind": "person", "label": "A. Chernoguzov", "url": "https://arxiv.org/abs/2107.07505", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2604.21866", "kind": "paper", "label": "High-performance cellular automaton decoders for quantum repetition and toric code", "url": "https://arxiv.org/abs/2604.21866", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:don-winter", "kind": "person", "label": "Don Winter", "url": "https://arxiv.org/abs/2604.21866", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:thiago-l-m-guedes", "kind": "person", "label": "Thiago L. M. Guedes", "url": "https://arxiv.org/abs/2604.21866", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2407.11523", "kind": "paper", "label": "Improved Belief Propagation Decoding Algorithms for Surface Codes", "url": "https://arxiv.org/abs/2407.11523", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:jiahan-chen", "kind": "person", "label": "Jiahan Chen", "url": "https://arxiv.org/abs/2407.11523", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:zhipeng-liang", "kind": "person", "label": "Zhipeng Liang", "url": "https://arxiv.org/abs/2407.11523", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:xuan-wang", "kind": "person", "label": "Xuan Wang", "url": "https://arxiv.org/abs/2407.11523", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2506.08331", "kind": "paper", "label": "Correcting a noisy quantum computer using a quantum computer", "url": "https://arxiv.org/abs/2506.08331", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2504.11805", "kind": "paper", "label": "Network-Integrated Decoding System for Real-Time Quantum Error Correction with Lattice Surgery", "url": "https://arxiv.org/abs/2504.11805", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:namitha-liyanage", "kind": "person", "label": "Namitha Liyanage", "url": "https://arxiv.org/abs/2504.11805", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yue-wu", "kind": "person", "label": "Yue Wu", "url": "https://arxiv.org/abs/2504.11805", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:emmet-houghton", "kind": "person", "label": "Emmet Houghton", "url": "https://arxiv.org/abs/2504.11805", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:lin-zhong", "kind": "person", "label": "Lin Zhong", "url": "https://arxiv.org/abs/2504.11805", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2509.06756", "kind": "paper", "label": "Enhancing Fault-Tolerant Surface Code Decoding with Iterative Lattice Reweighting", "url": "https://arxiv.org/abs/2509.06756", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:yi-tian", "kind": "person", "label": "Yi Tian", "url": "https://arxiv.org/abs/2509.06756", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:y-zheng", "kind": "person", "label": "Y. Zheng", "url": "https://arxiv.org/abs/2509.06756", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:xiaoting-wang", "kind": "person", "label": "Xiaoting Wang", "url": "https://arxiv.org/abs/2509.06756", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:ching-yi-lai", "kind": "person", "label": "Ching-Yi Lai", "url": "https://arxiv.org/abs/2509.06756", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2508.15743", "kind": "paper", "label": "Colour Codes Reach Surface Code Performance using Vibe Decoding", "url": "https://arxiv.org/abs/2508.15743", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:tamas-noszko", "kind": "person", "label": "Tamas Noszko", "url": "https://arxiv.org/abs/2508.15743", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2305.15767", "kind": "paper", "label": "A Scalable, Fast and Programmable Neural Decoder for Fault-Tolerant Quantum Computation Using Surface Codes", "url": "https://arxiv.org/abs/2305.15767", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:mengyu-zhang", "kind": "person", "label": "Mengyu Zhang", "url": "https://arxiv.org/abs/2305.15767", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:xiangyu-ren", "kind": "person", "label": "Xiangyu Ren", "url": "https://arxiv.org/abs/2305.15767", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:guanglei-xi", "kind": "person", "label": "Guanglei Xi", "url": "https://arxiv.org/abs/2305.15767", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:zhenxing-zhang", "kind": "person", "label": "Zhenxing Zhang", "url": "https://arxiv.org/abs/2305.15767", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:qiaonian-yu", "kind": "person", "label": "Qiaonian Yu", "url": "https://arxiv.org/abs/2305.15767", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:fuming-liu", "kind": "person", "label": "Fuming Liu", "url": "https://arxiv.org/abs/2305.15767", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:hualiang-zhang", "kind": "person", "label": "Hualiang Zhang", "url": "https://arxiv.org/abs/2305.15767", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:shengyu-zhang", "kind": "person", "label": "Shengyu Zhang", "url": "https://arxiv.org/abs/2305.15767", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2403.01353", "kind": "paper", "label": "Spatially parallel decoding for multi-qubit lattice surgery", "url": "https://arxiv.org/abs/2403.01353", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:sophia-fuhui-lin", "kind": "person", "label": "Sophia Fuhui Lin", "url": "https://arxiv.org/abs/2403.01353", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:eric-c-peterson", "kind": "person", "label": "Eric C. Peterson", "url": "https://arxiv.org/abs/2403.01353", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:krishanu-sankar", "kind": "person", "label": "Krishanu Sankar", "url": "https://arxiv.org/abs/2403.01353", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:prasahnt-sivarajah", "kind": "person", "label": "Prasahnt Sivarajah", "url": "https://arxiv.org/abs/2403.01353", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2509.03954", "kind": "paper", "label": "LATTE: A Decoding Architecture for Quantum Computing with Temporal and Spatial Scalability", "url": "https://arxiv.org/abs/2509.03954", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:jubo-xu", "kind": "person", "label": "Jubo Xu", "url": "https://arxiv.org/abs/2509.03954", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2510.05795", "kind": "paper", "label": "Efficient Post-Selection for General Quantum LDPC Codes", "url": "https://arxiv.org/abs/2510.05795", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:seok-hyung-lee", "kind": "person", "label": "Seok-Hyung Lee", "url": "https://arxiv.org/abs/2510.05795", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:lucas-h-english", "kind": "person", "label": "Lucas H. English", "url": "https://arxiv.org/abs/2510.05795", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:stephen-d-bartlett", "kind": "person", "label": "Stephen D. Bartlett", "url": "https://arxiv.org/abs/2510.05795", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2410.03073", "kind": "paper", "label": "LEGO: QEC Decoding System Architecture for Dynamic Circuits", "url": "https://arxiv.org/abs/2410.03073", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2307.03280", "kind": "paper", "label": "Neural network decoder for near-term surface-code experiments", "url": "https://arxiv.org/abs/2307.03280", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:boris-m-varbanov", "kind": "person", "label": "Boris M. Varbanov", "url": "https://arxiv.org/abs/2307.03280", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:david-byfield", "kind": "person", "label": "David Byfield", "url": "https://arxiv.org/abs/2307.03280", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:barbara-m-terhal", "kind": "person", "label": "Barbara M. Terhal", "url": "https://arxiv.org/abs/2307.03280", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2402.04834", "kind": "paper", "label": "A blockBP decoder for the surface code", "url": "https://arxiv.org/abs/2402.04834", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:aviad-kaufmann", "kind": "person", "label": "Aviad Kaufmann", "url": "https://arxiv.org/abs/2402.04834", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:itai-arad", "kind": "person", "label": "Itai Arad", "url": "https://arxiv.org/abs/2402.04834", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2306.16476", "kind": "paper", "label": "Minimising surface-code failures using a color-code decoder", "url": "https://arxiv.org/abs/2306.16476", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:kaavya-sahay", "kind": "person", "label": "Kaavya Sahay", "url": "https://arxiv.org/abs/2306.16476", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:lingling-lao", "kind": "person", "label": "Lingling Lao", "url": "https://arxiv.org/abs/2306.16476", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:benjamin-j-brown", "kind": "person", "label": "Benjamin J. Brown", "url": "https://arxiv.org/abs/2306.16476", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2505.13599", "kind": "paper", "label": "Decoding across transversal Clifford gates in the surface code", "url": "https://arxiv.org/abs/2505.13599", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:mackenzie-h-shaw", "kind": "person", "label": "Mackenzie H. Shaw", "url": "https://arxiv.org/abs/2505.13599", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1901.10847", "kind": "paper", "label": "Decoding surface code with a distributed neural network based decoder", "url": "https://arxiv.org/abs/1901.10847", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:carmen-g-almudever", "kind": "person", "label": "Carmen G. Almudever", "url": "https://arxiv.org/abs/1901.10847", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2509.10164", "kind": "paper", "label": "A Symmetry-Integrated Approach to Surface Code Decoding", "url": "https://arxiv.org/abs/2509.10164", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:hoshitaro-ohnishi", "kind": "person", "label": "Hoshitaro Ohnishi", "url": "https://arxiv.org/abs/2509.10164", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2110.05854", "kind": "paper", "label": "A scalable and fast artificial neural network syndrome decoder for surface codes", "url": "https://arxiv.org/abs/2110.05854", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:1801.01879", "kind": "paper", "label": "Linear-time general decoding algorithm for the surface code", "url": "https://arxiv.org/abs/1801.01879", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:andrew-s-darmawan", "kind": "person", "label": "Andrew S. Darmawan", "url": "https://arxiv.org/abs/1801.01879", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:david-poulin", "kind": "person", "label": "David Poulin", "url": "https://arxiv.org/abs/1801.01879", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1411.3028", "kind": "paper", "label": "A fast fault-tolerant decoder for qubit and qudit surface codes", "url": "https://arxiv.org/abs/1411.3028", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:fern-h-e-watson", "kind": "person", "label": "Fern H. E. Watson", "url": "https://arxiv.org/abs/1411.3028", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:hussain-anwar", "kind": "person", "label": "Hussain Anwar", "url": "https://arxiv.org/abs/1411.3028", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2510.11593", "kind": "paper", "label": "Qubit-centric Transformer for Surface Code Decoding", "url": "https://arxiv.org/abs/2510.11593", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:seong-joon-park", "kind": "person", "label": "Seong-Joon Park", "url": "https://arxiv.org/abs/2510.11593", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:hee-youl-kwak", "kind": "person", "label": "Hee-Youl Kwak", "url": "https://arxiv.org/abs/2510.11593", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yongjune-kim", "kind": "person", "label": "Yongjune Kim", "url": "https://arxiv.org/abs/2510.11593", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2209.09219", "kind": "paper", "label": "Scalable surface code decoders with parallelization in time", "url": "https://arxiv.org/abs/2209.09219", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:xinyu-tan", "kind": "person", "label": "Xinyu Tan", "url": "https://arxiv.org/abs/2209.09219", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:rui-chao", "kind": "person", "label": "Rui Chao", "url": "https://arxiv.org/abs/2209.09219", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yaoyun-shi", "kind": "person", "label": "Yaoyun Shi", "url": "https://arxiv.org/abs/2209.09219", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2403.08706", "kind": "paper", "label": "Optimal adaptation of surface-code decoders to local noise", "url": "https://arxiv.org/abs/2403.08706", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2203.04948", "kind": "paper", "label": "Improved decoding of circuit noise and fragile boundaries of tailored surface codes", "url": "https://arxiv.org/abs/2203.04948", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:oscar-higgott", "kind": "person", "label": "Oscar Higgott", "url": "https://arxiv.org/abs/2203.04948", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:thomas-c-bohdanowicz", "kind": "person", "label": "Thomas C. Bohdanowicz", "url": "https://arxiv.org/abs/2203.04948", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:aleksander-kubica", "kind": "person", "label": "Aleksander Kubica", "url": "https://arxiv.org/abs/2203.04948", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:steven-t-flammia", "kind": "person", "label": "Steven T. Flammia", "url": "https://arxiv.org/abs/2203.04948", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2405.07433", "kind": "paper", "label": "Efficient soft-output decoders for the surface code", "url": "https://arxiv.org/abs/2405.07433", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:nadine-meister", "kind": "person", "label": "Nadine Meister", "url": "https://arxiv.org/abs/2405.07433", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:john-preskill", "kind": "person", "label": "John Preskill", "url": "https://arxiv.org/abs/2405.07433", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2504.13043", "kind": "paper", "label": "Machine Learning Decoding of Circuit-Level Noise for Bivariate Bicycle Codes", "url": "https://arxiv.org/abs/2504.13043", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:john-blue", "kind": "person", "label": "John Blue", "url": "https://arxiv.org/abs/2504.13043", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:harshil-avlani", "kind": "person", "label": "Harshil Avlani", "url": "https://arxiv.org/abs/2504.13043", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:zhiyang-he", "kind": "person", "label": "Zhiyang He", "url": "https://arxiv.org/abs/2504.13043", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:liu-ziyin", "kind": "person", "label": "Liu Ziyin", "url": "https://arxiv.org/abs/2504.13043", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:isaac-l-chuang", "kind": "person", "label": "Isaac L. Chuang", "url": "https://arxiv.org/abs/2504.13043", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2212.11632", "kind": "paper", "label": "Performance enhancement of surface codes via recursive MWPM decoding", "url": "https://arxiv.org/abs/2212.11632", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:patricio-fuentes", "kind": "person", "label": "Patricio Fuentes", "url": "https://arxiv.org/abs/2212.11632", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:pedro-m-crespo", "kind": "person", "label": "Pedro M. Crespo", "url": "https://arxiv.org/abs/2212.11632", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2411.05785", "kind": "paper", "label": "Phases of decodability in the surface code with unitary errors", "url": "https://arxiv.org/abs/2411.05785", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:yimu-bao", "kind": "person", "label": "Yimu Bao", "url": "https://arxiv.org/abs/2411.05785", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:sajant-anand", "kind": "person", "label": "Sajant Anand", "url": "https://arxiv.org/abs/2411.05785", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2310.05900", "kind": "paper", "label": "Learning to Decode the Surface Code with a Recurrent, Transformer-Based Neural Network", "url": "https://arxiv.org/abs/2310.05900", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:johannes-bausch", "kind": "person", "label": "Johannes Bausch", "url": "https://arxiv.org/abs/2310.05900", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:andrew-w-senior", "kind": "person", "label": "Andrew W Senior", "url": "https://arxiv.org/abs/2310.05900", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:francisco-j-h-heras", "kind": "person", "label": "Francisco J H Heras", "url": "https://arxiv.org/abs/2310.05900", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:thomas-edlich", "kind": "person", "label": "Thomas Edlich", "url": "https://arxiv.org/abs/2310.05900", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:alex-davies", "kind": "person", "label": "Alex Davies", "url": "https://arxiv.org/abs/2310.05900", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:michael-newman", "kind": "person", "label": "Michael Newman", "url": "https://arxiv.org/abs/2310.05900", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:kevin-satzinger", "kind": "person", "label": "Kevin Satzinger", "url": "https://arxiv.org/abs/2310.05900", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2411.18090", "kind": "paper", "label": "High-Level Surface Code Decoding via Parallel FFNNs on CIM Platforms", "url": "https://arxiv.org/abs/2411.18090", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:erjia-xiao", "kind": "person", "label": "Erjia Xiao", "url": "https://arxiv.org/abs/2411.18090", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:wenbo-mu", "kind": "person", "label": "Wenbo Mu", "url": "https://arxiv.org/abs/2411.18090", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:songhuan-he", "kind": "person", "label": "Songhuan He", "url": "https://arxiv.org/abs/2411.18090", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:zhongyi-ni", "kind": "person", "label": "Zhongyi Ni", "url": "https://arxiv.org/abs/2411.18090", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:lingfeng-zhang", "kind": "person", "label": "Lingfeng Zhang", "url": "https://arxiv.org/abs/2411.18090", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:xiaokun-zhan", "kind": "person", "label": "Xiaokun Zhan", "url": "https://arxiv.org/abs/2411.18090", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:yifei-cui", "kind": "person", "label": "Yifei Cui", "url": "https://arxiv.org/abs/2411.18090", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:1405.4883", "kind": "paper", "label": "Efficient Algorithms for Maximum Likelihood Decoding in the Surface Code", "url": "https://arxiv.org/abs/1405.4883", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:sergey-bravyi", "kind": "person", "label": "Sergey Bravyi", "url": "https://arxiv.org/abs/1405.4883", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:martin-suchara", "kind": "person", "label": "Martin Suchara", "url": "https://arxiv.org/abs/1405.4883", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:alexander-vargo", "kind": "person", "label": "Alexander Vargo", "url": "https://arxiv.org/abs/1405.4883", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2110.10896", "kind": "paper", "label": "Efficient Decoding of Surface Code Syndromes for Error Correction in Quantum Computing", "url": "https://arxiv.org/abs/2110.10896", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:debasmita-bhoumik", "kind": "person", "label": "Debasmita Bhoumik", "url": "https://arxiv.org/abs/2110.10896", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:pinaki-sen", "kind": "person", "label": "Pinaki Sen", "url": "https://arxiv.org/abs/2110.10896", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:ritajit-majumdar", "kind": "person", "label": "Ritajit Majumdar", "url": "https://arxiv.org/abs/2110.10896", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:susmita-sur-kolay", "kind": "person", "label": "Susmita Sur-Kolay", "url": "https://arxiv.org/abs/2110.10896", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:latesh-kumar-k-j", "kind": "person", "label": "Latesh Kumar K J", "url": "https://arxiv.org/abs/2110.10896", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:sundaraja-sitharama-iyengar", "kind": "person", "label": "Sundaraja Sitharama Iyengar", "url": "https://arxiv.org/abs/2110.10896", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2309.10331", "kind": "paper", "label": "Hardness results for decoding the surface code with Pauli noise", "url": "https://arxiv.org/abs/2309.10331", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:alex-fischer", "kind": "person", "label": "Alex Fischer", "url": "https://arxiv.org/abs/2309.10331", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:akimasa-miyake", "kind": "person", "label": "Akimasa Miyake", "url": "https://arxiv.org/abs/2309.10331", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2405.01151", "kind": "paper", "label": "Spanning Tree Matching Decoder for Quantum Surface Codes", "url": "https://arxiv.org/abs/2405.01151", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:1812.08186", "kind": "paper", "label": "Tailoring surface codes for highly biased noise", "url": "https://arxiv.org/abs/1812.08186", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:david-k-tuckett", "kind": "person", "label": "David K. Tuckett", "url": "https://arxiv.org/abs/1812.08186", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:christopher-t-chubb", "kind": "person", "label": "Christopher T. Chubb", "url": "https://arxiv.org/abs/1812.08186", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2512.14255", "kind": "paper", "label": "Information-efficient decoding of surface codes", "url": "https://arxiv.org/abs/2512.14255", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:long-d-h-my", "kind": "person", "label": "Long D. H. My", "url": "https://arxiv.org/abs/2512.14255", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:shao-hen-chiew", "kind": "person", "label": "Shao-Hen Chiew", "url": "https://arxiv.org/abs/2512.14255", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:jing-hao-chai", "kind": "person", "label": "Jing Hao Chai", "url": "https://arxiv.org/abs/2512.14255", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:person:hui-khoon-ng", "kind": "person", "label": "Hui Khoon Ng", "url": "https://arxiv.org/abs/2512.14255", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2408.12135", "kind": "paper", "label": "Improved accuracy for decoding surface codes with matching synthesis", "url": "https://arxiv.org/abs/2408.12135", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2512.08914", "kind": "paper", "label": "SAQ: Stabilizer-Aware Quantum Error Correction Decoder", "url": "https://arxiv.org/abs/2512.08914", "source": "arxiv", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:person:david-zenati", "kind": "person", "label": "David Zenati", "url": "https://arxiv.org/abs/2512.08914", "source": "arxiv-author", "axis": "qec", "layer": 0}
{"type": "node", "id": "p2:paper:2303.17580", "kind": "paper", "label": "HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face", "url": "https://arxiv.org/abs/2303.17580", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2308.00352", "kind": "paper", "label": "MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework", "url": "https://arxiv.org/abs/2308.00352", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2304.03442", "kind": "paper", "label": "Generative Agents: Interactive Simulacra of Human Behavior", "url": "https://arxiv.org/abs/2304.03442", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2305.16291", "kind": "paper", "label": "Voyager: An Open-Ended Embodied Agent with Large Language Models", "url": "https://arxiv.org/abs/2305.16291", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2308.09687", "kind": "paper", "label": "Graph of Thoughts: Solving Elaborate Problems with Large Language Models", "url": "https://arxiv.org/abs/2308.09687", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2305.10601", "kind": "paper", "label": "Tree of Thoughts: Deliberate Problem Solving with Large Language Models", "url": "https://arxiv.org/abs/2305.10601", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2311.12983", "kind": "paper", "label": "GAIA: a benchmark for General AI Assistants", "url": "https://arxiv.org/abs/2311.12983", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2308.03688", "kind": "paper", "label": "AgentBench: Evaluating LLMs as Agents", "url": "https://arxiv.org/abs/2308.03688", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2302.04761", "kind": "paper", "label": "Toolformer: Language Models Can Teach Themselves to Use Tools", "url": "https://arxiv.org/abs/2302.04761", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2303.11366", "kind": "paper", "label": "Reflexion: Language Agents with Verbal Reinforcement Learning", "url": "https://arxiv.org/abs/2303.11366", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2304.05128", "kind": "paper", "label": "Self-Refine: Iterative Refinement with Self-Feedback", "url": "https://arxiv.org/abs/2304.05128", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2310.08560", "kind": "paper", "label": "MemGPT: Towards LLMs as Operating Systems", "url": "https://arxiv.org/abs/2310.08560", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2405.10467", "kind": "paper", "label": "Beyond static AI evaluations (agentic) / A-Mem agentic memory", "url": "https://arxiv.org/abs/2405.10467", "source": "arxiv-anchor", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:paper:2104.10350", "kind": "paper", "label": "Carbon Emissions and Large Neural Network Training", "url": "https://arxiv.org/abs/2104.10350", "source": "arxiv-anchor", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:paper:2306.16863", "kind": "paper", "label": "Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training", "url": "https://arxiv.org/abs/2306.16863", "source": "arxiv-anchor", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:paper:2311.03378", "kind": "paper", "label": "Power Hungry Processing: Watts Driving the Cost of AI Deployment?", "url": "https://arxiv.org/abs/2311.03378", "source": "arxiv-anchor", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:paper:1802.06441", "kind": "paper", "label": "Deep Neural Network Probabilistic Decoder for Stabilizer Codes", "url": "https://arxiv.org/abs/1802.06441", "source": "arxiv-anchor", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:1811.07835", "kind": "paper", "label": "Reinforcement Learning Decoders for Fault-Tolerant Quantum Computation", "url": "https://arxiv.org/abs/1811.07835", "source": "arxiv-anchor", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2310.05867", "kind": "paper", "label": "Learning high-accuracy error decoding for quantum processors (AlphaQubit)", "url": "https://arxiv.org/abs/2310.05867", "source": "arxiv-anchor", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2101.08946", "kind": "paper", "label": "PyMatching: A Python package for decoding quantum codes with MWPM", "url": "https://arxiv.org/abs/2101.08946", "source": "arxiv-anchor", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2103.02202", "kind": "paper", "label": "Stim: a fast stabilizer circuit simulator", "url": "https://arxiv.org/abs/2103.02202", "source": "arxiv-anchor", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:2001.11427", "kind": "paper", "label": "Neural network decoders for quantum error correcting codes", "url": "https://arxiv.org/abs/2001.11427", "source": "arxiv-anchor", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:1705.09334", "kind": "paper", "label": "Neural Decoder for Topological Codes", "url": "https://arxiv.org/abs/1705.09334", "source": "arxiv-anchor", "axis": "qec", "layer": 0, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:paper:1903.11027", "kind": "paper", "label": "nuScenes: A multimodal dataset for autonomous driving", "url": "https://arxiv.org/abs/1903.11027", "source": "arxiv-anchor", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:1901.03642", "kind": "paper", "label": "The KITTI Vision Benchmark / sensor fusion", "url": "https://arxiv.org/abs/1901.03642", "source": "arxiv-anchor", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:1912.04838", "kind": "paper", "label": "Scalability in Perception for Autonomous Driving: Waymo Open Dataset", "url": "https://arxiv.org/abs/1912.04838", "source": "arxiv-anchor", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:1901.08248", "kind": "paper", "label": "VINS-Fusion / robust visual-inertial state estimation", "url": "https://arxiv.org/abs/1901.08248", "source": "arxiv-anchor", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:paper:2411.13676", "kind": "paper", "label": "Hymba: A Hybrid-head Architecture for Small Language Models", "url": "https://arxiv.org/abs/2411.13676", "source": "arxiv-anchor", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:paper:2406.07887", "kind": "paper", "label": "Samba: Simple Hybrid State Space Models for Efficient Unlimited Context", "url": "https://arxiv.org/abs/2406.07887", "source": "arxiv-anchor", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:paper:2405.16712", "kind": "paper", "label": "Zamba: A Compact 7B SSM Hybrid Model", "url": "https://arxiv.org/abs/2405.16712", "source": "arxiv-anchor", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:person:harrison_chase", "kind": "person", "label": "Harrison Chase", "url": "https://github.com/hwchase17", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:person:chi_wang", "kind": "person", "label": "Chi Wang", "url": "https://www.microsoft.com/en-us/research/people/chiw/", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:person:omar_khattab", "kind": "person", "label": "Omar Khattab", "url": "https://omarkhattab.com", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:person:shunyu_yao", "kind": "person", "label": "Shunyu Yao (ReAct)", "url": "https://ysymyth.github.io", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:person:joon_sung_park", "kind": "person", "label": "Joon Sung Park (Generative Agents)", "url": "https://hai.stanford.edu/people/joon-sung-park", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:person:carlos_guestrin", "kind": "person", "label": "Carlos Guestrin (DSPy)", "url": "https://guestrin.su.domains", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:person:charles_packer", "kind": "person", "label": "Charles Packer (MemGPT/Letta)", "url": "https://github.com/cpacker", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:person:sasha_luccioni", "kind": "person", "label": "Sasha Luccioni", "url": "https://www.sashaluccioni.com", "source": "curated", "axis": "energy", "layer": 2}
{"type": "node", "id": "p2:person:emma_strubell", "kind": "person", "label": "Emma Strubell", "url": "https://strubell.github.io", "source": "curated", "axis": "energy", "layer": 2}
{"type": "node", "id": "p2:person:roy_schwartz", "kind": "person", "label": "Roy Schwartz (Green AI)", "url": "https://schwartz-lab-huji.github.io", "source": "curated", "axis": "energy", "layer": 2}
{"type": "node", "id": "p2:person:mosharaf_chowdhury", "kind": "person", "label": "Mosharaf Chowdhury (Zeus/ml-energy)", "url": "https://www.mosharaf.com", "source": "curated", "axis": "energy", "layer": 2}
{"type": "node", "id": "p2:person:lasse_wolff_anthony", "kind": "person", "label": "Lasse F. Wolff Anthony (Carbontracker)", "url": "https://github.com/lfwa", "source": "curated", "axis": "energy", "layer": 2}
{"type": "node", "id": "p2:person:oscar_higgott", "kind": "person", "label": "Oscar Higgott (PyMatching)", "url": "https://github.com/oscarhiggott", "source": "curated", "axis": "qec", "layer": 2}
{"type": "node", "id": "p2:person:craig_gidney", "kind": "person", "label": "Craig Gidney (Stim)", "url": "https://algassert.com", "source": "curated", "axis": "qec", "layer": 2}
{"type": "node", "id": "p2:person:johannes_bausch", "kind": "person", "label": "Johannes Bausch (AlphaQubit)", "url": "https://scholar.google.com/citations?user=johannes-bausch", "source": "curated", "axis": "qec", "layer": 2}
{"type": "node", "id": "p2:person:david_poulin", "kind": "person", "label": "David Poulin (neural decoders)", "url": "https://arxiv.org/a/poulin_d_1", "source": "curated", "axis": "qec", "layer": 2}
{"type": "node", "id": "p2:person:song_han", "kind": "person", "label": "Song Han (BEVFusion/MIT HAN Lab)", "url": "https://hanlab.mit.edu", "source": "curated", "axis": "fusion", "layer": 2}
{"type": "node", "id": "p2:person:zhijian_liu", "kind": "person", "label": "Zhijian Liu (BEVFusion)", "url": "https://zhijianliu.com", "source": "curated", "axis": "fusion", "layer": 2}
{"type": "node", "id": "p2:person:tri_dao_p2", "kind": "person", "label": "Tri Dao (FlashAttention/Mamba)", "url": "https://tridao.me", "source": "curated", "axis": "attention", "layer": 2}
{"type": "node", "id": "p2:person:albert_gu", "kind": "person", "label": "Albert Gu (Mamba/SSM)", "url": "https://goombalab.github.io", "source": "curated", "axis": "attention", "layer": 2}
{"type": "node", "id": "p2:person:soham_de", "kind": "person", "label": "Soham De (Griffin)", "url": "https://www.sohamde.com", "source": "curated", "axis": "attention", "layer": 2}
{"type": "node", "id": "p2:person:opher_lieber", "kind": "person", "label": "Opher Lieber (Jamba/AI21)", "url": "https://www.ai21.com", "source": "curated", "axis": "attention", "layer": 2}
{"type": "node", "id": "p2:org:langchain_org", "kind": "org", "label": "LangChain", "url": "https://www.langchain.com", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:org:crewai_org", "kind": "org", "label": "CrewAI", "url": "https://www.crewai.com", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:org:ai21_labs", "kind": "org", "label": "AI21 Labs", "url": "https://www.ai21.com", "source": "curated", "axis": "attention", "layer": 2, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:org:letta_org", "kind": "org", "label": "Letta (MemGPT)", "url": "https://www.letta.com", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:org:stanford_nlp_dspy", "kind": "org", "label": "Stanford NLP (DSPy)", "url": "https://nlp.stanford.edu", "source": "curated", "axis": "agents", "layer": 2}
{"type": "node", "id": "p2:org:ml_energy_org", "kind": "org", "label": "ML.ENERGY Initiative (SymbioticLab, Michigan)", "url": "https://ml.energy", "source": "curated", "axis": "energy", "layer": 2, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:org:codecarbon_org", "kind": "org", "label": "CodeCarbon", "url": "https://codecarbon.io", "source": "curated", "axis": "energy", "layer": 2, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:org:green_software_foundation", "kind": "org", "label": "Green Software Foundation", "url": "https://greensoftware.foundation", "source": "curated", "axis": "energy", "layer": 2, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:org:mlcommons_power", "kind": "org", "label": "MLCommons Power Working Group", "url": "https://mlcommons.org/working-groups/benchmarks/power/", "source": "curated", "axis": "energy", "layer": 2, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:org:google_quantum_ai", "kind": "org", "label": "Google Quantum AI", "url": "https://quantumai.google", "source": "curated", "axis": "qec", "layer": 2, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:org:riverlane", "kind": "org", "label": "Riverlane", "url": "https://www.riverlane.com", "source": "curated", "axis": "qec", "layer": 2, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:org:aws_braket_qec", "kind": "org", "label": "AWS Center for Quantum Computing", "url": "https://aws.amazon.com/braket/", "source": "curated", "axis": "qec", "layer": 2, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:org:errorcorrectionzoo", "kind": "org", "label": "The Error Correction Zoo", "url": "https://errorcorrectionzoo.org", "source": "curated", "axis": "qec", "layer": 2, "maps_to_surface": "qhall"}
{"type": "node", "id": "p2:org:mit_han_lab", "kind": "org", "label": "MIT HAN Lab", "url": "https://hanlab.mit.edu", "source": "curated", "axis": "fusion", "layer": 2}
{"type": "node", "id": "p2:org:dao_ailab", "kind": "org", "label": "Dao AI Lab (Princeton)", "url": "https://github.com/Dao-AILab", "source": "curated", "axis": "attention", "layer": 2, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:org:goomba_lab", "kind": "org", "label": "Goomba Lab (CMU, Albert Gu)", "url": "https://goombalab.github.io", "source": "curated", "axis": "attention", "layer": 2, "maps_to_surface": "ringattn"}
{"type": "node", "id": "p2:benchmark:swe_bench_ds", "kind": "benchmark", "label": "SWE-bench dataset", "url": "https://www.swebench.com", "source": "curated", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:benchmark:gaia_ds", "kind": "benchmark", "label": "GAIA benchmark (HF)", "url": "https://huggingface.co/datasets/gaia-benchmark/GAIA", "source": "curated", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:benchmark:agentbench_ds", "kind": "benchmark", "label": "AgentBench", "url": "https://github.com/THUDM/AgentBench", "source": "curated", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:benchmark:webarena_ds", "kind": "benchmark", "label": "WebArena", "url": "https://webarena.dev", "source": "curated", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:benchmark:toolbench_ds", "kind": "benchmark", "label": "ToolBench", "url": "https://github.com/OpenBMB/ToolBench", "source": "curated", "axis": "agents", "layer": 0}
{"type": "node", "id": "p2:benchmark:ml_energy_leaderboard", "kind": "benchmark", "label": "ML.ENERGY Leaderboard", "url": "https://ml.energy/leaderboard", "source": "curated", "axis": "energy", "layer": 0, "maps_to_surface": "energy"}
{"type": "node", "id": "p2:dataset:nuscenes_ds", "kind": "dataset", "label": "nuScenes", "url": "https://www.nuscenes.org", "source": "curated", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:dataset:waymo_open_ds", "kind": "dataset", "label": "Waymo Open Dataset", "url": "https://waymo.com/open/", "source": "curated", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:dataset:kitti_ds", "kind": "dataset", "label": "KITTI Vision Benchmark", "url": "https://www.cvlibs.net/datasets/kitti/", "source": "curated", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:dataset:anti_uav_ds", "kind": "dataset", "label": "Anti-UAV benchmark", "url": "https://anti-uav.github.io", "source": "curated", "axis": "defense", "layer": 0}
{"type": "node", "id": "p2:dataset:nuscenes_radar", "kind": "dataset", "label": "nuScenes radar (RadarScenes-adjacent)", "url": "https://radar-scenes.com", "source": "curated", "axis": "fusion", "layer": 0}
{"type": "node", "id": "p2:benchmark:longbench_p2", "kind": "benchmark", "label": "LongBench (hybrid long-context eval)", "url": "https://github.com/THUDM/LongBench", "source": "curated", "axis": "attention", "layer": 0, "maps_to_surface": "ringattn"}
{"type": "edge", "src": "p2:axis:energy", "dst": "surface:energy", "rel": "maps-to-surface"}
{"type": "edge", "src": "p2:axis:qec", "dst": "surface:qhall", "rel": "maps-to-surface"}
{"type": "edge", "src": "p2:axis:attention", "dst": "surface:ringattn", "rel": "maps-to-surface"}
{"type": "edge", "src": "p2:repo:langgenius--dify", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:labring--fastgpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:builderz-labs--mission-control", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iflytek--astron-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:deepset-ai--haystack", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jnmetacode--agency-agents-zh", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:weibocom--rill-flow", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bytechefhq--bytechef", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:graniet--llm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:liweiphys--layra", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lofcz--llmtornado", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:thibautmelen--agentic-ai-systems", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rocketride-org--rocketride-server", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:imfeh2--flowent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pipelex--pipelex", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dataelement--bisheng", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zhnt--loushang", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:agenticgokit--agenticgokit", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xorbitsai--xagent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:linora-u--agentloom", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:i365dev--llm_agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:swarmauri--swarmauri-sdk", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:alexli18--binex", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yx-fan--multi-agent-orchestration-framework", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:azure--intelligent-app-workshop", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xeloxa--temodar-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hereandnowai--master-langgraph-workflows-in-python-20-real-world-agent-projects-by-hereandnow-ai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lostbean--jido_composer", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ces-ltd--titanx", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:redhat-community-ai-tools--unifai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pipelex--pipelex-cookbook", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:juglans-ai--juglans", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:llm-use--llm-use", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fzn0x--watchtower", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pinkpixel-dev--mindbridge-mcp", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kaivyy--kabot", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aksingh-0704--team_agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:anurmatov--phleet", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:projectliminality--interbrain", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:reworkd--agentgpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:e2b-dev--awesome-ai-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:elricliu--autogpt-next-web", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:idosal--agentllm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:scarletpan--awesome-autonomous-gpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jbesomi--awesome-autonomous-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:intelligenzaartificiale--free-auto-gpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:alexk1919--mackgpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:curated-awesome-lists--awesome-auto-gpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:edmar--whenx", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iskandarreza--ai-worker-js", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fredsiika--gpt-vector-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:0xmerl99--agent-world-protocol", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:web007-spec--autogpt-next-web", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iskandarreza--loopgpt-next", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:naveen123bh--autogpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:javierlozo--langchain-autogpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:spyderrex--squadai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bchip--chippt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bobmhong--autogpt-work", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ksen27--deploy-autonomous-ai-agents-in-your-browser.-autogpt-", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ratnakar1009--autonomous-ai-task-agent-autogpt-crewai-style-", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:api-evangelist--autogpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:d68864767--autogpt-master-edition-fully-autonomous-desktop-agent-for-google-chrome", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sunny-raj-sah--replit-agent-v1-a-mini-autonomous-ai-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dick2450121353-dot--autonomous-problem-solving", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aiblogfirst--autonomous-ai-comparison", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chhunt17--autonomous-ai-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adithi-md--autogpt-ollama-qwen", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:udayteja21--autogpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aiwaves-cn--agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:agentuniverse-ai--agentuniverse", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:transformeroptimus--superagi", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aielte-research--hacksynth", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aaronjmars--aeon", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:wanshuiyin--auto-claude-code-research-in-sleep", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:undertone0809--promptulate", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mervinpraison--praisonai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jatingargiitk--saas-builder", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:swarmclawai--swarmclaw", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jwentong--wirelessagent_r1", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cordum-io--cordum", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aviralgarg05--agentunit", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sagentic-ai--sagentic-af", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:libraryofcelsus--aetherius_ai_assistant", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:alfredolopez80--multi-agent-ralph-loop", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:openlegion-ai--openlegion", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ashutosh0x--arc-cli", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chaosync-org--awesome-ai-agent-testing", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xybruceliu--thoughtful-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gustavoeenriquez--makerai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:inquisimind--digital-life", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:opencsgs--coagent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ericwang915--pythonclaw", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:beidald--liliumai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gwenlake--gwenflow", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kalaspuff--ai-assisted-task-executor", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:h4ckologic--bughunter-ai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:francescostabile--omnigent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lixin97--agora-lab", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nirholas--three.ws", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ktol1--redteam-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sarthak1095--redefining-qa-multi-agent-ai-automation-using-mcp-protocol", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tenchineko--standalone-orchestrator", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:envisionmindca--os-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:simonstaton--agentmanager", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ai-agentswarm--agentswarm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:micro-novelty--integratedpipeline-specialized-non-llm-ai-agent-framework", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fu351--doberman-core", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kyegomez--awesome-multi-agent-papers", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aianytime--multi-agents-system-from-scratch", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:owshq-mec--ws-3-crew-ai-multi-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:benitomartin--crewai-rag-langchain-qdrant", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mesutdmn--autonomous-multi-agent-systems-with-crewai-essay-writer", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nisaaragharia--ai-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jiaxuanliu-arsko--vaspilot", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gurpreetkaurjethra--ai-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:abdulbasit110--blog-writer-multi-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:oneduckyboy--awesome-ai-agents-hub-for-crewai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:byrencheema--job-search-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aws-samples--sample-multi-agent-builder-bedrock-crewai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:the-swarm-corporation--multi-agent-template-app", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dataforscience--crewai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kbhujbal--multi-agent-ai-travel-advisor", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:botextractai--ai-crewai-multi-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bhargobdeka--multi-agent-apps", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:numb94--crewai-astock", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adongwanai--agentguide", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:techindicium--multiagent-crewai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:the-swarm-corporation--multi-agent-rag-template", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:luandev--comfyui-crewai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aws-samples--sample-compliance-assistant-with-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rn0311--crewaisecurityagent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hanantabak2--crewai_ai_business_consultant_on_streamlit", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aisquare-studio--aisquare-studio-qa", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:felixggj--multi-agent-ai-newsletter", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nomannayeem--langchain_crewai_gemini-ai_agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nousresearch--hermes-agent-self-evolution", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:karthikscale3--dspyground", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:davidberenstein1957--dspydantic", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:omidzamani--dspy-skills", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:laxminarayen--dspy-prompt-optimizer", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mahir-isikli--ai-tinkerers-dspy-talk", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mozilla-ai--visual-dspy", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kazkozdev--dspy-optimization-patterns", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nielsgl--dspy-optimizer", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:heathbrew--qdrant-dspy-colbertv2", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:immu4989--dspy-security-bench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:emirhan-gazi--kaizen", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:juyangbai--mas-promptbench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yotambraun--flowprompt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aijnek--dspy_multimodal", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:asirwad--dspy-prompt-auto-optimizer", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:saibhaskerraju--dspy-optimization", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jordan-barrett-jm--llm-page-extraction-gepa-dspy", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tosinamuda--llama-finetuning-dspy", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ai-maker-space--dspyevent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:salaivishnu123--adaptive-rag-secure-assistant", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:curiositech--prompt-learning-mcp", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nivlewd1--prompt-optimizer", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:armanhm--dspy-prompt-optimization-simulator", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:longntl-namitech--promptoptimization_mlflow-dspy", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hersh-gupta--safety-prompt-optimization", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nafew-azim--dspy-frameworks-mipro-better-together-", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ridhima-jain--dspy-prompt-optimization", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aymeric-roucher--gaia", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gaia-agent--gaia-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chiarapaglioni--gaia-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kvpratama--gaia-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sassarini-marco--gaia-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:e-alizadeh--gaia-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:stanford-ppl--agentic_benchmarking_for_gaia", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fisherman611--gaia-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jungwoonshin--agent-benchmark", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sunjilgahatraj1--autonomous-ai-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sagar-garg--ai-agent-huggingface-project", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:brauliopf--agent-gaia-benchmark", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jomonsugi--gaia-benchmark-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:abdulmunimjemal--gaia-benchmark", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:daksh-chaudhary99--agent_gaia_benchmark", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:andrea-acampora--gaia-benchmark-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:saidkaban--gaia-benchmark-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jaimemontea--agent_gaia_benchmark", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rcarioni--gaia-benchmark-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iamvibhav--gaia-benchmark-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nicholasgoh--fastapi-mcp-langgraph-template", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sonnysangha--ai-agent-langchain-langgraph-convex-clerk-ibm-wxtools-nextjs15", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:foreveryh--mentis", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fareedkhan-dev--scalable-rag-pipeline", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fancy1108--clutch", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:laxmimerit--agentic-rag-with-langgraph-and-ollama", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bernatsampera--event-deep-research", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:realyinchen--agenthub", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aws-solutions-library-samples--guidance-for-multi-agent-orchestration-langgraph-on-aws", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sinanuozdemir--advanced-agentic-ai-in-three-weeks", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bobmatnyc--claude-multiagent-pm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:langtail--ai-orchestra", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:samirpatil2000--agentic-template", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ani-in--multi-agent-customer-support", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:harimxchoi--langgraph-travel-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jonathanscholtes--azure-ai-foundry-agentic-workshop", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:himanshumohanty-git24--rakshaquant", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:extrawest--fastapi-langgraph-chatbot-with-vector-store-memory-mcp-tools-and-voice-mode", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nvidia-ai-blueprints--retail-shopping-assistant", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:azurecosmosdb--multi-agent-langgraph", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yaalalabs--agent-kernel", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:prsaurabh--agentic-rag-orchestrated", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:youhonda30--agent-skill-bus", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:martymcenroe--assemblyzero", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bjornmelin--dev-pro-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tencentcloud--tencentdb-agent-memory", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:memvid--memvid", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:teleai-uagi--awesome-agent-memory", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lycheemem--lycheemem", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:farzad-r--agentic-longterm-memory", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:matrixorigin--memoria", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dataojitori--nocturne_memory", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:akirusprod--llm-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:timan-group--plugmem", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:edeai--openflux", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xortexai--xmem", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:uukuguy--speechless", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:morettt--my-neuro", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mig-nju--personavlm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iaar-shanghai--awesome-ai-memory", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:teleai-uagi--telemem", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:wuwangzhang1216--opendb", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ob-labs--memory-powermem", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sibyl-labs--sibyl-memory", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:memtomem--memtomem", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jo-inc--pi-mem", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gizclaw--flowcraft", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:goodai--goodai-ltm-benchmark", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:k-kolomeitsev--data-structure-protocol", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:markmbain--aius", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:russellcanfield--wingman-ai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pinkpixel-dev--mem0-mcp", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:letta-ai--learning-sdk", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tostechbr--memoryclaw", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sqliteai--adam", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:achetronic--magec", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:visendi-labs--uffe", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mine-ustc--atommem", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:0verl1nk--papersage", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mmx920--ebbingflow", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sompote--tiger_bot", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yunghuihsu--long-term-agentic-memory-with-langgraph", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mhndayesh--easy-agentic-memory-system-easy-memory-", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ksm26--llms-as-operating-systems-agent-memory", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:foundationagents--metagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lynnooo--multi-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cerqwq--multi-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:htoyll8--metagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mishuni--metagpt_bkd", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ravindrakush11--metagpt_multi-agent-framework", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:edgemoorlf--metagptagents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rizusaki--ai-multi-agent-metagpt-guide", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:0325kai-huang--metagpt_write_story_multi-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mormerneed--multi-agent-policy-discussion", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lynx-1221--centadmetagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:k-rks--metagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sai-prannav--metagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:smiroofingcompany--metagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:khoabd--metagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:void-kusho--metagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gridgentoo--metagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:serkac1000--metagpt-1", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:violettance--metagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:daniel-flynn-github--multi-agent-collaboration-for-ffe-in-the-metagpt-framework", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jjj54788--multi-agent-debate", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vincentwei1021--awesome-ai-agent-frameworks", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:arvind-sundararajan--metagpt-sd-optimizer", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:neverpanick--lv_metagpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:open-sourcery-umd--impact-of-agent-personality-on-multi-agent-system-performance", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:joyozhang333-lgtm--awesome-ai-organization", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xinxin2021110--inkrealm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:octadecimal-ai--hydra-agent-orchestration-showcase", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tauricresearch--tradingagents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:openai--openai-agents-python", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:open-multi-agent--open-multi-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lazyagi--lazyllm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:trypromptly--llmstack", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:internlm--mindsearch", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zhangzhengeric--sage", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:wjayesh--mahilo", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tsinghuac3i--marti", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:huygiatrng--alpacatradingagent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bupt-gamma--masfactory", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:raga-ai-hub--ragaai-catalyst", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:framerslab--agentos", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:langroid--langroid-examples", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:a-agmon--rs-graph-llm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:terry-cyx--metaopenfoam", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zju-llms--agent-kernel", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yongchao98--multi-agent-framework", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:liquidos-ai--autoagents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nlpodyssey--openai-agents-go", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cnsdqd-dyb--villageragent-minecraft-multiagent-framework", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sii-research--siirl", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:wanxingai--lightagent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:geteff1--multi-agent-conversation-for-disease-diagnosis", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pettingllms-ai--pettingllms", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:deepauto-ai--automl-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:minimalfuture--agentmesh", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:samholt--l2mac", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:codefuse-ai--codefuse-muagent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tradinggoose--tradinggoose.github.io", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:0pusai--opus-agent-swarm-llm-framework", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:llmp-io--legion", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:freedomintelligence--twinmarket", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:servicenow--tapeagents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adris-misra--multi-agentic-framework", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:openai--openai-cs-agents-demo", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:strands-agents--harness-sdk", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qx-labs--agents-deep-research", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:openai--openai-voice-agent-sdk-sample", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:shahidali54--openai-agents-sdk", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:agentops-ai--agentops", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:strands-agents--samples", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:panaversity--learn-agentic-ai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chatwoot--ai-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dannymac180--meta-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vercel--ai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:packtpublishing--building-agents-with-openai-agents-sdk", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:strands-agents--sdk-typescript", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jgravelle--openai-agentssdk-gui", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:davidpc007--solana-agent-kit", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:enkrateialucca--oreilly-openai-agents-sdk", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:deepstation--openai-academy-openai-agents-sdk", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:subhankaladi--openai_agents_sdk", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tanstack--ai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:apssouza22--ai-agent-react-llm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jeomon--meta-agent-with-more-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:anionex--llm-react-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cerno-ai--cerno-agentic-local-deep-research", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:thepradip--nexussql", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:om-ai-lab--open-agent-leaderboard", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:balaji-r-05--visa-hackathon", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:wz289494--anyclaw", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:banghuazhao--swift-ai-agent-demo", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vanillasky00--reagent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jasonclark--agentic-search-react", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nishchal-29--reasoning-llm-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lamemind--react-agent-ts", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:johnmachado11--react-agent-from-scratch", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zj-rrissh--react-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xinzhel--lits-llm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adilshamim8--ask-the-web-103", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:eriri9876--thought-collapse-llm-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:josephg3001--reactagent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rtj1--reflexive-llm-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tushar2704--react-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fireflyframework--fireflyframework-agentic", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nmhelmy--conversational-ai-reasoning-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:devxjitin--autourgos-react-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:alexanzilex--llm-agents-playground", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fvilmos--ai_react_agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mayankmishra15--math_reasoning_agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gambletan--agent-engine", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:farhad-davaripour--react_agent_from_scratch", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:alucek--smolagents-guide", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mstryoda--llm-agents-example", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:snowflake-labs--sfguide-build-agentic-workflows-with-huggingface-smolagents-in-snowflake", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vladkha--drone-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kazemihabib--huggingface-agents-course-marimo-edition", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:thecolonycc--smolagents-colony", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:murataslan1--ai-agent-benchmark", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:raymyers--swe-bench-util", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vexp-ai--vexp-swe-bench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:humphreysun98--repoagentbench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:linny006--agent-eval-harness", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:benchflow-ai--agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:robertkodes--repo-eval", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jlab-nlp--dialogue_swe_bench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rounakbende10--rh-swe-bench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nripankadas07--patchgym", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ttxs69--coding-agent-eval", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:he-yufeng--issuebenchkit", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xavierxmorris--ai-coding-benchmarks-reference", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nvandessel--floop-bench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ryanstoffel--context-layer-bench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sergeyklay--agentprobe", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:daseinlabs--code-compression-bench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sabofxx--agent-smith-42", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ttxs69--awesome-coding-agent-eval", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fl4p--kimi-tools", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:architehc--30b-moe-benchmarks", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:t-timms--godspeed-coding-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:huzaifa-57--self-sycophancy-on-swe-bench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:anandesh-sharma--awesome-agent-harnesses", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:euraika-labs--swe-postcutoff-bench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:brandeispatrick--openbench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tajaddin--swe-mini-bench", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:uran-company--awesome-ai-models-for-software-developers", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zuwasi--quickswe", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:flo7up--swe-rl-forge-lite", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ryota-kawamura--functions-tools-and-agents-with-langchain", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:oct4pie--toolbridge", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:arslankas--functions-tools-and-agents-with-langchain", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sjakati98--awesome-tools-for-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:haxxorcialtion--simpletool", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:violet-sword--ai-agent-toolcall-function", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pd2871--end-to-end-llm-projects", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fullstacksam23--gofer", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nghiavt2906--multi-agent-code-assistant-with-rag-and-tool-use", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:faruk-ops--ai-agent-function-calling", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kristofferv98--agent_nexus", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:paul-kingston--llm-tool-calling-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jra-codinglab--tool-use-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:wmmthu--awesome-llm-agent-skills-papers", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cerenaaa--ai-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:emrekaanb--ai-agent-tool-use", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yousefbadr0--agent-with-function-calling", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:prathameshlohar--functions-tools-and-agents-with-langchain", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sanskar1724--ai_agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chenkuanchung--llm-function-calling-lab", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:puru763--rag-powered-ai-travel-assistant-with-real-time-tool-calling-workflow-automation", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:johnnysgithubaccount--smart-home-virtual-assistant", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iammoafiaanawaz---agentic-ai-study-helper", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dlcastan--agentes", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:shashankg-dev404--react-native-gemma-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:danidevadoss--agentic-ai-poc-local-llm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:balamurali0532--llm-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:abhinav744--functions-tools-and-agents-with-langchain", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jbamigbade--llm-customer-support-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:karrrmma--codeguide-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hrishi0102--ai_agent_dbintegration", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sina158--llm-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rjmcginley--ai-agents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nftushar--from-llm-to-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rdowning07--agent-sandbox", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sumitroy154--the-knowledge-navigator-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:samuelmartinezduran--agenteval", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:deejayy14--career-conversation-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ngozikam--ai-agent-plant-advisor", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:poojitha29cj--llm", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:flashinfer-ai--flashinfer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hkustdial--flash-sparse-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:moonshotai--flashkda", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:amorehead--jvp_flash_attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tlc-pack--libflash_attn", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kyegomez--flashattention20", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:catswe--flash-attention-residuals", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nx-ai--mlstm_kernels", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dwvs2004--a.u.r.a.---flashattention-asic-accelerator", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zjy0516--fa-fwd", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lavawolfiee--mini-flash-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mog9--flashattention-cupy", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lyj20071013--triton-flashattention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fms-zth--blackflash", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tugbars--flash-attention-ptx-cuda", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aicl-lab--diy-flash-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:alexdremov--chill-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:alex4210987--qwen-tilelang-infer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:priyammaz--tritonkernels", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tonbistudio--gqa-flash-attn-rtx3060", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mvideet--adaptive-splash-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ankitbelbase17--flash-attention-forward-backward-pass-in-trition-kernel-", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sumantrad--flash", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:danieleschmidt--dp-flash-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mpsops--mps-linear-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:reyansh00--flashattention-kernels", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:v1kstrand--triton_fused_rope_flash_attn", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bruce-lee-ly--decoding_attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mininglamp-ai--cider", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:syhya--mlsys26-flashinfer-solution-sparse-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gloria72--flashinfer-kernel-bench", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:colin6618--flashinfer-performance-benchmarks", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ammar-alnagar--yaie", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kamalrss88--flashmla", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aymanelrody--flashmla", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kyegomez--jamba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nick7nlp--jamba_paper_reading", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:suzuki-2001--genomic-jamba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:farzanehjafari1987--jambatalk", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:amlplugins--ai21-chat", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sapmitra--ssm-scope", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gpantaz--retrievit", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:shivpratap10--hybridsegnet", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:wallscreet--tinymamba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:scraper-sky--cs224n_final_project", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chokevin8--mvhybrid", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gracee-dion--mambavision-multispectral-soil-analysis", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gokulprasanth-m--vimbaformer-a-hybrid-vision-mamba-unet-architecture-for-uav-semantic-segmentation", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:harsh543--nemotron-vllm-l4-infra", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:anany25--advanced-colorization-gan", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:arks0001--hymba-1.5b", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fabian-bautista--mlx-hymba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dogacel--auto-gpu-kernel", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:msdllcpapers--triton-sigmoid", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:prachi-kushwaha--triton-guide", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jerry2423--triton-attention-kernels", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mohamedabbouda--flash-attention-gpu-kernel", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:caroline430--kernel-learning", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kaustubhas--triton-based-tiled-flashattention-gpu-kernel", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chinmaydk99--gpu_optimized_attention_mechanisms", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:anggipratama17--triton-accelerated-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:harrisonvshen--triton-accelerated-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jrajath94--triton-inference-kernels", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:visharadr--mini-transformer---gpu-optimized", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bhavikupadhyay--triton-kernels", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yifu-ding--mp-sparse-attn", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tobiaszn8972--turboquant-gpu", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:selau642--quantizedattention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:susmitsingh01--triton-llm-kernels-lab", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:winnie1221--flash-attention-triton", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:indrarg8899--triton-rocm-samples", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:argonaut790--fused-turboquant", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:brianyu43--triton-training", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chelokot--flash-attention-rdna3", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gaurav711cgu--tritonforge", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:haregali--pageskip", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:j-arndt--orthocache-gpu", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iamrahulreddy--flashtile", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jaehbk--triton-programming-course", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:joey0122--mini-gpu-inference-engine", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:skyhehe123--scatterformer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xinghaochen--slab", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:milmor--ladagan", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:acosharma--elita-transformer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aliothren--efficient-transformer-accelerator", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zeeza18--efficient_transformer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:arturbeg--efficient_transformer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:szu-advtech-2024-test--363-gated-linear-attention-transformers-with-hardware-efficient-training", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:szu-advtech-2024--363-gated-linear-attention-transformers-with-hardware-efficient-training", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:johndpope--ladagan-pytorch", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:duongngockhanh--ladagan", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mohammedqaraad--msh-trans", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:shahazzat--fanformergpt", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:imfatal--implementation-and-analysis-of-transformer-variants", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ghsjk--esst", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:likith-sg--hmct", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:amrutiyakirtan--factorized-vit-probsparsing", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sohamkudva--gcltmodel", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nvlabs--mambavision", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xiongxiaoxu--sst", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tiger-ai-lab--vamba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xiaoyao3302--pointramba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:wenjuan7275--matir", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hu-po--karpamambathy", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vukrosic--hybrid-llm-mamba-transformer-research", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:deepinact--hybridtm", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:enesdoruk--da-mamba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nubot-nudt--inscmpr", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xiaomi-research--timeviper", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vukrosic--hybrid-llm-mamba-transformer-research-2", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nhanth301--mambastegaformer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:elonlit--melchior", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yixing-li--transmamba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lihongzhao99--rrgmambaformer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vukrosic--hybrid-llm-mamba-transformer-research-3", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:varun3ware--paged-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:icecreammilkytea--pagedkvcomm", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mukhal--micro-vllm", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jnros--cuda-attn-ref", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:manankapoor23--kv-paged-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bojjachetan--flash-decode-paged-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:truongson421--triton_kernel_paged_kv_cache_attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gaurav-redhat--paged-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:capybara-brain346--pagedattention-simulation", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lisihao--thunderllama", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zhihengy--int8-quantized-kv-cache-for-efficient-paged-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:p4ralyn--aapt_pagedattention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:abderahmane-ai--pagedattentionmetal", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hemanthiitj--kvstream", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sanjanashah--llm-paged-batching", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:akshitha024--kv-cache-optimizer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gandholisarat--kv-cache-visualizer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zlatanwic--fused-kernel-for-paged-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kennethjefferson--ccg_app_cuda_vllmpagedinference", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sahil139--predictive-kv-prefetch", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:google-deepmind--recurrentgemma", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:google-gemma--cookbook", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:surakku--cadence-gemma", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tushaargvs--sae", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sw10-cryptanalysis--recurrentgemma", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:firmanadi2002--recurrentgemma_summarizer", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vyom1611--recurrentgemma-cuda", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tushaargvs--simple-linear-rnn", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rajivraghu--google-recurrentgemma_2b", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:harshks911--molgemma-using-recurrentgemma-architecture", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:brendanjameslynskey--arch_03_long_context", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:semanticarchitectures--interceptordronesim", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:paragontechnologies--cuas-drone-detection", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:soussi-aymen--drone-detection-frontend", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mohamesb--ai-powered-drone-detection-system", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gerardgz--autonomous-drone-landing-risk-detection", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:soussi-aymen--drone-detection-backend", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:suliman8--skyshield", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jiyounroth--drone_rf_detection_fpga", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sayeh-1337--meshkah", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:a-for-aarushi--ps-09---ai-tools-for-maritime-domain-awareness-", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:razerardi--dark-vessel-sar-detection", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iberasa3--carcosa", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:andrewkritikos--ais_anomaly_detection", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:moulirichards--a-machine-learning-based-approach-for-detection-of-ships-and-uavs-in-military-forces", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:madeit07--radarmotr", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:radar-lab--radar_camera_mot", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ramchendooran--unscented-kalman-filter-multiple-object-tracking", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:santimontiel--lira-mot", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dinggh0817--4d_radar_mot", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:madeit07--radtrack", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:andreimoraru123--needforscenes", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nsenel--sensordatafusion", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jie311--lidar-radar-mot", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:steve-p99--radar-console-display-simulator", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vaiy108--multi-object-radar-tracking", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bingxue-xu--radarmot", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vaiy108--radar-camera-fusion", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:smanohar201--automotive_object_tracking", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:airou-lab--velacar3dmot", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:akajiaku11--carbon-footprint-analysis-and-emission-forecasting", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:beckybams--carbon-footprint-estimation-tool", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nefagi-01--cumulator", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gauravswarnakar--carbon-footprint-predictor", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:harshitadd--dp-carbon-footprint", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:curiosit--phd-predictingcarbonfootprintofbuildings", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nelvinebi--carbon-footprint-estimator-for-urban-households", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:airi-institute--eco4cast", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:avelero--avelero_hydrocarbon", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zero010010--usin-ml-to-predict-carbon-footprint-", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lokenderpratap8-sketch--carbon-footprint-ml", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:atharvchaudhari2907-code--carbonquest", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ksm26--carbon-aware-computing-for-genai-developers", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gurpreet0022--carbonfootprint", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mayowa1012--carbon-footprint-prediction", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tanayshandilya--carbon-footprint-monitoring-system", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jellybeansxo--carbonfootprintemission", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mounicauddagiri--carbon_footprints", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mazid2003--carbon-footprint-estimator-using-machine-learning", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kwabena-a--carbon-footprint", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yugh88--carbon-footprint-calculator_app", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dakshesh-1293--carbon-footprint-predictor", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vamshiiyer--ai-carbon-footprint-sustainability-advisor", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:krishiv-dev07--ecofootprint-analyzer", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:guan404ming--carbon-footprint-reporting", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aarti-paridwal--ai_carbon_footprint_predictor", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:viivianreine--carbon-footprint-calculator-using-advanced-machine-learning-cnn-", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ridhis110--carbon-footprint-fashion-ml", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:elizavetabugaeva--emissions_estimator", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cyrilbaah--carboncue", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:saintslab--carbontracker", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mlco2--codecarbon", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:juanjoowendler--co-emissions-tracking-for-ollama-ai-using-codecarbon", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:alexhroom--pytest-codecarbon", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:florisvdf--ai-environmental-impact", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:coluciana--codecarbon.jl", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gaurav-van--exploring-codecarbon", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:managerbanneaaya--carbon_tracker", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aswathy-k--sparsegpt-int8-quantization-codecarbon", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:albertovalerio--sustainability-of-recsys", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ajita07--carbon-efficient-chatbot", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sukanya-lahkar--green-ml-experiments", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:izzulroslan--greenmodel-ai-carbon-emission-tracker", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:riddhiijoshi--e-commerce-green-software-development", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:manojs15--carbon-footprint", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bonjourdave--ml-pipeline-project", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rohitsah13--eco-ops-green-computing-analytics-", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:051188-rk--greenml", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rohan-excelr--automl-green-model-selector", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vanshini04--ai-for-the-ai", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sb-ai-lab--eco2ai", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vladimir-laz--eco2ai_prototype", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:justlab-ai--eco2ai-backend", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:andvarfolomeev--eco2ai-playground", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fijishi-enterprises--eco2ai-power-comsumption", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pikvic--fefu-eco2ai", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:danieleschmidt--hf-eco2ai-plugin", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yinuoyang327--eco2ai_dashboard", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kp-156--eco2ai-implementation-minor-project-", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:breakend--experiment-impact-tracker", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tomlouismurphy--velocitytracker", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aqui001--web-dev-journey-from-zero-to-impact-", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:2236117534--experimental-data-sharing-", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:2236117534--analysis-code-and-experimental-materials", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:moeghashim--10x-shot", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:varsha199--vanguard-digital-redesign-impact-study", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cagriertem--eye-tracking-experiment", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:surfab--product-discovery-canvas", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ronithjuluri18--causal-impact-of-promotions-on-customer-retention", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rayyan-ridwan--greengrad", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:karankadhir86--green-ai-optimization-techniques-and-performance-energy-trade-off-studies.", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zwonziss--green-recipes", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hewwee--ai-in-manufacturing", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:satyanshu404--ai-carbon-footprint-manager", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:uygarkurt--llm-carbon-footprint", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:greenscale-ai--genai-carbon-footprint", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rebeccahihi--llm", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:maymiled--carbon-footprint-llm", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:talyke--javallmcarbonfootprint", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dhiksha-713--llm-carbon-footprint-research-portal", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pyladiesams--optimize-ai-prompts-jun2025", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lueasf--hack-loria", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jmdevita--carbon-proxy", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vivekaradshan--llm-inference-carbon-tracker", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:boettiger-lab--nrp-carbon-api", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:divyansh0208--carbon-footprint-awareness", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:prasun-sitaula--carbonwise", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:wyl2607--llm-carbon-index", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bigscience-workshop--carbon-footprint", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:conda-forge--codecarbon-feedstock", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mlco2--vscode-extension-codecarbon", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mlco2--codecarbon-static-website", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vienneraphael--scalene-codecarbon-workshop", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:fnndsc--pypx-repack-codecarbon-datalad", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sabrinamuh--projectcodecarbon-javascript-program", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:greatdevaks--iiit-codecarbon", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:raphischer--ai-energy-validation", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:up1--demo-codecarbon", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:blessinvarkey--ecocoding", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zkan--hello-codecarbon", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:koosuyeon--codecarbonforjetson", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mlcommons--power-dev", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:helmholtz-ai-energy--perun", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:powerapi-ng--pyjoules", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:amaurytiss--tf_energy_consumption", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:raghavsingraur--energy-_efficient-_systems", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sense-gvt--fast-bev", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ankita-kalra--pixor", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chaytonmin--awesome-bev-perception-multi-cameras", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kkk324--vehicle-distance-detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vdigpku--rcbevdet", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bharath5673--yolo_bev", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:uranus4ever--advanced-lane-detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ziningwang--sparse_pooling", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tteepe--tracktacular", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:overfitover--pixor_pytorch", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:megvii-research--cvpr2023-unidistill", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tmadl--ros-road-line-junction-extraction", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mengtan00--sa-bev", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zzj403--bev_robust", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pierluigiferrari--ssd3dbv", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:arcanaxion--cracked-egg-detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:norlab-ulaval--mask_bev", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:manaliagarwal--advanced-lane-detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:parkerfrisk--bird-s-eye-view", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cdemutiis--advanced_lanes_detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:handsomeyun--mic-bev", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aj-wuu--soccernetplus", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:shishir-pokhrel--bevlanedetection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lienghongky--cmx-hmi", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:autocompsyslab--dctnet", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:soubhikmajumdar--3d-lidar-based-birds-eye-view-object-detection-via-bevfusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:min60--lane_detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cp-security--cp-guard", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:trustai--robustbev", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kulmanferdi--rail-detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adlab-autodrive--bevfusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:linclubs--bevfusion-ros-tensorrt", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:maxleo-lmz--bevfusion_learningnote", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nvidia-ai-iot--lidar_ai_solution", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:seunghwi0613--ros2_bevfusion_demo", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:egemenkopuz--temporal-bevfusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:knzo25--bevfusion_ros2", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:shouxieai--bevfusion_02hero", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mx2013713828--cuda_bevfusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dreamdreams8--bevfusion_custom", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:barrydoooit--bevfusion4kitti", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iei-ap--iei-bevfusion_plus_plus", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:newintelligence4--bevfusion_preprocess", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sharkls--bevfusione2e", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mukaffi28--banglacalamitymmd-a-comprehensive-benchmark-dataset-for-multimodal-disaster-identification", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hoangquy18--multimodal-aspect-category-sentiment-analysis", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:neticus--dreamer-multimodal-emotion-recognition", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nhdnguyenhoangduc--llvip-pedestrian-detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:simondlevy--sensorfusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sharathsrini--kalman-filter-for-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:paulyehtw--lidar-and-radar-sensor-fusion-with-extended-kalman-filter", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:technitute--akfsf-simulation-cpp", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:diegoavillegasg--imu-gnss-lidar-sensor-fusion-using-extended-kalman-filter-for-state-estimation", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jeff-zhouxiaolong--demo_for_kalmanfilter", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:williamhyin--sfnd_unscented_kalman_filter", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ptiwari0664--sensorfusionnanodegree", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:asuri2--carnd-extended-kalman-filter-p6", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:niksknocksu--decentralized_kalmanfilter", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:neksfyris--esekf_imu_gnss_lidar", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:srnand--object-tracking-and-state-prediction-with-unscented-and-extended-kalman-filters", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rahul-sb--vins", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:janudis--extended-kalman-filter-gps_imu", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:informramiz--unscented-kalman-filter", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:paulyehtw--sensor-fusion-using-es-ekf", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:raghuramshankar--kalman-filter-localization", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:betabison--gnss-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cawfree--react-native-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vannizhou--dwd_sensor_fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sargisyonan--ukal", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:shantanubhadoria--go-kalmanfilter", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pangsu0613--clocs", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:timkie--yolo-lidar-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:loahit5101--pointpillars-camera-lidar-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rasd3--3d-cvf", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ram-godavarthi--sensor_fusion_3d_object_tracking_lidar-camera", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:laiqingsi--clocs_lqs", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rasd3--3d-dual-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xiongweiyi--lxl", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ika-rwth-aachen--multicorrupt", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adlab-autodrive--lidar-camera-robust-benchmark", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yinjunbo--centerpoint-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:shiluyang96--camera-lidar-map-fusion-model", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:azitt--lidar-camerafusion-3dobjectdetection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gokulk1994--3d-object-tracking-lidar-camera-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iranqin--supfusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xxlbigbrother--fusion-rcnn", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:amolloma--nd013-c2-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mingqj--depthfusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jigmiey--clocs", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:liyih--corenet", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:denyz--fadn", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rsade090--relifusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mingqj--dfu3d", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:morganm94--multicorrupt", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dr-utopia--lidar-camera-fusion-3d-detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tasarma--lidar-camera-fusion-3d-object-detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jynxzzz--dual-camera-lidar-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jylee-114--is-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:praveenkottari--multi-modal-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:redddddyyyyy--lidar-camera-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ashwinnraj--3d-obstacle-detection-with-lidar-camera", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:andia76--sdcnd02-03_3d_object_detection_and_tracking", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ka234388--lidar-camera-fusion-for-3d-object-detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nishanth-cryptos--3d-object-detection-bev-fusion-lidar-radar-camera-", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:saif-ashraf99--lidar-camera-fusion-for-3d-object-detection", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mhatre-shubham--camera-lidar-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lorenzofaoro--porject-data-fusion3d-object-detection-with-lidar-camera-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:whymesomeng--rgh-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:farhanaristo--ffcl3d", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:advaitp--clocs-pointpillars-and-cascade-rcnn-", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iceory--pmf", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lyon2020--msp-attacks", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:asguard-uci--msf-adv", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:oskarnatan--compact-perception", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ipranaysatija--multi-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mh-kav-institute--multi_sensor_perception_fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:msftest--multitest", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yeshwanthkumar-sa--multi-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aicha-el-idrissi--adas-multisensor-perception", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hdb1301040027--multi-sensor-fusion-for-perception", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gauravr2001--autonomous-vehicle-multi-sensor-fusion-perception", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:afondiel--multimodal-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:supergokou--sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adityasonawane1155--multi-sensor-fusion-for-advanced-perception-and-estimation-", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rahmanfarhan555--multi-sensor-fusion-for-advanced-perception-and-estimation-", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mendesri--multimodal_sensor_fusion_for_perception_and_state_estimation", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rahulaloth--robosense-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:muresaijaideepreddy--autonomous-vehicle-multi-sensor-perception-pipeline", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chenyang-zhu--self-driving-fusion-perception-tracking", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:poojasawantadas--adas-perception-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yeshwanthkumar-sa--multi-sensor-fusion-autonomous-vehicle", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sidkos--multi_sensor_fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jacksonzhang1116--astrionfusionengine", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kvemuru--spacecraft-perception-extended-kalman", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ahmedzainsyed--ai-based-multi-sensor-fusion-engine-for-autonomous-systems", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:msftest--drivence", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chr3720-alt--a-robust-multi-sensor-fusion-framework-for-autonomous-vehicle", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sarathkumarkomathukattil--deep-learning-perception-system", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yuukijiang--fire_perception", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:joshleh--fusiontrack", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:radwaelsobki--ros2-sensor-fusion-with-kalman-filter-for-real-time-multi-sensor-integration", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sothulthorn--mcformer", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qeyphen--ekfcore", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:awakenfury--cyber-bio-neural-perception-hud", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dabbuharshini--autosense", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aminetouiouel--digital-twin-acc-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sania01082002--enhancing-autonomous-vehicle-capabilities-for-inclement-weather-conditions", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:slowakp--arm-ros-gaz-data", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nithineeswar--profile", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cci9--ioucalculation", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chinmayak1197--visual-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:guigor020--lidar-camera-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:umtclskn--carla-similator-collision-avoidance-module", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:charithlegend--lidar-camera-sensor-fusion-for-3d-object-detection-and-depth-estimation", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bhuvan-belliyappa--object-level-sensor-data-fusion-for-road-user-detection-and-motion-prediction-", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:addykore--road-detection-through-sensor-fusion-with-fully-convolutional-neural-networks", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:rajaasimmustafa--3d-lidar-object-detection-dbscan-kitti", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gpanero--sensorfusionandtracking", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tumftm--dpft", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:purduedigitaltwin--redformer", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vanjeebeiyandeepmodeldevelopinggroup--innovusion_lidar_camera_radar_last_stage_fusion_perception", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kar-ab--ad_sensor_fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:collector-m--sensor_fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:guihaik--rcperception", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hrid16-32572-2--radar-camera-fusion-3d-perception", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zhinengz--sensor_fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cc-owner--rcdbf", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xiaorun2345--traffic_event", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:330012--av-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:omaremadaldin--end_to_end_perception_pipeline_with_3d_detection_tracking", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:thuvaragak--carla_project", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sguha16--multimodal-fusion-agent-negotiation", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:shrutik-panchal--masters-thesis-multimodal-feature-extraction-and-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:11rahi23--gusramoc", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:opendilab--interfuser", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:virtual-vehicle--aa274_autoware_ws", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:superxiaoying--autonomous_vehicle_paper_reading_list", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:say2l--gaussianfusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cmvs-lab--sac-residual-fusion-carla", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cakwok--autonomous-driving", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:manojkannan0803--autonomous-driving-controls", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:visionpilot-project--visionpilot", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:janudis--extented-kalman-filter-lidar-gps-imu", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yousefmansy--autonomous-highway-driving", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:loki-silvres--autonomous-driving-b3rb-buggy", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gopi-erabati--msf3ddetr", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yashstudy2025-collab--sensor-fusion-autonomous-driving", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chandru-python--multi-sensor-data-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jeswanth-kanipakam--ros2-bumperbot", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ece257b--sensor-fusion-for-autonomous-driving", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:marianocaccavale--sensorfusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:basictask--sensorfusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:highsky7--my_project_work_ws", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ronitsharan--autonomousdriving", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adamai-systems--autonomous", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aryanp2107--autonomous-perception-ensemble", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ra9hur--udacity-self-driving-car-nd-term2", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:robot-park--slam", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nikhil-xavier-ds--self_driving_car----sensor-fusion-localization---control", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zar-e--sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aryankrowser--early-sensor-fusion-and-object-detection-fro-autonomous-driving", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:manvithmadhuvarsu--multimodal-autonomous-driving-ssl-pipeline", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:vadhri--cps-notebook", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adam-shawky23--autonomous-driving-simulator", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:michil91--adas-sensor-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dawoodkhan9478--transformer-based-multi-modal-sensor-fusion-for-autonomous-driving-in-carla", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:saanindia--adas-gpu-sensor-fusion-cuda", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dloc19--autonomous-driving-", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:quantumgizmos--bp_osd", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kit-cel--quantum-neural-bp4-demo", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:weileizeng--belief-propagation", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yysf-brait--css_make", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:serco712--bplp", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:maltmn--quantumldpc", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aumpatel07--quantum-error-correction", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zynerji--qec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:musikavanhu--biomimetic-quantum-error-correction-simulation", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dies-irae--bp-sf", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:guillaumelessard--qector-decoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:quantumgizmos--ldpc", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qldpcorg--qldpc", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:quantumgizmos--bias_tailored_qldpc", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yuewuo--mwpf", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:seokhyung-lee--ldpc-post-selection", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kasaikenta--gd-css-decoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:diegoruiz-git--ldpcat", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:perlinm--qldpc", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:maxtremblay--ldpc", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:quantumsavory--pyqdecoders.jl", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:samyak-surti--qldpccodesim", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qec-pages--quantum_ldpc_codes", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qiskit-community--qcode-discovery", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:iqubit-org--auto-stabilizer-check", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kasaikenta--quantum-ldpc-decoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:punkdit--ldpc2018", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aleverrier--frontier", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mdwoolls--quantumldpccodelist", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:prismaticflame--qec_decoder_transformer", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:quantumlib--tesseract-decoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:quantumlib--chromobius", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:panqec--panqec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:winfred666--surfacecode-mwpmdecoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dhruvbhq--surf_code_sim", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ariawu34--qec-surface-code-simulation", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tqec--tqec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qiskit-community--qiskit-qec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qiskit-community--qiskit-ignis", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:deltakit--deltakit", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nvidia--ising-decoding", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:latticesurgery-com--lattice-surgery-compiler", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:cgranade--python-quaec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yuewuo--fusion-blossom", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jolle-ag--qdx", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qecsim--qecsim", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nzy1997--tensorqec.jl", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pecos-packages--pecos", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:saashajoshi--quantum-computing", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yuewuo--micro-blossom", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:deltakit--deltakit-textbook", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:francois-marie--awesome-quantum-computing-experiments", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chy-i--qecgpt", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:abdullahkhalids--qecft", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:sneakyweasel--genetic-quantum-correction", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:entropicalabs--el-loom", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yuewuo--qec-playground", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hongyehu--pyclifford", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:xanaduai--flamingpy", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:samgodwood--quantum_error_correction", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yezhuoyang--scalerqec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:unarylab--syndrilla", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chahak13--quantum-error-correction", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:socathie--quantum-error-correction", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qec-codes--qec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tahahassan92003--quantum_computing_tackle_noise_with_error_correction", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:the-singularity-research--error-correction", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nanleij--the-toric-code", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:stavan-jain--qeclean", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adelshb--graphqec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:lewis-od--quantumerrorcorrection", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:phionx--quantumnetworks", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:deduckproject--tesseract-code-stim", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:glanzz--quantum-error-correction", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nitchayanint--quantum-error-correction", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:alexisdevpro--surfaces_codes_stim", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:haber7789--quantumfaultsim", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qvazarius648--repetition-qec-stim", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pyhroff--qec-lab", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mkatal--stim-learning", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:msubhia--intermediate-qec-symmetries", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:wseltd--waynestark-quantum-decoderops-workbench", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:smitpatel228--surface-code-qec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ridgeback1982--cameramediacodec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:emilbjornson--irs-relaying", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:leye0--xamarinandroidmediacodecsurfacetosurface", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:usarica--fnal-qcdecodingtests", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:r-sweke--gym-surfacecode", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mbecker12--surface-rl-decoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ypwk--decodervis", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:marcserraperalta--lomatching", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:tjivuraveng--mwpm-irmwpm-decoder-of-surface-codes", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dua-arpit--single_shot_decoding_fractal", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ichirohasegawa07557--surface-code-decoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:jazzych--bp-mwpm-xzzx-code", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:qvazarius648--surface-code-decoders", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:adeelurehman--surface-code-decoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:liziming18--surface-code-simulation", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:aknapen--pinball", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:shraggy--xzzx-surface-code-decoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:timchan0--localuf", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:pisush--surface-code", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bryanzwu--transformer-surface-decoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:33hariharann-ux--synop_decoding", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kechen666--decoding", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:abenhemou--unimatch", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:bajwa4200--surface-code-qec", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:snpal--surface_code", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:natashamp--quantum-error-correction-decoder", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:quicophy--mdopt", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:surdui--eva", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:108mk--tensor_network_codes", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:chubbc--ju2021", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mlco2--impact", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ml-energy--zeus", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:ml-energy--leaderboard", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:responsibleproblemsolving--energy-usage", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:green-software-foundation--carbon-aware-sdk", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:green-software-foundation--if", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:powerapi-ng--powerapi", "dst": "p2:axis:energy", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:quantumlib--stim", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:oscarhiggott--pymatching", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:seokhyung-lee--color-code-stim", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:gongaa--feedback-gnn", "dst": "p2:axis:qec", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:dao-ailab--flash-attention", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zyphra--zamba2", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:nvlabs--hymba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:microsoft--samba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:state-spaces--mamba", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:kyegomez--griffin", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:proger--hippogriff", "dst": "p2:axis:attention", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:hkust-aerial-robotics--vins-fusion", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:open-mmlab--mmdetection3d", "dst": "p2:axis:fusion", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:zhouyi1023--awesome-radar-perception", "dst": "p2:axis:defense", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:significant-gravitas--autogpt", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:crewaiinc--crewai", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:stanfordnlp--dspy", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:mem0ai--mem0", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:letta-ai--letta", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:huggingface--smolagents", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:swe-agent--swe-agent", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:openbmb--chatdev", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:yoheinakajima--babyagi", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:run-llama--llama_index", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:repo:assafelovic--gpt-researcher", "dst": "p2:axis:agents", "rel": "repo-in-axis"}
{"type": "edge", "src": "p2:paper:2504.00727", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lewis-newsham", "dst": "p2:paper:2504.00727", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-prince", "dst": "p2:paper:2504.00727", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2308.11432", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lei-wang", "dst": "p2:paper:2308.11432", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-ma", "dst": "p2:paper:2308.11432", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xueyang-feng", "dst": "p2:paper:2308.11432", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zeyu-zhang", "dst": "p2:paper:2308.11432", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-yang", "dst": "p2:paper:2308.11432", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingsen-zhang", "dst": "p2:paper:2308.11432", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiyuan-chen", "dst": "p2:paper:2308.11432", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiakai-tang", "dst": "p2:paper:2308.11432", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.01603", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mayk-caldas-ramos", "dst": "p2:paper:2407.01603", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-j-collison", "dst": "p2:paper:2407.01603", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrew-d-white", "dst": "p2:paper:2407.01603", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.04442", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:saikat-barua", "dst": "p2:paper:2404.04442", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.17281", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sadia-sultana-chowa", "dst": "p2:paper:2508.17281", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:riasad-alvi", "dst": "p2:paper:2508.17281", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:subhey-sadi-rahman", "dst": "p2:paper:2508.17281", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:md-abdur-rahman", "dst": "p2:paper:2508.17281", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohaimenul-azam-khan-raiaan", "dst": "p2:paper:2508.17281", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:md-rafiqul-islam", "dst": "p2:paper:2508.17281", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mukhtar-hussain", "dst": "p2:paper:2508.17281", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sami-azam", "dst": "p2:paper:2508.17281", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.16340", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zefan-wang", "dst": "p2:paper:2310.16340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zichuan-liu", "dst": "p2:paper:2310.16340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yingying-zhang", "dst": "p2:paper:2310.16340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aoxiao-zhong", "dst": "p2:paper:2310.16340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jihong-wang", "dst": "p2:paper:2310.16340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fengbin-yin", "dst": "p2:paper:2310.16340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lunting-fan", "dst": "p2:paper:2310.16340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lingfei-wu", "dst": "p2:paper:2310.16340", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.16878", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:songjun-tu", "dst": "p2:paper:2412.16878", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingbo-sun", "dst": "p2:paper:2412.16878", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qichao-zhang", "dst": "p2:paper:2412.16878", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiangyuan-lan", "dst": "p2:paper:2412.16878", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dongbin-zhao", "dst": "p2:paper:2412.16878", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.11826", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chen-zhu", "dst": "p2:paper:2408.11826", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yihang-cheng", "dst": "p2:paper:2408.11826", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingshuai-zhang", "dst": "p2:paper:2408.11826", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yusheng-qiu", "dst": "p2:paper:2408.11826", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sitao-xia", "dst": "p2:paper:2408.11826", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hengshu-zhu", "dst": "p2:paper:2408.11826", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.09567", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:laura-fern-ndez-becerra", "dst": "p2:paper:2403.09567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:miguel-ngel-gonz-lez-santamarta", "dst": "p2:paper:2403.09567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ngel-manuel-guerrero-higueras", "dst": "p2:paper:2403.09567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francisco-javier-rodr-guez-lera", "dst": "p2:paper:2403.09567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vicente-matell-n-olivera", "dst": "p2:paper:2403.09567", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2308.10204", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhuolun-he", "dst": "p2:paper:2308.10204", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoyuan-wu", "dst": "p2:paper:2308.10204", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyun-zhang", "dst": "p2:paper:2308.10204", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xufeng-yao", "dst": "p2:paper:2308.10204", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:su-zheng", "dst": "p2:paper:2308.10204", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haisheng-zheng", "dst": "p2:paper:2308.10204", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bei-yu", "dst": "p2:paper:2308.10204", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.03459", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:pengbo-hu", "dst": "p2:paper:2503.03459", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiang-ying", "dst": "p2:paper:2503.03459", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2401.02851", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:akhil-vaid", "dst": "p2:paper:2401.02851", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joshua-lampert", "dst": "p2:paper:2401.02851", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:juhee-lee", "dst": "p2:paper:2401.02851", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ashwin-sawant", "dst": "p2:paper:2401.02851", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:donald-apakama", "dst": "p2:paper:2401.02851", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ankit-sakhuja", "dst": "p2:paper:2401.02851", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ali-soroush", "dst": "p2:paper:2401.02851", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sarah-bick", "dst": "p2:paper:2401.02851", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.11872", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jakub-hoscilowicz", "dst": "p2:paper:2410.11872", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bartosz-maj", "dst": "p2:paper:2410.11872", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bartosz-kozakiewicz", "dst": "p2:paper:2410.11872", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:oleksii-tymoshchuk", "dst": "p2:paper:2410.11872", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:artur-janicki", "dst": "p2:paper:2410.11872", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.16197", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hao-gao", "dst": "p2:paper:2410.16197", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingyue-wang", "dst": "p2:paper:2410.16197", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenyang-fang", "dst": "p2:paper:2410.16197", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingwei-xu", "dst": "p2:paper:2410.16197", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yunpeng-huang", "dst": "p2:paper:2410.16197", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:taolue-chen", "dst": "p2:paper:2410.16197", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoxing-ma", "dst": "p2:paper:2410.16197", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.16855", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zijing-shi", "dst": "p2:paper:2504.16855", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:meng-fang", "dst": "p2:paper:2504.16855", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ling-chen", "dst": "p2:paper:2504.16855", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.10971", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tianyu-fan", "dst": "p2:paper:2512.10971", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuhao-yang", "dst": "p2:paper:2512.10971", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yangqin-jiang", "dst": "p2:paper:2512.10971", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yifei-zhang", "dst": "p2:paper:2512.10971", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxuan-chen", "dst": "p2:paper:2512.10971", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chao-huang", "dst": "p2:paper:2512.10971", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.13383", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:akbar-anbar-jafari", "dst": "p2:paper:2601.13383", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cagri-ozcinar", "dst": "p2:paper:2601.13383", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gholamreza-anbarjafari", "dst": "p2:paper:2601.13383", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.11021", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tanmana-sadhu", "dst": "p2:paper:2408.11021", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ali-pesaranghader", "dst": "p2:paper:2408.11021", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanan-chen", "dst": "p2:paper:2408.11021", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dong-hoon-yi", "dst": "p2:paper:2408.11021", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.09990", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sietse-schelpe", "dst": "p2:paper:2605.09990", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.08136", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zefang-liu", "dst": "p2:paper:2506.08136", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yinzhu-quan", "dst": "p2:paper:2506.08136", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.12644", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zonghao-ying", "dst": "p2:paper:2603.12644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiao-yang", "dst": "p2:paper:2603.12644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:siyang-wu", "dst": "p2:paper:2603.12644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yumeng-song", "dst": "p2:paper:2603.12644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-qu", "dst": "p2:paper:2603.12644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hainan-li", "dst": "p2:paper:2603.12644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianlin-li", "dst": "p2:paper:2603.12644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiakai-wang", "dst": "p2:paper:2603.12644", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.13143", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ruofan-lu", "dst": "p2:paper:2508.13143", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yichen-li", "dst": "p2:paper:2508.13143", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yintong-huo", "dst": "p2:paper:2508.13143", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.24024", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yifan-xu", "dst": "p2:paper:2410.24024", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiao-liu", "dst": "p2:paper:2410.24024", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xueqiao-sun", "dst": "p2:paper:2410.24024", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:siyi-cheng", "dst": "p2:paper:2410.24024", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-yu", "dst": "p2:paper:2410.24024", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanyu-lai", "dst": "p2:paper:2410.24024", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shudan-zhang", "dst": "p2:paper:2410.24024", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dan-zhang", "dst": "p2:paper:2410.24024", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2308.05960", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhiwei-liu", "dst": "p2:paper:2308.05960", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weiran-yao", "dst": "p2:paper:2308.05960", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianguo-zhang", "dst": "p2:paper:2308.05960", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:le-xue", "dst": "p2:paper:2308.05960", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shelby-heinecke", "dst": "p2:paper:2308.05960", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rithesh-murthy", "dst": "p2:paper:2308.05960", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yihao-feng", "dst": "p2:paper:2308.05960", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zeyuan-chen", "dst": "p2:paper:2308.05960", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.03159", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:reshabh-k-sharma", "dst": "p2:paper:2605.03159", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gaurav-mittal", "dst": "p2:paper:2605.03159", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-hu", "dst": "p2:paper:2605.03159", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.13820", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jun-liu", "dst": "p2:paper:2505.13820", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenglun-kong", "dst": "p2:paper:2505.13820", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peiyan-dong", "dst": "p2:paper:2505.13820", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:changdi-yang", "dst": "p2:paper:2505.13820", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianqi-li", "dst": "p2:paper:2505.13820", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-tang", "dst": "p2:paper:2505.13820", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:geng-yuan", "dst": "p2:paper:2505.13820", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-niu", "dst": "p2:paper:2505.13820", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.23193", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:elzo-brito-dos-santos-filho", "dst": "p2:paper:2602.23193", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.09901", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lianhao-zhou", "dst": "p2:paper:2510.09901", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongyi-ling", "dst": "p2:paper:2510.09901", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cong-fu", "dst": "p2:paper:2510.09901", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yepeng-huang", "dst": "p2:paper:2510.09901", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-sun", "dst": "p2:paper:2510.09901", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wendi-yu", "dst": "p2:paper:2510.09901", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoxuan-wang", "dst": "p2:paper:2510.09901", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiner-li", "dst": "p2:paper:2510.09901", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2501.05171", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jinghua-piao", "dst": "p2:paper:2501.05171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhihong-lu", "dst": "p2:paper:2501.05171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-gao", "dst": "p2:paper:2501.05171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fengli-xu", "dst": "p2:paper:2501.05171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qinghua-hu", "dst": "p2:paper:2501.05171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fernando-p-santos", "dst": "p2:paper:2501.05171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-li", "dst": "p2:paper:2501.05171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:james-evans", "dst": "p2:paper:2501.05171", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2312.13382", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:arnav-singhvi", "dst": "p2:paper:2312.13382", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:manish-shetty", "dst": "p2:paper:2312.13382", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shangyin-tan", "dst": "p2:paper:2312.13382", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-potts", "dst": "p2:paper:2312.13382", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:koushik-sen", "dst": "p2:paper:2312.13382", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matei-zaharia", "dst": "p2:paper:2312.13382", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:omar-khattab", "dst": "p2:paper:2312.13382", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.04869", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shiek-ruksana", "dst": "p2:paper:2604.04869", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sailesh-kiran-kurra", "dst": "p2:paper:2604.04869", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thipparthi-sanjay-baradwaj", "dst": "p2:paper:2604.04869", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.03620", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:francisca-lemos", "dst": "p2:paper:2507.03620", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:victor-alves", "dst": "p2:paper:2507.03620", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:filipa-ferraz", "dst": "p2:paper:2507.03620", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.15298", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:bhaskarjit-sarmah", "dst": "p2:paper:2412.15298", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kriti-dutta", "dst": "p2:paper:2412.15298", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anna-grigoryan", "dst": "p2:paper:2412.15298", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sachin-tiwari", "dst": "p2:paper:2412.15298", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stefano-pasquali", "dst": "p2:paper:2412.15298", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dhagash-mehta", "dst": "p2:paper:2412.15298", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.18564", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:rong-wang", "dst": "p2:paper:2411.18564", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kun-sun", "dst": "p2:paper:2411.18564", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jonas-kuhn", "dst": "p2:paper:2411.18564", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.25169", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:marina-s-nchez-torr-n", "dst": "p2:paper:2603.25169", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daria-akselrod", "dst": "p2:paper:2603.25169", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jason-rauchwerk", "dst": "p2:paper:2603.25169", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.17937", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiaotang-du", "dst": "p2:paper:2602.17937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:giwon-hong", "dst": "p2:paper:2602.17937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wai-chung-kwan", "dst": "p2:paper:2602.17937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rohit-saxena", "dst": "p2:paper:2602.17937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ivan-titov", "dst": "p2:paper:2602.17937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pasquale-minervini", "dst": "p2:paper:2602.17937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:emily-allaway", "dst": "p2:paper:2602.17937", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.16827", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:maksim-eren", "dst": "p2:paper:2603.16827", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eric-michalak", "dst": "p2:paper:2603.16827", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:brian-cook", "dst": "p2:paper:2603.16827", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:johnny-seales", "dst": "p2:paper:2603.16827", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.22565", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wenyuan-chen", "dst": "p2:paper:2509.22565", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fateme-nateghi-haredasht", "dst": "p2:paper:2509.22565", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kameron-c-black", "dst": "p2:paper:2509.22565", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francois-grolleau", "dst": "p2:paper:2509.22565", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:emily-alsentzer", "dst": "p2:paper:2509.22565", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jonathan-h-chen", "dst": "p2:paper:2509.22565", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stephen-p-ma", "dst": "p2:paper:2509.22565", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.20836", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:asad-aali", "dst": "p2:paper:2511.20836", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:muhammad-ahmed-mohsin", "dst": "p2:paper:2511.20836", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vasiliki-bikia", "dst": "p2:paper:2511.20836", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arnav-singhvi", "dst": "p2:paper:2511.20836", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:richard-gaus", "dst": "p2:paper:2511.20836", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:suhana-bedi", "dst": "p2:paper:2511.20836", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hejie-cui", "dst": "p2:paper:2511.20836", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:miguel-fuentes", "dst": "p2:paper:2511.20836", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.10673", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hisham-a-alyahya", "dst": "p2:paper:2503.10673", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haidar-khan", "dst": "p2:paper:2503.10673", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yazeed-alnumay", "dst": "p2:paper:2503.10673", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:m-saiful-bari", "dst": "p2:paper:2503.10673", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:b-lent-yener", "dst": "p2:paper:2503.10673", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.00410", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aninda-ray", "dst": "p2:paper:2605.00410", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.11019", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:vincent-koc", "dst": "p2:paper:2506.11019", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jacques-verre", "dst": "p2:paper:2506.11019", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:douglas-blank", "dst": "p2:paper:2506.11019", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abigail-morgan", "dst": "p2:paper:2506.11019", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.26521", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nafiseh-kahani", "dst": "p2:paper:2605.26521", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mojtaba-bagherzadeh", "dst": "p2:paper:2605.26521", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.04859", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:stefano-de-paoli", "dst": "p2:paper:2503.04859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:walter-stan-mathis", "dst": "p2:paper:2503.04859", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.18524", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:guowei-xu", "dst": "p2:paper:2505.18524", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mert-yuksekgonul", "dst": "p2:paper:2505.18524", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:carlos-guestrin", "dst": "p2:paper:2505.18524", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:james-zou", "dst": "p2:paper:2505.18524", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.13930", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:matey-krastev", "dst": "p2:paper:2508.13930", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:miklos-hamar", "dst": "p2:paper:2508.13930", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:danilo-toapanta", "dst": "p2:paper:2508.13930", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jesse-brouwers", "dst": "p2:paper:2508.13930", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yibin-lei", "dst": "p2:paper:2508.13930", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.11299", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:andrei-niculae", "dst": "p2:paper:2507.11299", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:adrian-cosma", "dst": "p2:paper:2507.11299", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cosmin-dumitrache", "dst": "p2:paper:2507.11299", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:emilian-r-doi", "dst": "p2:paper:2507.11299", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.14629", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:peng-zhang", "dst": "p2:paper:2603.14629", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.20491", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:filomene-roquefort", "dst": "p2:paper:2505.20491", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexandre-ducorroy", "dst": "p2:paper:2505.20491", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rachid-riad", "dst": "p2:paper:2505.20491", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.11118", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kristin-qi", "dst": "p2:paper:2503.11118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:youxiang-zhu", "dst": "p2:paper:2503.11118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaohui-liang", "dst": "p2:paper:2503.11118", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.13346", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:pengcheng-wang", "dst": "p2:paper:2604.13346", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jerry-huang", "dst": "p2:paper:2604.13346", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiarui-yao", "dst": "p2:paper:2604.13346", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rui-pan", "dst": "p2:paper:2604.13346", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peizhi-niu", "dst": "p2:paper:2604.13346", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yaowenqi-liu", "dst": "p2:paper:2604.13346", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruida-wang", "dst": "p2:paper:2604.13346", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:renhao-lu", "dst": "p2:paper:2604.13346", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.06937", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:teo-susnjak", "dst": "p2:paper:2605.06937", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.14544", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:augustin-toma", "dst": "p2:paper:2404.14544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ronald-xie", "dst": "p2:paper:2404.14544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:steven-palayew", "dst": "p2:paper:2404.14544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:patrick-r-lawler", "dst": "p2:paper:2404.14544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bo-wang", "dst": "p2:paper:2404.14544", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.21907", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kemal-sami-karaca", "dst": "p2:paper:2509.21907", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bahaeddin-eravc", "dst": "p2:paper:2509.21907", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.11267", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zeyu-he", "dst": "p2:paper:2502.11267", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:saniya-naphade", "dst": "p2:paper:2502.11267", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ting-hao-kenneth-huang", "dst": "p2:paper:2502.11267", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.10930", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dilara-soylu", "dst": "p2:paper:2407.10930", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-potts", "dst": "p2:paper:2407.10930", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:omar-khattab", "dst": "p2:paper:2407.10930", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.16544", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zachary-ellis", "dst": "p2:paper:2511.16544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jared-joselowitz", "dst": "p2:paper:2511.16544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yash-deo", "dst": "p2:paper:2511.16544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yajie-he", "dst": "p2:paper:2511.16544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anna-kalygina", "dst": "p2:paper:2511.16544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aisling-higham", "dst": "p2:paper:2511.16544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mana-rahimzadeh", "dst": "p2:paper:2511.16544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yan-jia", "dst": "p2:paper:2511.16544", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.11051", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chandler-smith", "dst": "p2:paper:2603.11051", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:magnus-sesodia", "dst": "p2:paper:2603.11051", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:friedrich-lindenberg", "dst": "p2:paper:2603.11051", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christian-schroeder-de-witt", "dst": "p2:paper:2603.11051", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.07456", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhiyong-wu", "dst": "p2:paper:2402.07456", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chengcheng-han", "dst": "p2:paper:2402.07456", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zichen-ding", "dst": "p2:paper:2402.07456", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenmin-weng", "dst": "p2:paper:2402.07456", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhoumianze-liu", "dst": "p2:paper:2402.07456", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shunyu-yao", "dst": "p2:paper:2402.07456", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tao-yu", "dst": "p2:paper:2402.07456", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lingpeng-kong", "dst": "p2:paper:2402.07456", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.05665", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chang-yang", "dst": "p2:paper:2602.05665", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chuang-zhou", "dst": "p2:paper:2602.05665", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yilin-xiao", "dst": "p2:paper:2602.05665", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:su-dong", "dst": "p2:paper:2602.05665", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luyao-zhuang", "dst": "p2:paper:2602.05665", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yujing-zhang", "dst": "p2:paper:2602.05665", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhu-wang", "dst": "p2:paper:2602.05665", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zijin-hong", "dst": "p2:paper:2602.05665", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.07798", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiaquan-zhang", "dst": "p2:paper:2604.07798", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chaoning-zhang", "dst": "p2:paper:2604.07798", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuxu-chen", "dst": "p2:paper:2604.07798", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenzhen-huang", "dst": "p2:paper:2604.07798", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pengcheng-zheng", "dst": "p2:paper:2604.07798", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhicheng-wang", "dst": "p2:paper:2604.07798", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ping-guo", "dst": "p2:paper:2604.07798", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fan-mo", "dst": "p2:paper:2604.07798", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.20465", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yang-li", "dst": "p2:paper:2601.20465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaxiang-liu", "dst": "p2:paper:2601.20465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yusong-wang", "dst": "p2:paper:2601.20465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yujie-wu", "dst": "p2:paper:2601.20465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingkun-xu", "dst": "p2:paper:2601.20465", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.18642", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lei-wei", "dst": "p2:paper:2601.18642", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiao-peng", "dst": "p2:paper:2601.18642", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xu-dong", "dst": "p2:paper:2601.18642", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:niantao-xie", "dst": "p2:paper:2601.18642", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bin-wang", "dst": "p2:paper:2601.18642", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.01885", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yi-yu", "dst": "p2:paper:2601.01885", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liuyi-yao", "dst": "p2:paper:2601.01885", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuexiang-xie", "dst": "p2:paper:2601.01885", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qingquan-tan", "dst": "p2:paper:2601.01885", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaqi-feng", "dst": "p2:paper:2601.01885", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yaliang-li", "dst": "p2:paper:2601.01885", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:libing-wu", "dst": "p2:paper:2601.01885", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.23195", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zewen-liu", "dst": "p2:paper:2606.23195", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.15701", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiawei-yu", "dst": "p2:paper:2605.15701", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yixiang-fang", "dst": "p2:paper:2605.15701", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xilin-liu", "dst": "p2:paper:2605.15701", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuchi-ma", "dst": "p2:paper:2605.15701", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.18421", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuyao-wang", "dst": "p2:paper:2605.18421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhongjian-zhang", "dst": "p2:paper:2605.18421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mo-chi", "dst": "p2:paper:2605.18421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaichi-yu", "dst": "p2:paper:2605.18421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuhan-li", "dst": "p2:paper:2605.18421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:miao-peng", "dst": "p2:paper:2605.18421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bing-tong", "dst": "p2:paper:2605.18421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-zhang", "dst": "p2:paper:2605.18421", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.02373", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qianshan-wei", "dst": "p2:paper:2510.02373", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tengchao-yang", "dst": "p2:paper:2510.02373", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yaochen-wang", "dst": "p2:paper:2510.02373", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinfeng-li", "dst": "p2:paper:2510.02373", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lijun-li", "dst": "p2:paper:2510.02373", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenfei-yin", "dst": "p2:paper:2510.02373", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-zhan", "dst": "p2:paper:2510.02373", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thorsten-holz", "dst": "p2:paper:2510.02373", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.06025", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haozhen-zhang", "dst": "p2:paper:2602.06025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haodong-yue", "dst": "p2:paper:2602.06025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tao-feng", "dst": "p2:paper:2602.06025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:quanyu-long", "dst": "p2:paper:2602.06025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianzhu-bao", "dst": "p2:paper:2602.06025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bowen-jin", "dst": "p2:paper:2602.06025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weizhi-zhang", "dst": "p2:paper:2602.06025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiao-li", "dst": "p2:paper:2602.06025", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.14498", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jingbo-yang", "dst": "p2:paper:2605.14498", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kwei-herng-lai", "dst": "p2:paper:2605.14498", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaowen-wang", "dst": "p2:paper:2605.14498", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shiyu-chang", "dst": "p2:paper:2605.14498", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yaar-harari", "dst": "p2:paper:2605.14498", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:evgeniy-gabrilovich", "dst": "p2:paper:2605.14498", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.29914", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kuan-wang", "dst": "p2:paper:2606.29914", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.06716", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jinghao-luo", "dst": "p2:paper:2605.06716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuchen-tian", "dst": "p2:paper:2605.06716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chuxue-cao", "dst": "p2:paper:2605.06716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ziyang-luo", "dst": "p2:paper:2605.06716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongzhan-lin", "dst": "p2:paper:2605.06716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaixin-li", "dst": "p2:paper:2605.06716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chuyi-kong", "dst": "p2:paper:2605.06716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruichao-yang", "dst": "p2:paper:2605.06716", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.21567", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:changzhi-sun", "dst": "p2:paper:2512.21567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiangyu-chen", "dst": "p2:paper:2512.21567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jixiang-luo", "dst": "p2:paper:2512.21567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dell-zhang", "dst": "p2:paper:2512.21567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuelong-li", "dst": "p2:paper:2512.21567", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.10702", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ruozhen-yang", "dst": "p2:paper:2601.10702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yucheng-jiang", "dst": "p2:paper:2601.10702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yueqi-jiang", "dst": "p2:paper:2601.10702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:priyanka-kargupta", "dst": "p2:paper:2601.10702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yunyi-zhang", "dst": "p2:paper:2601.10702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiawei-han", "dst": "p2:paper:2601.10702", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.14470", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:pavan-c-shekar", "dst": "p2:paper:2606.14470", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abhishek-h-s", "dst": "p2:paper:2606.14470", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aswanth-krishnan", "dst": "p2:paper:2606.14470", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.29341", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chengzhi-liu", "dst": "p2:paper:2605.29341", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuzhe-yang", "dst": "p2:paper:2605.29341", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sophia-xiao-pu", "dst": "p2:paper:2605.29341", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yepeng-liu", "dst": "p2:paper:2605.29341", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lin-long", "dst": "p2:paper:2605.29341", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yichen-guo", "dst": "p2:paper:2605.29341", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nuo-chen", "dst": "p2:paper:2605.29341", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhaotian-weng", "dst": "p2:paper:2605.29341", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.20117", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lei-zheng", "dst": "p2:paper:2604.20117", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weinan-song", "dst": "p2:paper:2604.20117", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daili-li", "dst": "p2:paper:2604.20117", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanming-yang", "dst": "p2:paper:2604.20117", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.19320", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dongming-jiang", "dst": "p2:paper:2602.19320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-li", "dst": "p2:paper:2602.19320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:songtao-wei", "dst": "p2:paper:2602.19320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinxin-yang", "dst": "p2:paper:2602.19320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ayushi-kishore", "dst": "p2:paper:2602.19320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alysa-zhao", "dst": "p2:paper:2602.19320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dingyi-kang", "dst": "p2:paper:2602.19320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xu-hu", "dst": "p2:paper:2602.19320", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.12686", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:samarth-sarin", "dst": "p2:paper:2512.12686", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lovepreet-singh", "dst": "p2:paper:2512.12686", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bhaskarjit-sarmah", "dst": "p2:paper:2512.12686", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dhagash-mehta", "dst": "p2:paper:2512.12686", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.12110", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wujiang-xu", "dst": "p2:paper:2502.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zujie-liang", "dst": "p2:paper:2502.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kai-mei", "dst": "p2:paper:2502.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hang-gao", "dst": "p2:paper:2502.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:juntao-tan", "dst": "p2:paper:2502.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongfeng-zhang", "dst": "p2:paper:2502.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.01528", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shizuo-tian", "dst": "p2:paper:2606.01528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaohong-weng", "dst": "p2:paper:2606.01528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rui-kong", "dst": "p2:paper:2606.01528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxuan-chen", "dst": "p2:paper:2606.01528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guohong-liu", "dst": "p2:paper:2606.01528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuebing-song", "dst": "p2:paper:2606.01528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiacheng-liu", "dst": "p2:paper:2606.01528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuchen-li", "dst": "p2:paper:2606.01528", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.09747", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xingyu-lyu", "dst": "p2:paper:2604.09747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianfeng-he", "dst": "p2:paper:2604.09747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ning-wang", "dst": "p2:paper:2604.09747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yidan-hu", "dst": "p2:paper:2604.09747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tao-li", "dst": "p2:paper:2604.09747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:danjue-chen", "dst": "p2:paper:2604.09747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shixiong-li", "dst": "p2:paper:2604.09747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yimin-chen", "dst": "p2:paper:2604.09747", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.05520", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:rui-li", "dst": "p2:paper:2510.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zeyu-zhang", "dst": "p2:paper:2510.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaohe-bo", "dst": "p2:paper:2510.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zihang-tian", "dst": "p2:paper:2510.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xu-chen", "dst": "p2:paper:2510.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:quanyu-dai", "dst": "p2:paper:2510.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenhua-dong", "dst": "p2:paper:2510.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruiming-tang", "dst": "p2:paper:2510.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.03236", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dongming-jiang", "dst": "p2:paper:2601.03236", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-li", "dst": "p2:paper:2601.03236", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guanpeng-li", "dst": "p2:paper:2601.03236", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bingzhe-li", "dst": "p2:paper:2601.03236", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.23723", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhewen-tan", "dst": "p2:paper:2605.23723", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yilun-yao", "dst": "p2:paper:2605.23723", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huiyan-jin", "dst": "p2:paper:2605.23723", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenhan-yu", "dst": "p2:paper:2605.23723", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guoan-wang", "dst": "p2:paper:2605.23723", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mengyuan-fan", "dst": "p2:paper:2605.23723", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liang-lu", "dst": "p2:paper:2605.23723", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:feng-liu", "dst": "p2:paper:2605.23723", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.19537", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:bobo-li", "dst": "p2:paper:2512.19537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xudong-han", "dst": "p2:paper:2512.19537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiang-liu", "dst": "p2:paper:2512.19537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuzhe-ding", "dst": "p2:paper:2512.19537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liqiang-jing", "dst": "p2:paper:2512.19537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhaoqi-zhang", "dst": "p2:paper:2512.19537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinheng-li", "dst": "p2:paper:2512.19537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinya-du", "dst": "p2:paper:2512.19537", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.15421", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:taeyun-roh", "dst": "p2:paper:2603.15421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wonjune-jang", "dst": "p2:paper:2603.15421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junha-jung", "dst": "p2:paper:2603.15421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jaewoo-kang", "dst": "p2:paper:2603.15421", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.12285", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhaofen-wu", "dst": "p2:paper:2604.12285", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanrong-zhang", "dst": "p2:paper:2604.12285", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fulin-lin", "dst": "p2:paper:2604.12285", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wujiang-xu", "dst": "p2:paper:2604.12285", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinran-xu", "dst": "p2:paper:2604.12285", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yankai-chen", "dst": "p2:paper:2604.12285", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:henry-peng-zou", "dst": "p2:paper:2604.12285", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaowen-chen", "dst": "p2:paper:2604.12285", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.13189", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:j-de-curt", "dst": "p2:paper:2603.13189", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:i-de-zarz", "dst": "p2:paper:2603.13189", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.05449", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:raphael-shu", "dst": "p2:paper:2412.05449", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nilaksh-das", "dst": "p2:paper:2412.05449", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michelle-yuan", "dst": "p2:paper:2412.05449", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:monica-sunkara", "dst": "p2:paper:2412.05449", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-zhang", "dst": "p2:paper:2412.05449", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.26352", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kotaro-furuya", "dst": "p2:paper:2510.26352", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuichi-kitagawa", "dst": "p2:paper:2510.26352", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.00131", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:moritz-weckbecker", "dst": "p2:paper:2603.00131", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jonas-m-ller", "dst": "p2:paper:2603.00131", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ben-hagag", "dst": "p2:paper:2603.00131", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-mulet", "dst": "p2:paper:2603.00131", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.01295", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zarreen-reza", "dst": "p2:paper:2510.01295", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.05980", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:bin-xuan", "dst": "p2:paper:2603.05980", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruo-ai", "dst": "p2:paper:2603.05980", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hakyeon-lee", "dst": "p2:paper:2603.05980", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.15790", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:akhil-sharma", "dst": "p2:paper:2512.15790", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaikh-yaser-arafat", "dst": "p2:paper:2512.15790", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jai-kumar-sharma", "dst": "p2:paper:2512.15790", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ken-huang", "dst": "p2:paper:2512.15790", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.06567", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yangyang-yu", "dst": "p2:paper:2407.06567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiyuan-yao", "dst": "p2:paper:2407.06567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haohang-li", "dst": "p2:paper:2407.06567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiyang-deng", "dst": "p2:paper:2407.06567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yupeng-cao", "dst": "p2:paper:2407.06567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhi-chen", "dst": "p2:paper:2407.06567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jordan-w-suchow", "dst": "p2:paper:2407.06567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rong-liu", "dst": "p2:paper:2407.06567", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.15968", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:rushil-thareja", "dst": "p2:paper:2603.15968", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gautam-gupta", "dst": "p2:paper:2603.15968", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francesco-pinto", "dst": "p2:paper:2603.15968", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nils-lukas", "dst": "p2:paper:2603.15968", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.04652", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shuo-liu", "dst": "p2:paper:2508.04652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianle-chen", "dst": "p2:paper:2508.04652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zeyu-liang", "dst": "p2:paper:2508.04652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xueguang-lyu", "dst": "p2:paper:2508.04652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-amato", "dst": "p2:paper:2508.04652", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.08501", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ummar-abbas", "dst": "p2:paper:2603.08501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mourad-ouzzani", "dst": "p2:paper:2603.08501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohamed-y-eltabakh", "dst": "p2:paper:2603.08501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:omar-sinan", "dst": "p2:paper:2603.08501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gagan-bhatia", "dst": "p2:paper:2603.08501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hamdy-mubarak", "dst": "p2:paper:2603.08501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:majd-hawasly", "dst": "p2:paper:2603.08501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohammed-qusay-hashim", "dst": "p2:paper:2603.08501", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.27409", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:igor-itkin", "dst": "p2:paper:2606.27409", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.01019", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:imran-mirza", "dst": "p2:paper:2507.01019", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cole-huang", "dst": "p2:paper:2507.01019", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ishwara-vasista", "dst": "p2:paper:2507.01019", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rohan-patil", "dst": "p2:paper:2507.01019", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:asli-akalin", "dst": "p2:paper:2507.01019", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sean-o-brien", "dst": "p2:paper:2507.01019", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kevin-zhu", "dst": "p2:paper:2507.01019", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.05269", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ishan-kavathekar", "dst": "p2:paper:2511.05269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hemang-jain", "dst": "p2:paper:2511.05269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ameya-rathod", "dst": "p2:paper:2511.05269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ponnurangam-kumaraguru", "dst": "p2:paper:2511.05269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tanuja-ganu", "dst": "p2:paper:2511.05269", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.00132", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:peiwen-xing", "dst": "p2:paper:2509.00132", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aske-plaat", "dst": "p2:paper:2509.00132", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:niki-van-stein", "dst": "p2:paper:2509.00132", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.07283", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:donghyun-lee", "dst": "p2:paper:2410.07283", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mo-tiwari", "dst": "p2:paper:2410.07283", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.24239", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sana-ebrahimi", "dst": "p2:paper:2505.24239", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohsen-dehghankar", "dst": "p2:paper:2505.24239", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abolfazl-asudeh", "dst": "p2:paper:2505.24239", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.14314", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yang-zhang", "dst": "p2:paper:2405.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shixin-yang", "dst": "p2:paper:2405.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chenjia-bai", "dst": "p2:paper:2405.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fei-wu", "dst": "p2:paper:2405.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiu-li", "dst": "p2:paper:2405.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhen-wang", "dst": "p2:paper:2405.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuelong-li", "dst": "p2:paper:2405.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.25850", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kevin-qiu", "dst": "p2:paper:2510.25850", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marek-cygan", "dst": "p2:paper:2510.25850", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.01928", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sumeet-ramesh-motwani", "dst": "p2:paper:2412.01928", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chandler-smith", "dst": "p2:paper:2412.01928", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rocktim-jyoti-das", "dst": "p2:paper:2412.01928", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rafael-rafailov", "dst": "p2:paper:2412.01928", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ivan-laptev", "dst": "p2:paper:2412.01928", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:philip-h-s-torr", "dst": "p2:paper:2412.01928", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fabio-pizzati", "dst": "p2:paper:2412.01928", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ronald-clark", "dst": "p2:paper:2412.01928", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.08268", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiaolin-sun", "dst": "p2:paper:2605.08268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zixuan-liu", "dst": "p2:paper:2605.08268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yibin-hu", "dst": "p2:paper:2605.08268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zizhan-zheng", "dst": "p2:paper:2605.08268", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.15755", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:philip-drammeh", "dst": "p2:paper:2511.15755", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.13707", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:fan-zhang", "dst": "p2:paper:2606.13707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vireo-zhang", "dst": "p2:paper:2606.13707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shengju-qian", "dst": "p2:paper:2606.13707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoxuan-li", "dst": "p2:paper:2606.13707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-wu", "dst": "p2:paper:2606.13707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinyang-wu", "dst": "p2:paper:2606.13707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:donghao-zhou", "dst": "p2:paper:2606.13707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhihong-zhu", "dst": "p2:paper:2606.13707", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.09543", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:arihant-tripathy", "dst": "p2:paper:2512.09543", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ch-pavan-harshit", "dst": "p2:paper:2512.09543", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:karthik-vaidhyanathan", "dst": "p2:paper:2512.09543", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.03312", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiayi-chen", "dst": "p2:paper:2605.03312", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yingcong-li", "dst": "p2:paper:2605.03312", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guiling-wang", "dst": "p2:paper:2605.03312", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.25746", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haoran-li", "dst": "p2:paper:2605.25746", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shulun-chen", "dst": "p2:paper:2605.25746", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaoyuan-sun", "dst": "p2:paper:2605.25746", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanchen-wang", "dst": "p2:paper:2605.25746", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.13598", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:king-yeung-tsang", "dst": "p2:paper:2606.13598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zihao-zhao", "dst": "p2:paper:2606.13598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vishal-venkataramani", "dst": "p2:paper:2606.13598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haizhou-shi", "dst": "p2:paper:2606.13598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zixuan-ke", "dst": "p2:paper:2606.13598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:semih-yavuz", "dst": "p2:paper:2606.13598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shafiq-joty", "dst": "p2:paper:2606.13598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-wang", "dst": "p2:paper:2606.13598", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.22823", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ivan-dobrovolskyi", "dst": "p2:paper:2603.22823", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.00326", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hassen-dhrif", "dst": "p2:paper:2510.00326", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.19896", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:boyan-liu", "dst": "p2:paper:2603.19896", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gongming-zhao", "dst": "p2:paper:2603.19896", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongli-xu", "dst": "p2:paper:2603.19896", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.02801", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chenchen-zhang", "dst": "p2:paper:2605.02801", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.01416", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:rahul-suresh-babu", "dst": "p2:paper:2606.01416", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:adarsh-agrawal", "dst": "p2:paper:2606.01416", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.21822", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zitong-yu", "dst": "p2:paper:2601.21822", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:boquan-sun", "dst": "p2:paper:2601.21822", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-li", "dst": "p2:paper:2601.21822", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zheyan-qu", "dst": "p2:paper:2601.21822", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xing-zhang", "dst": "p2:paper:2601.21822", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.17964", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:antony-seabra", "dst": "p2:paper:2412.17964", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:claudio-cavalcante", "dst": "p2:paper:2412.17964", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joao-nepomuceno", "dst": "p2:paper:2412.17964", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lucas-lago", "dst": "p2:paper:2412.17964", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nicolaas-ruberg", "dst": "p2:paper:2412.17964", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sergio-lifschitz", "dst": "p2:paper:2412.17964", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.14483", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xudong-chen", "dst": "p2:paper:2605.14483", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yixin-liu", "dst": "p2:paper:2605.14483", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hua-wei", "dst": "p2:paper:2605.14483", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaize-ding", "dst": "p2:paper:2605.14483", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.16873", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:geunbin-yu", "dst": "p2:paper:2602.16873", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.19591", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yufan-dang", "dst": "p2:paper:2505.19591", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-qian", "dst": "p2:paper:2505.19591", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xueheng-luo", "dst": "p2:paper:2505.19591", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingru-fan", "dst": "p2:paper:2505.19591", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zihao-xie", "dst": "p2:paper:2505.19591", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruijie-shi", "dst": "p2:paper:2505.19591", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weize-chen", "dst": "p2:paper:2505.19591", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cheng-yang", "dst": "p2:paper:2505.19591", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.31174", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kaiwen-xiong", "dst": "p2:paper:2606.31174", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haonian-ji", "dst": "p2:paper:2606.31174", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shi-qiu", "dst": "p2:paper:2606.31174", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zeyu-zheng", "dst": "p2:paper:2606.31174", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cihang-xie", "dst": "p2:paper:2606.31174", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyu-ye", "dst": "p2:paper:2606.31174", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huaxiu-yao", "dst": "p2:paper:2606.31174", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.24354", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qianqian-zhang", "dst": "p2:paper:2505.24354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiajia-liao", "dst": "p2:paper:2505.24354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:heting-ying", "dst": "p2:paper:2505.24354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yibo-ma", "dst": "p2:paper:2505.24354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haozhan-shen", "dst": "p2:paper:2505.24354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingcheng-li", "dst": "p2:paper:2505.24354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peng-liu", "dst": "p2:paper:2505.24354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-zhang", "dst": "p2:paper:2505.24354", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.21255", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jean-philippe-garnier", "dst": "p2:paper:2602.21255", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.23537", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aaron-xuxiang-tian", "dst": "p2:paper:2509.23537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruofan-zhang", "dst": "p2:paper:2509.23537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiayao-tang", "dst": "p2:paper:2509.23537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:young-min-cho", "dst": "p2:paper:2509.23537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xueqian-li", "dst": "p2:paper:2509.23537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qiang-yi", "dst": "p2:paper:2509.23537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ji-wang", "dst": "p2:paper:2509.23537", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhunping-zhang", "dst": "p2:paper:2509.23537", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.13721", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:abdulhalim-dandoush", "dst": "p2:paper:2403.13721", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:viswanath-kumarskandpriya", "dst": "p2:paper:2403.13721", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mueen-uddin", "dst": "p2:paper:2403.13721", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:usman-khalil", "dst": "p2:paper:2403.13721", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.12129", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:swanand-rao", "dst": "p2:paper:2604.12129", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kiran-kashalkar", "dst": "p2:paper:2604.12129", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:parvathi-somashekar", "dst": "p2:paper:2604.12129", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:priya-krishnan", "dst": "p2:paper:2604.12129", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.15055", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:naveen-kumar-krishnan", "dst": "p2:paper:2602.15055", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.08979", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhuoyun-du", "dst": "p2:paper:2406.08979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-qian", "dst": "p2:paper:2406.08979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-liu", "dst": "p2:paper:2406.08979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zihao-xie", "dst": "p2:paper:2406.08979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yifei-wang", "dst": "p2:paper:2406.08979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rennai-qiu", "dst": "p2:paper:2406.08979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yufan-dang", "dst": "p2:paper:2406.08979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weize-chen", "dst": "p2:paper:2406.08979", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.13227", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:eranga-bandara", "dst": "p2:paper:2602.13227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ross-gore", "dst": "p2:paper:2602.13227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sachin-shetty", "dst": "p2:paper:2602.13227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ravi-mukkamala", "dst": "p2:paper:2602.13227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tharaka-hewa", "dst": "p2:paper:2602.13227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abdul-rahman", "dst": "p2:paper:2602.13227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xueping-liang", "dst": "p2:paper:2602.13227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:safdar-h-bouk", "dst": "p2:paper:2602.13227", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.01599", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhaoyan-sun", "dst": "p2:paper:2507.01599", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiayi-wang", "dst": "p2:paper:2507.01599", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyang-zhao", "dst": "p2:paper:2507.01599", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiachi-wang", "dst": "p2:paper:2507.01599", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guoliang-li", "dst": "p2:paper:2507.01599", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.03005", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yichao-feng", "dst": "p2:paper:2603.03005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoran-luo", "dst": "p2:paper:2603.03005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenghong-lin", "dst": "p2:paper:2603.03005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiqun-sun", "dst": "p2:paper:2603.03005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pengfei-wei", "dst": "p2:paper:2603.03005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lawrence-b-hsieh", "dst": "p2:paper:2603.03005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anh-tuan-luu", "dst": "p2:paper:2603.03005", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.21784", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:anubhav-shrimal", "dst": "p2:paper:2410.21784", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stanley-kanagaraj", "dst": "p2:paper:2410.21784", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kriti-biswas", "dst": "p2:paper:2410.21784", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:swarnalatha-raghuraman", "dst": "p2:paper:2410.21784", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anish-nediyanchath", "dst": "p2:paper:2410.21784", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-zhang", "dst": "p2:paper:2410.21784", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:promod-yenigalla", "dst": "p2:paper:2410.21784", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.00922", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:md-mainul-abrar", "dst": "p2:paper:2606.00922", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xun-jia", "dst": "p2:paper:2606.00922", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yujie-chi", "dst": "p2:paper:2606.00922", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.02716", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xu-huang", "dst": "p2:paper:2402.02716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weiwen-liu", "dst": "p2:paper:2402.02716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaolong-chen", "dst": "p2:paper:2402.02716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xingmei-wang", "dst": "p2:paper:2402.02716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-wang", "dst": "p2:paper:2402.02716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:defu-lian", "dst": "p2:paper:2402.02716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yasheng-wang", "dst": "p2:paper:2402.02716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruiming-tang", "dst": "p2:paper:2402.02716", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.12740", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shuo-yang", "dst": "p2:paper:2603.12740", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:soyeon-caren-han", "dst": "p2:paper:2603.12740", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yihao-ding", "dst": "p2:paper:2603.12740", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuhe-wang", "dst": "p2:paper:2603.12740", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eduard-hoy", "dst": "p2:paper:2603.12740", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.12501", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:edward-y-chang", "dst": "p2:paper:2505.12501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:longling-geng", "dst": "p2:paper:2505.12501", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.05227", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:gonzalo-gonzalez-pumariega", "dst": "p2:paper:2502.05227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:leong-su-yean", "dst": "p2:paper:2502.05227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:neha-sunkara", "dst": "p2:paper:2502.05227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sanjiban-choudhury", "dst": "p2:paper:2502.05227", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.10507", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:juncheng-diao", "dst": "p2:paper:2606.10507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhicong-lu", "dst": "p2:paper:2606.10507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peiguang-li", "dst": "p2:paper:2606.10507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongwei-zhou", "dst": "p2:paper:2606.10507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:changyuan-tian", "dst": "p2:paper:2606.10507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qingbin-li", "dst": "p2:paper:2606.10507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rongxiang-weng", "dst": "p2:paper:2606.10507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingang-wang", "dst": "p2:paper:2606.10507", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.09474", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiayuan-huang", "dst": "p2:paper:2503.09474", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:runlong-he", "dst": "p2:paper:2503.09474", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:danyal-zaman-khan", "dst": "p2:paper:2503.09474", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:evangelos-b-mazomenos", "dst": "p2:paper:2503.09474", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:danail-stoyanov", "dst": "p2:paper:2503.09474", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hani-marcus", "dst": "p2:paper:2503.09474", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:linzhe-jiang", "dst": "p2:paper:2503.09474", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matthew-j-clarkson", "dst": "p2:paper:2503.09474", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.01390", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:gaole-he", "dst": "p2:paper:2502.01390", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gianluca-demartini", "dst": "p2:paper:2502.01390", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ujwal-gadiraju", "dst": "p2:paper:2502.01390", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.17833", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhenlan-ji", "dst": "p2:paper:2404.17833", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daoyuan-wu", "dst": "p2:paper:2404.17833", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pingchuan-ma", "dst": "p2:paper:2404.17833", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zongjie-li", "dst": "p2:paper:2404.17833", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuai-wang", "dst": "p2:paper:2404.17833", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.30639", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xuan-zhang", "dst": "p2:paper:2606.30639", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenxuan-zhang", "dst": "p2:paper:2606.30639", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:see-kiong-ng", "dst": "p2:paper:2606.30639", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-deng", "dst": "p2:paper:2606.30639", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.19598", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhiwei-li", "dst": "p2:paper:2508.19598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-hu", "dst": "p2:paper:2508.19598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenqing-wang", "dst": "p2:paper:2508.19598", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.02424", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jae-woo-choi", "dst": "p2:paper:2511.02424", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hyungmin-kim", "dst": "p2:paper:2511.02424", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hyobin-ong", "dst": "p2:paper:2511.02424", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:youngwoo-yoon", "dst": "p2:paper:2511.02424", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:minsu-jang", "dst": "p2:paper:2511.02424", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dohyung-kim", "dst": "p2:paper:2511.02424", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jaehong-kim", "dst": "p2:paper:2511.02424", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.22718", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tianming-liu", "dst": "p2:paper:2503.22718", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jirong-yang", "dst": "p2:paper:2503.22718", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yafeng-yin", "dst": "p2:paper:2503.22718", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.04874", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haoyu-sun", "dst": "p2:paper:2606.04874", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenxuan-wang", "dst": "p2:paper:2606.04874", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingyang-song", "dst": "p2:paper:2606.04874", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jujie-he", "dst": "p2:paper:2606.04874", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weinan-zhang", "dst": "p2:paper:2606.04874", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-liu", "dst": "p2:paper:2606.04874", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-yang", "dst": "p2:paper:2606.04874", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-cheng", "dst": "p2:paper:2606.04874", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.11143", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lingzhi-wang", "dst": "p2:paper:2512.11143", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyi-shi", "dst": "p2:paper:2512.11143", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ziyu-li", "dst": "p2:paper:2512.11143", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-jiang", "dst": "p2:paper:2512.11143", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shiyu-tan", "dst": "p2:paper:2512.11143", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuhao-jiang", "dst": "p2:paper:2512.11143", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junjie-cheng", "dst": "p2:paper:2512.11143", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenyuan-chen", "dst": "p2:paper:2512.11143", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.13050", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:daniel-chin", "dst": "p2:paper:2405.13050", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxuan-wang", "dst": "p2:paper:2405.13050", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gus-xia", "dst": "p2:paper:2405.13050", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.04168", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qingbin-zeng", "dst": "p2:paper:2408.04168", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qinglong-yang", "dst": "p2:paper:2408.04168", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shunan-dong", "dst": "p2:paper:2408.04168", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:heming-du", "dst": "p2:paper:2408.04168", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liang-zheng", "dst": "p2:paper:2408.04168", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fengli-xu", "dst": "p2:paper:2408.04168", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-li", "dst": "p2:paper:2408.04168", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.03610", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tomoyuki-kagaya", "dst": "p2:paper:2402.03610", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thong-jing-yuan", "dst": "p2:paper:2402.03610", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxuan-lou", "dst": "p2:paper:2402.03610", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jayashree-karlekar", "dst": "p2:paper:2402.03610", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sugiri-pranata", "dst": "p2:paper:2402.03610", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:akira-kinose", "dst": "p2:paper:2402.03610", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:koki-oguri", "dst": "p2:paper:2402.03610", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:felix-wick", "dst": "p2:paper:2402.03610", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.09171", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:samuel-holt", "dst": "p2:paper:2506.09171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:max-ruiz-luyten", "dst": "p2:paper:2506.09171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thomas-pouplin", "dst": "p2:paper:2506.09171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mihaela-van-der-schaar", "dst": "p2:paper:2506.09171", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.21033", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:gautier-dagan", "dst": "p2:paper:2412.21033", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:frank-keller", "dst": "p2:paper:2412.21033", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alex-lascarides", "dst": "p2:paper:2412.21033", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.03581", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:davide-paglieri", "dst": "p2:paper:2509.03581", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bart-omiej-cupia", "dst": "p2:paper:2509.03581", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jonathan-cook", "dst": "p2:paper:2509.03581", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ulyana-piterbarg", "dst": "p2:paper:2509.03581", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jens-tuyls", "dst": "p2:paper:2509.03581", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:edward-grefenstette", "dst": "p2:paper:2509.03581", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jakob-nicolaus-foerster", "dst": "p2:paper:2509.03581", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jack-parker-holder", "dst": "p2:paper:2509.03581", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.06153", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yu-shang", "dst": "p2:paper:2410.06153", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-li", "dst": "p2:paper:2410.06153", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:keyu-zhao", "dst": "p2:paper:2410.06153", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:likai-ma", "dst": "p2:paper:2410.06153", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiahe-liu", "dst": "p2:paper:2410.06153", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fengli-xu", "dst": "p2:paper:2410.06153", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-li", "dst": "p2:paper:2410.06153", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.05651", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuheng-zhao", "dst": "p2:paper:2411.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junjie-wang", "dst": "p2:paper:2411.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:linbin-xiang", "dst": "p2:paper:2411.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaowen-zhang", "dst": "p2:paper:2411.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zifei-guo", "dst": "p2:paper:2411.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cagatay-turkay", "dst": "p2:paper:2411.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-zhang", "dst": "p2:paper:2411.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:siming-chen", "dst": "p2:paper:2411.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.21868", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuxuan-li", "dst": "p2:paper:2509.21868", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sauvik-das", "dst": "p2:paper:2509.21868", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hirokazu-shirado", "dst": "p2:paper:2509.21868", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.14635", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jo-o-vitor-de-carvalho-silva", "dst": "p2:paper:2508.14635", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:douglas-g-macharet", "dst": "p2:paper:2508.14635", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.06318", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yanan-chen", "dst": "p2:paper:2408.06318", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ali-pesaranghader", "dst": "p2:paper:2408.06318", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tanmana-sadhu", "dst": "p2:paper:2408.06318", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dong-hoon-yi", "dst": "p2:paper:2408.06318", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.06957", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shirin-sohrabi", "dst": "p2:paper:2605.06957", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haritha-ananthakrishnan", "dst": "p2:paper:2605.06957", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:harsha-kokel", "dst": "p2:paper:2605.06957", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kavitha-srinivas", "dst": "p2:paper:2605.06957", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-katz", "dst": "p2:paper:2605.06957", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.17767", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:weiwen-liu", "dst": "p2:paper:2505.17767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiarui-qin", "dst": "p2:paper:2505.17767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xu-huang", "dst": "p2:paper:2505.17767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xingshan-zeng", "dst": "p2:paper:2505.17767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yunjia-xi", "dst": "p2:paper:2505.17767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianghao-lin", "dst": "p2:paper:2505.17767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chuhan-wu", "dst": "p2:paper:2505.17767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yasheng-wang", "dst": "p2:paper:2505.17767", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.03111", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zichuan-li", "dst": "p2:paper:2504.03111", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jian-cui", "dst": "p2:paper:2504.03111", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaojing-liao", "dst": "p2:paper:2504.03111", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luyi-xing", "dst": "p2:paper:2504.03111", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.09970", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mrinal-rawat", "dst": "p2:paper:2505.09970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ambuje-gupta", "dst": "p2:paper:2505.09970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rushil-goomer", "dst": "p2:paper:2505.09970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alessandro-di-bari", "dst": "p2:paper:2505.09970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:neha-gupta", "dst": "p2:paper:2505.09970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:roberto-pieraccini", "dst": "p2:paper:2505.09970", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.23590", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiazheng-kang", "dst": "p2:paper:2605.23590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bowen-zhang", "dst": "p2:paper:2605.23590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zixin-song", "dst": "p2:paper:2605.23590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiangwang-chen", "dst": "p2:paper:2605.23590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiao-yang", "dst": "p2:paper:2605.23590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:da-zhu", "dst": "p2:paper:2605.23590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guanjun-jiang", "dst": "p2:paper:2605.23590", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.01262", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:michelle-elizabeth", "dst": "p2:paper:2412.01262", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:morgan-veyret", "dst": "p2:paper:2412.01262", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:miguel-couceiro", "dst": "p2:paper:2412.01262", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ondrej-dusek", "dst": "p2:paper:2412.01262", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lina-m-rojas-barahona", "dst": "p2:paper:2412.01262", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2312.10003", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:renat-aksitov", "dst": "p2:paper:2312.10003", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sobhan-miryoosefi", "dst": "p2:paper:2312.10003", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zonglin-li", "dst": "p2:paper:2312.10003", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daliang-li", "dst": "p2:paper:2312.10003", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sheila-babayan", "dst": "p2:paper:2312.10003", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kavya-kopparapu", "dst": "p2:paper:2312.10003", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zachary-fisher", "dst": "p2:paper:2312.10003", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruiqi-guo", "dst": "p2:paper:2312.10003", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.07236", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:oleg-sautenkov", "dst": "p2:paper:2505.07236", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yasheerah-yaqoot", "dst": "p2:paper:2505.07236", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:muhammad-ahsan-mustafa", "dst": "p2:paper:2505.07236", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:faryal-batool", "dst": "p2:paper:2505.07236", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jeffrin-sam", "dst": "p2:paper:2505.07236", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:artem-lykov", "dst": "p2:paper:2505.07236", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chih-yung-wen", "dst": "p2:paper:2505.07236", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dzmitry-tsetserukou", "dst": "p2:paper:2505.07236", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.18000", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:seyed-morteza-ahmadian", "dst": "p2:paper:2606.18000", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:paolo-monti", "dst": "p2:paper:2606.18000", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:carlos-natalino", "dst": "p2:paper:2606.18000", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.11068", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:iman-peivaste", "dst": "p2:paper:2603.11068", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:salim-belouettar", "dst": "p2:paper:2603.11068", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1906.11932", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hussam-habib", "dst": "p2:paper:1906.11932", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:maaz-bin-musa", "dst": "p2:paper:1906.11932", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fareed-zaffar", "dst": "p2:paper:1906.11932", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rishab-nithyanand", "dst": "p2:paper:1906.11932", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.01413", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiaofan-zhou", "dst": "p2:paper:2604.01413", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huy-nguyen", "dst": "p2:paper:2604.01413", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bo-yu", "dst": "p2:paper:2604.01413", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chenxi-liu", "dst": "p2:paper:2604.01413", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-cheng", "dst": "p2:paper:2604.01413", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.00927", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:vardhan-dongre", "dst": "p2:paper:2411.00927", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaocheng-yang", "dst": "p2:paper:2411.00927", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:emre-can-acikgoz", "dst": "p2:paper:2411.00927", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:suvodip-dey", "dst": "p2:paper:2411.00927", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gokhan-tur", "dst": "p2:paper:2411.00927", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dilek-hakkani-t-r", "dst": "p2:paper:2411.00927", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.12036", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:elvis-hsieh", "dst": "p2:paper:2408.12036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:preston-fu", "dst": "p2:paper:2408.12036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jonathan-chen", "dst": "p2:paper:2408.12036", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.07773", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chen-zhang", "dst": "p2:paper:2602.07773", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kuicai-dong", "dst": "p2:paper:2602.07773", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dexun-li", "dst": "p2:paper:2602.07773", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenjun-li", "dst": "p2:paper:2602.07773", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qu-yang", "dst": "p2:paper:2602.07773", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-han", "dst": "p2:paper:2602.07773", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-liu", "dst": "p2:paper:2602.07773", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.17794", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:bui-the-trung", "dst": "p2:paper:2604.17794", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:do-minh-duc", "dst": "p2:paper:2604.17794", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nguyen-van-vinh", "dst": "p2:paper:2604.17794", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bui-nguyen-quoc-trinh", "dst": "p2:paper:2604.17794", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.13382", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ayoub-ben-chaliah", "dst": "p2:paper:2508.13382", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hela-dellagi", "dst": "p2:paper:2508.13382", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.02025", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:prachi-jadhav", "dst": "p2:paper:2506.02025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongwei-jin", "dst": "p2:paper:2506.02025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ewa-deelman", "dst": "p2:paper:2506.02025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:prasanna-balaprakash", "dst": "p2:paper:2506.02025", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2312.07671", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ali-ghadami", "dst": "p2:paper:2312.07671", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohammadreza-taghimohammadi", "dst": "p2:paper:2312.07671", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohammad-mohammadzadeh", "dst": "p2:paper:2312.07671", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohammad-hosseinipour", "dst": "p2:paper:2312.07671", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alireza-taheri", "dst": "p2:paper:2312.07671", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.10658", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mamadou-seck", "dst": "p2:paper:2604.10658", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.07035", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiahao-zhao", "dst": "p2:paper:2602.07035", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaoxuan-xu", "dst": "p2:paper:2602.07035", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhongxiang-sun", "dst": "p2:paper:2602.07035", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fengqi-zhu", "dst": "p2:paper:2602.07035", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingyang-ou", "dst": "p2:paper:2602.07035", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuling-shi", "dst": "p2:paper:2602.07035", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiao-zhang", "dst": "p2:paper:2602.07035", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.23415", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:alexander-murphy", "dst": "p2:paper:2503.23415", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohd-sanad-zaki-rizvi", "dst": "p2:paper:2503.23415", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aden-haussmann", "dst": "p2:paper:2503.23415", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ping-nie", "dst": "p2:paper:2503.23415", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guifu-liu", "dst": "p2:paper:2503.23415", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aryo-pradipta-gema", "dst": "p2:paper:2503.23415", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pasquale-minervini", "dst": "p2:paper:2503.23415", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.11534", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dayuan-fu", "dst": "p2:paper:2402.11534", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianzhao-huang", "dst": "p2:paper:2402.11534", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:siyuan-lu", "dst": "p2:paper:2402.11534", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guanting-dong", "dst": "p2:paper:2402.11534", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yejie-wang", "dst": "p2:paper:2402.11534", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:keqing-he", "dst": "p2:paper:2402.11534", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weiran-xu", "dst": "p2:paper:2402.11534", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.08098", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sabrina-patania", "dst": "p2:paper:2511.08098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luca-annese", "dst": "p2:paper:2511.08098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anita-pellegrini", "dst": "p2:paper:2511.08098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:silvia-serino", "dst": "p2:paper:2511.08098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anna-lambiase", "dst": "p2:paper:2511.08098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luca-pallonetto", "dst": "p2:paper:2511.08098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:silvia-rossi", "dst": "p2:paper:2511.08098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:simone-colombani", "dst": "p2:paper:2511.08098", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.06825", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chenpeng-wang", "dst": "p2:paper:2510.06825", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaojie-cheng", "dst": "p2:paper:2510.06825", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chunye-wang", "dst": "p2:paper:2510.06825", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:linfeng-yang", "dst": "p2:paper:2510.06825", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-zhang", "dst": "p2:paper:2510.06825", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.01171", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:stefan-szeider", "dst": "p2:paper:2602.01171", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2312.04511", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sehoon-kim", "dst": "p2:paper:2312.04511", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:suhong-moon", "dst": "p2:paper:2312.04511", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ryan-tabrizi", "dst": "p2:paper:2312.04511", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nicholas-lee", "dst": "p2:paper:2312.04511", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-w-mahoney", "dst": "p2:paper:2312.04511", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kurt-keutzer", "dst": "p2:paper:2312.04511", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:amir-gholami", "dst": "p2:paper:2312.04511", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2401.02777", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:na-liu", "dst": "p2:paper:2401.02777", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liangyu-chen", "dst": "p2:paper:2401.02777", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoyu-tian", "dst": "p2:paper:2401.02777", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-zou", "dst": "p2:paper:2401.02777", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaijiang-chen", "dst": "p2:paper:2401.02777", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ming-cui", "dst": "p2:paper:2401.02777", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.23422", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tobias-lindenbauer", "dst": "p2:paper:2505.23422", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:georg-groh", "dst": "p2:paper:2505.23422", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hinrich-sch-tze", "dst": "p2:paper:2505.23422", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.17734", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hongjun-liu", "dst": "p2:paper:2605.17734", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yifei-ming", "dst": "p2:paper:2605.17734", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shafiq-joty", "dst": "p2:paper:2605.17734", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-zhao", "dst": "p2:paper:2605.17734", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.11211", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wenxuan-wang", "dst": "p2:paper:2502.11211", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zizhan-ma", "dst": "p2:paper:2502.11211", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zheng-wang", "dst": "p2:paper:2502.11211", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chenghan-wu", "dst": "p2:paper:2502.11211", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaming-ji", "dst": "p2:paper:2502.11211", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenting-chen", "dst": "p2:paper:2502.11211", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiang-li", "dst": "p2:paper:2502.11211", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yixuan-yuan", "dst": "p2:paper:2502.11211", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.18970", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xixun-lin", "dst": "p2:paper:2509.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yucheng-ning", "dst": "p2:paper:2509.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingwen-zhang", "dst": "p2:paper:2509.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yan-dong", "dst": "p2:paper:2509.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yilong-liu", "dst": "p2:paper:2509.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongxuan-wu", "dst": "p2:paper:2509.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaohua-qi", "dst": "p2:paper:2509.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nan-sun", "dst": "p2:paper:2509.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.02479", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haolin-jin", "dst": "p2:paper:2408.02479", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:linghan-huang", "dst": "p2:paper:2408.02479", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haipeng-cai", "dst": "p2:paper:2408.02479", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-yan", "dst": "p2:paper:2408.02479", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bo-li", "dst": "p2:paper:2408.02479", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huaming-chen", "dst": "p2:paper:2408.02479", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.16416", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:asaf-yehudai", "dst": "p2:paper:2503.16416", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lilach-eden", "dst": "p2:paper:2503.16416", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alan-li", "dst": "p2:paper:2503.16416", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guy-uziel", "dst": "p2:paper:2503.16416", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yilun-zhao", "dst": "p2:paper:2503.16416", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:roy-bar-haim", "dst": "p2:paper:2503.16416", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arman-cohan", "dst": "p2:paper:2503.16416", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michal-shmueli-scheuer", "dst": "p2:paper:2503.16416", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.22458", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shengyue-guan", "dst": "p2:paper:2503.22458", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jindong-wang", "dst": "p2:paper:2503.22458", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiang-bian", "dst": "p2:paper:2503.22458", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bin-zhu", "dst": "p2:paper:2503.22458", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jian-guang-lou", "dst": "p2:paper:2503.22458", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoyi-xiong", "dst": "p2:paper:2503.22458", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.00083", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yihong-dong", "dst": "p2:paper:2508.00083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xue-jiang", "dst": "p2:paper:2508.00083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaru-qian", "dst": "p2:paper:2508.00083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tian-wang", "dst": "p2:paper:2508.00083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kechi-zhang", "dst": "p2:paper:2508.00083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhi-jin", "dst": "p2:paper:2508.00083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ge-li", "dst": "p2:paper:2508.00083", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.09523", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuyou-gan", "dst": "p2:paper:2411.09523", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-yang", "dst": "p2:paper:2411.09523", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhe-ma", "dst": "p2:paper:2411.09523", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ping-he", "dst": "p2:paper:2411.09523", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rui-zeng", "dst": "p2:paper:2411.09523", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiming-wang", "dst": "p2:paper:2411.09523", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qingming-li", "dst": "p2:paper:2411.09523", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chunyi-zhou", "dst": "p2:paper:2411.09523", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.00675", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yiming-du", "dst": "p2:paper:2505.00675", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenyu-huang", "dst": "p2:paper:2505.00675", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:danna-zheng", "dst": "p2:paper:2505.00675", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhaowei-wang", "dst": "p2:paper:2505.00675", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sebastien-montella", "dst": "p2:paper:2505.00675", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mirella-lapata", "dst": "p2:paper:2505.00675", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kam-fai-wong", "dst": "p2:paper:2505.00675", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jeff-z-pan", "dst": "p2:paper:2505.00675", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.13305", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:rangeet-pan", "dst": "p2:paper:2511.13305", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:raju-pavuluri", "dst": "p2:paper:2511.13305", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruikai-huang", "dst": "p2:paper:2511.13305", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rahul-krishna", "dst": "p2:paper:2511.13305", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tyler-stennett", "dst": "p2:paper:2511.13305", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alessandro-orso", "dst": "p2:paper:2511.13305", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:saurabh-sinha", "dst": "p2:paper:2511.13305", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.17692", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:bingxi-zhao", "dst": "p2:paper:2508.17692", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lin-geng-foo", "dst": "p2:paper:2508.17692", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ping-hu", "dst": "p2:paper:2508.17692", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christian-theobalt", "dst": "p2:paper:2508.17692", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hossein-rahmani", "dst": "p2:paper:2508.17692", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-liu", "dst": "p2:paper:2508.17692", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.17232", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yun-shiuan-chuang", "dst": "p2:paper:2406.17232", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:krirk-nirunwiroj", "dst": "p2:paper:2406.17232", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zach-studdiford", "dst": "p2:paper:2406.17232", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:agam-goyal", "dst": "p2:paper:2406.17232", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vincent-v-frigo", "dst": "p2:paper:2406.17232", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sijia-yang", "dst": "p2:paper:2406.17232", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dhavan-shah", "dst": "p2:paper:2406.17232", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junjie-hu", "dst": "p2:paper:2406.17232", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.03758", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiarui-ji", "dst": "p2:paper:2511.03758", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:runlin-lei", "dst": "p2:paper:2511.03758", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuchen-pan", "dst": "p2:paper:2511.03758", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhewei-wei", "dst": "p2:paper:2511.03758", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-sun", "dst": "p2:paper:2511.03758", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yankai-lin", "dst": "p2:paper:2511.03758", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xu-chen", "dst": "p2:paper:2511.03758", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongzheng-yang", "dst": "p2:paper:2511.03758", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.02977", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:junwei-liu", "dst": "p2:paper:2409.02977", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaixin-wang", "dst": "p2:paper:2409.02977", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yixuan-chen", "dst": "p2:paper:2409.02977", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xin-peng", "dst": "p2:paper:2409.02977", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenpeng-chen", "dst": "p2:paper:2409.02977", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lingming-zhang", "dst": "p2:paper:2409.02977", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiling-lou", "dst": "p2:paper:2409.02977", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.04813", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shubham-vatsal", "dst": "p2:paper:2602.04813", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:harsh-dubey", "dst": "p2:paper:2602.04813", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aditi-singh", "dst": "p2:paper:2602.04813", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.05804", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xinzhe-li", "dst": "p2:paper:2406.05804", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.09030", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yanlin-wang", "dst": "p2:paper:2409.09030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wanjun-zhong", "dst": "p2:paper:2409.09030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanxian-huang", "dst": "p2:paper:2409.09030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ensheng-shi", "dst": "p2:paper:2409.09030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:min-yang", "dst": "p2:paper:2409.09030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiachi-chen", "dst": "p2:paper:2409.09030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hui-li", "dst": "p2:paper:2409.09030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuchi-ma", "dst": "p2:paper:2409.09030", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.02744", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ke-chen", "dst": "p2:paper:2508.02744", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peiran-wang", "dst": "p2:paper:2508.02744", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yaoning-yu", "dst": "p2:paper:2508.02744", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xianyang-zhan", "dst": "p2:paper:2508.02744", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haohan-wang", "dst": "p2:paper:2508.02744", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.16330", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:minxing-zhang", "dst": "p2:paper:2509.16330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-yang", "dst": "p2:paper:2509.16330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:roy-xie", "dst": "p2:paper:2509.16330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bhuwan-dhingra", "dst": "p2:paper:2509.16330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuyan-zhou", "dst": "p2:paper:2509.16330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jian-pei", "dst": "p2:paper:2509.16330", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.12786", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:minrui-xu", "dst": "p2:paper:2505.12786", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiani-fan", "dst": "p2:paper:2505.12786", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyu-huang", "dst": "p2:paper:2505.12786", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:conghao-zhou", "dst": "p2:paper:2505.12786", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiawen-kang", "dst": "p2:paper:2505.12786", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dusit-niyato", "dst": "p2:paper:2505.12786", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shiwen-mao", "dst": "p2:paper:2505.12786", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhu-han", "dst": "p2:paper:2505.12786", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.00629", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lizhi-lin", "dst": "p2:paper:2404.00629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:honglin-mu", "dst": "p2:paper:2404.00629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zenan-zhai", "dst": "p2:paper:2404.00629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:minghan-wang", "dst": "p2:paper:2404.00629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxia-wang", "dst": "p2:paper:2404.00629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:renxi-wang", "dst": "p2:paper:2404.00629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junjie-gao", "dst": "p2:paper:2404.00629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yixuan-zhang", "dst": "p2:paper:2404.00629", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.12567", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wenrui-xu", "dst": "p2:paper:2505.12567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:keshab-k-parhi", "dst": "p2:paper:2505.12567", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.13501", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zeyu-zhang", "dst": "p2:paper:2404.13501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaohe-bo", "dst": "p2:paper:2404.13501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-ma", "dst": "p2:paper:2404.13501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rui-li", "dst": "p2:paper:2404.13501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xu-chen", "dst": "p2:paper:2404.13501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:quanyu-dai", "dst": "p2:paper:2404.13501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jieming-zhu", "dst": "p2:paper:2404.13501", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenhua-dong", "dst": "p2:paper:2404.13501", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.20683", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jianyuan-guo", "dst": "p2:paper:2606.20683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiwei-hao", "dst": "p2:paper:2606.20683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chengcheng-wang", "dst": "p2:paper:2606.20683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cheng-fan", "dst": "p2:paper:2606.20683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tingzhang-luo", "dst": "p2:paper:2606.20683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongguang-li", "dst": "p2:paper:2606.20683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ying-gao", "dst": "p2:paper:2606.20683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hefei-mei", "dst": "p2:paper:2606.20683", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.12434", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shangheng-du", "dst": "p2:paper:2503.12434", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiabao-zhao", "dst": "p2:paper:2503.12434", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinxin-shi", "dst": "p2:paper:2503.12434", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhentao-xie", "dst": "p2:paper:2503.12434", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xin-jiang", "dst": "p2:paper:2503.12434", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanhong-bai", "dst": "p2:paper:2503.12434", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liang-he", "dst": "p2:paper:2503.12434", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.19213", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:murong-yue", "dst": "p2:paper:2503.19213", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2312.17601", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dhruv-dhamani", "dst": "p2:paper:2312.17601", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mary-lou-maher", "dst": "p2:paper:2312.17601", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.07864", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhiheng-xi", "dst": "p2:paper:2309.07864", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenxiang-chen", "dst": "p2:paper:2309.07864", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xin-guo", "dst": "p2:paper:2309.07864", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-he", "dst": "p2:paper:2309.07864", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiwen-ding", "dst": "p2:paper:2309.07864", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:boyang-hong", "dst": "p2:paper:2309.07864", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ming-zhang", "dst": "p2:paper:2309.07864", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junzhe-wang", "dst": "p2:paper:2309.07864", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.00753", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:henry-peng-zou", "dst": "p2:paper:2505.00753", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-chieh-huang", "dst": "p2:paper:2505.00753", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yaozu-wu", "dst": "p2:paper:2505.00753", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jizhou-guo", "dst": "p2:paper:2505.00753", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yankai-chen", "dst": "p2:paper:2505.00753", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chunyu-miao", "dst": "p2:paper:2505.00753", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hoang-nguyen", "dst": "p2:paper:2505.00753", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yue-zhou", "dst": "p2:paper:2505.00753", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.21504", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mahmoud-mohammadi", "dst": "p2:paper:2507.21504", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yipeng-li", "dst": "p2:paper:2507.21504", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jane-lo", "dst": "p2:paper:2507.21504", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wendy-yip", "dst": "p2:paper:2507.21504", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.23419", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:linghao-zhang", "dst": "p2:paper:2505.23419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shilin-he", "dst": "p2:paper:2505.23419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chaoyun-zhang", "dst": "p2:paper:2505.23419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-kang", "dst": "p2:paper:2505.23419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bowen-li", "dst": "p2:paper:2505.23419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chengxing-xie", "dst": "p2:paper:2505.23419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junhao-wang", "dst": "p2:paper:2505.23419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:maoquan-wang", "dst": "p2:paper:2505.23419", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.08996", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:spandan-garg", "dst": "p2:paper:2510.08996", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:benjamin-steenhoek", "dst": "p2:paper:2510.08996", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yufan-huang", "dst": "p2:paper:2510.08996", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.06992", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:reem-aleithan", "dst": "p2:paper:2410.06992", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoran-xue", "dst": "p2:paper:2410.06992", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohammad-mahdi-mohajer", "dst": "p2:paper:2410.06992", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:elijah-nnorom", "dst": "p2:paper:2410.06992", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gias-uddin", "dst": "p2:paper:2410.06992", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:song-wang", "dst": "p2:paper:2410.06992", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.16941", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiang-deng", "dst": "p2:paper:2509.16941", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jeff-da", "dst": "p2:paper:2509.16941", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:edwin-pan", "dst": "p2:paper:2509.16941", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yannis-yiming-he", "dst": "p2:paper:2509.16941", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:charles-ide", "dst": "p2:paper:2509.16941", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kanak-garg", "dst": "p2:paper:2509.16941", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:niklas-lauffer", "dst": "p2:paper:2509.16941", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrew-park", "dst": "p2:paper:2509.16941", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.03859", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:john-yang", "dst": "p2:paper:2410.03859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:carlos-e-jimenez", "dst": "p2:paper:2410.03859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alex-l-zhang", "dst": "p2:paper:2410.03859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kilian-lieret", "dst": "p2:paper:2410.03859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joyce-yang", "dst": "p2:paper:2410.03859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xindi-wu", "dst": "p2:paper:2410.03859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ori-press", "dst": "p2:paper:2410.03859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:niklas-muennighoff", "dst": "p2:paper:2410.03859", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.14683", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:leonhard-applis", "dst": "p2:paper:2506.14683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuntong-zhang", "dst": "p2:paper:2506.14683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shanchao-liang", "dst": "p2:paper:2506.14683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nan-jiang", "dst": "p2:paper:2506.14683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lin-tan", "dst": "p2:paper:2506.14683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abhik-roychoudhury", "dst": "p2:paper:2506.14683", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.08696", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:timothy-bula", "dst": "p2:paper:2504.08696", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:saurabh-pujar", "dst": "p2:paper:2504.08696", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luca-buratti", "dst": "p2:paper:2504.08696", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mihaela-bornea", "dst": "p2:paper:2504.08696", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:avirup-sil", "dst": "p2:paper:2504.08696", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.09289", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:boxi-yu", "dst": "p2:paper:2506.09289", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxuan-zhu", "dst": "p2:paper:2506.09289", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pinjia-he", "dst": "p2:paper:2506.09289", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-kang", "dst": "p2:paper:2506.09289", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.12286", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shanchao-liang", "dst": "p2:paper:2506.12286", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:spandan-garg", "dst": "p2:paper:2506.12286", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:roshanak-zilouchian-moghaddam", "dst": "p2:paper:2506.12286", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.04485", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:anton-cheshkov", "dst": "p2:paper:2410.04485", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pavel-zadorozhny", "dst": "p2:paper:2410.04485", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rodion-levichev", "dst": "p2:paper:2410.04485", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:evgeny-maslov", "dst": "p2:paper:2410.04485", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ronaldo-franco-jaldin", "dst": "p2:paper:2410.04485", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.15223", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:you-wang", "dst": "p2:paper:2503.15223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-pradel", "dst": "p2:paper:2503.15223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhongxin-liu", "dst": "p2:paper:2503.15223", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.06770", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:carlos-e-jimenez", "dst": "p2:paper:2310.06770", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:john-yang", "dst": "p2:paper:2310.06770", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexander-wettig", "dst": "p2:paper:2310.06770", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shunyu-yao", "dst": "p2:paper:2310.06770", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kexin-pei", "dst": "p2:paper:2310.06770", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ofir-press", "dst": "p2:paper:2310.06770", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:karthik-narasimhan", "dst": "p2:paper:2310.06770", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.14354", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:daoguang-zan", "dst": "p2:paper:2408.14354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhirong-huang", "dst": "p2:paper:2408.14354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ailun-yu", "dst": "p2:paper:2408.14354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaoxin-lin", "dst": "p2:paper:2408.14354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yifan-shi", "dst": "p2:paper:2408.14354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-liu", "dst": "p2:paper:2408.14354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dong-chen", "dst": "p2:paper:2408.14354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zongshuai-qi", "dst": "p2:paper:2408.14354", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.17208", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:matias-martinez", "dst": "p2:paper:2506.17208", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xavier-franch", "dst": "p2:paper:2506.17208", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.04449", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:matias-martinez", "dst": "p2:paper:2602.04449", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xavier-franch", "dst": "p2:paper:2602.04449", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.03411", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:huatong-song", "dst": "p2:paper:2602.03411", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lisheng-huang", "dst": "p2:paper:2602.03411", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuang-sun", "dst": "p2:paper:2602.03411", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinhao-jiang", "dst": "p2:paper:2602.03411", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ran-le", "dst": "p2:paper:2602.03411", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daixuan-cheng", "dst": "p2:paper:2602.03411", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guoxin-chen", "dst": "p2:paper:2602.03411", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiwen-hu", "dst": "p2:paper:2602.03411", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.22129", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yifeng-ding", "dst": "p2:paper:2601.22129", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lingming-zhang", "dst": "p2:paper:2601.22129", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.00520", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:boxi-yu", "dst": "p2:paper:2603.00520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-cao", "dst": "p2:paper:2603.00520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuzhong-zhang", "dst": "p2:paper:2603.00520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liting-lin", "dst": "p2:paper:2603.00520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junjielong-xu", "dst": "p2:paper:2603.00520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiqing-zhong", "dst": "p2:paper:2603.00520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qinghua-xu", "dst": "p2:paper:2603.00520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guancheng-wang", "dst": "p2:paper:2603.00520", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.03419", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shuang-sun", "dst": "p2:paper:2602.03419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huatong-song", "dst": "p2:paper:2602.03419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lisheng-huang", "dst": "p2:paper:2602.03419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinhao-jiang", "dst": "p2:paper:2602.03419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ran-le", "dst": "p2:paper:2602.03419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhihao-lv", "dst": "p2:paper:2602.03419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zongchao-chen", "dst": "p2:paper:2602.03419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiwen-hu", "dst": "p2:paper:2602.03419", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.17419", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lilin-wang", "dst": "p2:paper:2512.17419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lucas-ramalho", "dst": "p2:paper:2512.17419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alan-celestino", "dst": "p2:paper:2512.17419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:phuc-anthony-pham", "dst": "p2:paper:2512.17419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-liu", "dst": "p2:paper:2512.17419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:umang-kumar-sinha", "dst": "p2:paper:2512.17419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andres-portillo", "dst": "p2:paper:2512.17419", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:onassis-osunwa", "dst": "p2:paper:2512.17419", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.00014", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:thomas-joshi", "dst": "p2:paper:2507.00014", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shayan-chowdhury", "dst": "p2:paper:2507.00014", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fatih-uysal", "dst": "p2:paper:2507.00014", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.02605", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:daoguang-zan", "dst": "p2:paper:2504.02605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhirong-huang", "dst": "p2:paper:2504.02605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-liu", "dst": "p2:paper:2504.02605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanwu-chen", "dst": "p2:paper:2504.02605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:linhao-zhang", "dst": "p2:paper:2504.02605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shulin-xin", "dst": "p2:paper:2504.02605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-chen", "dst": "p2:paper:2504.02605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qi-liu", "dst": "p2:paper:2504.02605", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.09108", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:gustavo-a-oliva", "dst": "p2:paper:2507.09108", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gopi-krishnan-rajbahadur", "dst": "p2:paper:2507.09108", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aaditya-bhatia", "dst": "p2:paper:2507.09108", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoxiang-zhang", "dst": "p2:paper:2507.09108", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yihao-chen", "dst": "p2:paper:2507.09108", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhilong-chen", "dst": "p2:paper:2507.09108", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arthur-leung", "dst": "p2:paper:2507.09108", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dayi-lin", "dst": "p2:paper:2507.09108", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.09540", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:muxin-tian", "dst": "p2:paper:2602.09540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhe-wang", "dst": "p2:paper:2602.09540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:blair-yang", "dst": "p2:paper:2602.09540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenwei-tang", "dst": "p2:paper:2602.09540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kunlun-zhu", "dst": "p2:paper:2602.09540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:honghua-dong", "dst": "p2:paper:2602.09540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanchen-li", "dst": "p2:paper:2602.09540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinni-xie", "dst": "p2:paper:2602.09540", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.12344", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mengyu-zheng", "dst": "p2:paper:2606.12344", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kai-han", "dst": "p2:paper:2606.12344", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:boxun-li", "dst": "p2:paper:2606.12344", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haiyang-xu", "dst": "p2:paper:2606.12344", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuchuan-tian", "dst": "p2:paper:2606.12344", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-he", "dst": "p2:paper:2606.12344", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hang-zhou", "dst": "p2:paper:2606.12344", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianyuan-guo", "dst": "p2:paper:2606.12344", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2607.00990", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yaoqi-guo", "dst": "p2:paper:2607.00990", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-liu", "dst": "p2:paper:2607.00990", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jie-m-zhang", "dst": "p2:paper:2607.00990", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yun-ma", "dst": "p2:paper:2607.00990", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiling-lou", "dst": "p2:paper:2607.00990", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenpeng-chen", "dst": "p2:paper:2607.00990", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.10218", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:thanosan-prathifkumar", "dst": "p2:paper:2512.10218", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:noble-saji-mathews", "dst": "p2:paper:2512.10218", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:meiyappan-nagappan", "dst": "p2:paper:2512.10218", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.11051", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kirill-gelvan", "dst": "p2:paper:2605.11051", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:igor-slinko", "dst": "p2:paper:2605.11051", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:felix-steinbauer", "dst": "p2:paper:2605.11051", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:egor-bogomolov", "dst": "p2:paper:2605.11051", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:florian-kofler", "dst": "p2:paper:2605.11051", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yaroslav-zharov", "dst": "p2:paper:2605.11051", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.13995", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:brendan-king", "dst": "p2:paper:2606.13995", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jeffrey-flanigan", "dst": "p2:paper:2606.13995", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.18332", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wei-ma", "dst": "p2:paper:2605.18332", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhi-chen", "dst": "p2:paper:2605.18332", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingxu-gu", "dst": "p2:paper:2605.18332", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianling-li", "dst": "p2:paper:2605.18332", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shangqing-liu", "dst": "p2:paper:2605.18332", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lingxiao-jiang", "dst": "p2:paper:2605.18332", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.00835", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jinchao-hu", "dst": "p2:paper:2604.00835", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:meizhi-zhong", "dst": "p2:paper:2604.00835", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kehai-chen", "dst": "p2:paper:2604.00835", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuefeng-bai", "dst": "p2:paper:2604.00835", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:min-zhang", "dst": "p2:paper:2604.00835", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.12430", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:renjun-xu", "dst": "p2:paper:2602.12430", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-yan", "dst": "p2:paper:2602.12430", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.12908", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ziyi-wang", "dst": "p2:paper:2606.12908", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxuan-lu", "dst": "p2:paper:2606.12908", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yimeng-zhang", "dst": "p2:paper:2606.12908", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qun-liu", "dst": "p2:paper:2606.12908", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-luo", "dst": "p2:paper:2606.12908", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiri-gesi", "dst": "p2:paper:2606.12908", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanqing-lu", "dst": "p2:paper:2606.12908", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yisi-sang", "dst": "p2:paper:2606.12908", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.21590", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuanjie-lyu", "dst": "p2:paper:2604.21590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chengyu-wang", "dst": "p2:paper:2604.21590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haonan-zheng", "dst": "p2:paper:2604.21590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuanhao-yue", "dst": "p2:paper:2604.21590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junbing-yan", "dst": "p2:paper:2604.21590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ming-wang", "dst": "p2:paper:2604.21590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-huang", "dst": "p2:paper:2604.21590", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.01279", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yongchao-chen", "dst": "p2:paper:2510.01279", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiefeng-chen", "dst": "p2:paper:2510.01279", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rui-meng", "dst": "p2:paper:2510.01279", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ji-yin", "dst": "p2:paper:2510.01279", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:na-li", "dst": "p2:paper:2510.01279", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chuchu-fan", "dst": "p2:paper:2510.01279", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chi-wang", "dst": "p2:paper:2510.01279", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tomas-pfister", "dst": "p2:paper:2510.01279", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2607.04686", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:harsh-soni", "dst": "p2:paper:2607.04686", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.02050", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zeping-li", "dst": "p2:paper:2602.02050", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongru-wang", "dst": "p2:paper:2602.02050", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiwen-zhao", "dst": "p2:paper:2602.02050", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guanhua-chen", "dst": "p2:paper:2602.02050", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yixia-li", "dst": "p2:paper:2602.02050", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:keyang-chen", "dst": "p2:paper:2602.02050", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yixin-cao", "dst": "p2:paper:2602.02050", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guangnan-ye", "dst": "p2:paper:2602.02050", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.08567", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tajamul-ashraf", "dst": "p2:paper:2510.08567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:umair-nawaz", "dst": "p2:paper:2510.08567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abdelrahman-m-shaker", "dst": "p2:paper:2510.08567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rao-anwer", "dst": "p2:paper:2510.08567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:philip-torr", "dst": "p2:paper:2510.08567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fahad-shahbaz-khan", "dst": "p2:paper:2510.08567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:salman-khan", "dst": "p2:paper:2510.08567", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.18747", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xuying-ning", "dst": "p2:paper:2605.18747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:katherine-tieu", "dst": "p2:paper:2605.18747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dongqi-fu", "dst": "p2:paper:2605.18747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianxin-wei", "dst": "p2:paper:2605.18747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zihao-li", "dst": "p2:paper:2605.18747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuanchen-bei", "dst": "p2:paper:2605.18747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaru-zou", "dst": "p2:paper:2605.18747", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mengting-ai", "dst": "p2:paper:2605.18747", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.19369", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:changhyun-jeon", "dst": "p2:paper:2509.19369", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinhee-park", "dst": "p2:paper:2509.19369", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jungwoo-choi", "dst": "p2:paper:2509.19369", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:keonwoo-kim", "dst": "p2:paper:2509.19369", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jisu-kim", "dst": "p2:paper:2509.19369", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:minji-hong", "dst": "p2:paper:2509.19369", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.16260", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:fei-lei", "dst": "p2:paper:2508.16260", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yibo-yang", "dst": "p2:paper:2508.16260", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenxiu-sun", "dst": "p2:paper:2508.16260", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dahua-lin", "dst": "p2:paper:2508.16260", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.14480", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:weiting-tan", "dst": "p2:paper:2509.14480", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinghua-qu", "dst": "p2:paper:2509.14480", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ming-tu", "dst": "p2:paper:2509.14480", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:meng-ge", "dst": "p2:paper:2509.14480", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andy-t-liu", "dst": "p2:paper:2509.14480", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:philipp-koehn", "dst": "p2:paper:2509.14480", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-lu", "dst": "p2:paper:2509.14480", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.14460", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mingyue-cheng", "dst": "p2:paper:2511.14460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuo-yu", "dst": "p2:paper:2511.14460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daoyu-wang", "dst": "p2:paper:2511.14460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qingchuan-li", "dst": "p2:paper:2511.14460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoyu-tao", "dst": "p2:paper:2511.14460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jie-ouyang", "dst": "p2:paper:2511.14460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yucong-luo", "dst": "p2:paper:2511.14460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yitong-zhou", "dst": "p2:paper:2511.14460", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.12687", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:naveen-krishnan", "dst": "p2:paper:2503.12687", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.20036", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:marianne-menglin-liu", "dst": "p2:paper:2510.20036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-garcia", "dst": "p2:paper:2510.20036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fjona-parllaku", "dst": "p2:paper:2510.20036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vikas-upadhyay", "dst": "p2:paper:2510.20036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:syed-fahad-allam-shah", "dst": "p2:paper:2510.20036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dan-roth", "dst": "p2:paper:2510.20036", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.11652", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yifan-yang", "dst": "p2:paper:2606.11652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhen-zhang", "dst": "p2:paper:2606.11652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiayi-tian", "dst": "p2:paper:2606.11652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liyan-tan", "dst": "p2:paper:2606.11652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zheng-zhang", "dst": "p2:paper:2606.11652", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.04550", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:pengfei-he", "dst": "p2:paper:2510.04550", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenwei-dai", "dst": "p2:paper:2510.04550", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bing-he", "dst": "p2:paper:2510.04550", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hui-liu", "dst": "p2:paper:2510.04550", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xianfeng-tang", "dst": "p2:paper:2510.04550", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanqing-lu", "dst": "p2:paper:2510.04550", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:juanhui-li", "dst": "p2:paper:2510.04550", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiayuan-ding", "dst": "p2:paper:2510.04550", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.05432", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wuyang-zhang", "dst": "p2:paper:2604.05432", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shichao-pei", "dst": "p2:paper:2604.05432", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.25135", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:amir-saeidi", "dst": "p2:paper:2604.25135", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:venkatesh-mishra", "dst": "p2:paper:2604.25135", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:souradeep-mukhopadhyay", "dst": "p2:paper:2604.25135", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gaowen-liu", "dst": "p2:paper:2604.25135", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ali-payani", "dst": "p2:paper:2604.25135", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jayanth-srinivasa", "dst": "p2:paper:2604.25135", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chitta-baral", "dst": "p2:paper:2604.25135", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.20145", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wei-zhou", "dst": "p2:paper:2412.20145", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohsen-mesgar", "dst": "p2:paper:2412.20145", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:annemarie-friedrich", "dst": "p2:paper:2412.20145", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:heike-adel", "dst": "p2:paper:2412.20145", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.22862", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haoyuan-xu", "dst": "p2:paper:2603.22862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chang-li", "dst": "p2:paper:2603.22862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyan-ma", "dst": "p2:paper:2603.22862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xianhao-ou", "dst": "p2:paper:2603.22862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zihan-zhang", "dst": "p2:paper:2603.22862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tao-he", "dst": "p2:paper:2603.22862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiangyu-liu", "dst": "p2:paper:2603.22862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zixiang-wang", "dst": "p2:paper:2603.22862", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.00994", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yu-li", "dst": "p2:paper:2602.00994", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingyang-yi", "dst": "p2:paper:2602.00994", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiuyu-li", "dst": "p2:paper:2602.00994", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ju-fan", "dst": "p2:paper:2602.00994", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fuxin-jiang", "dst": "p2:paper:2602.00994", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:binbin-chen", "dst": "p2:paper:2602.00994", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peng-li", "dst": "p2:paper:2602.00994", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jie-song", "dst": "p2:paper:2602.00994", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.01716", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yifei-zhou", "dst": "p2:paper:2506.01716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sergey-levine", "dst": "p2:paper:2506.01716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jason-weston", "dst": "p2:paper:2506.01716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xian-li", "dst": "p2:paper:2506.01716", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sainbayar-sukhbaatar", "dst": "p2:paper:2506.01716", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.22504", "dst": "p2:axis:agents", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jinyeop-song", "dst": "p2:paper:2509.22504", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jeff-gore", "dst": "p2:paper:2509.22504", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:max-kleiman-weiner", "dst": "p2:paper:2509.22504", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.16997", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shimao-chen", "dst": "p2:paper:2409.16997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zirui-liu", "dst": "p2:paper:2409.16997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiying-wu", "dst": "p2:paper:2409.16997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ce-zheng", "dst": "p2:paper:2409.16997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peizhuang-cong", "dst": "p2:paper:2409.16997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zihan-jiang", "dst": "p2:paper:2409.16997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuhan-wu", "dst": "p2:paper:2409.16997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-su", "dst": "p2:paper:2409.16997", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.11331", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiawei-lin", "dst": "p2:paper:2507.11331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuanlong-li", "dst": "p2:paper:2507.11331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guokai-chen", "dst": "p2:paper:2507.11331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thomas-bourgeat", "dst": "p2:paper:2507.11331", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.14201", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kosmas-alexandridis", "dst": "p2:paper:2505.14201", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vasileios-titopoulos", "dst": "p2:paper:2505.14201", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:giorgos-dimitrakopoulos", "dst": "p2:paper:2505.14201", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.00367", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:joonmyung-choi", "dst": "p2:paper:2508.00367", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sanghyeok-lee", "dst": "p2:paper:2508.00367", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:byungoh-ko", "dst": "p2:paper:2508.00367", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eunseo-kim", "dst": "p2:paper:2508.00367", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jihyung-kil", "dst": "p2:paper:2508.00367", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hyunwoo-j-kim", "dst": "p2:paper:2508.00367", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.14314", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kosmas-alexandridis", "dst": "p2:paper:2505.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vasileios-titopoulos", "dst": "p2:paper:2505.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:giorgos-dimitrakopoulos", "dst": "p2:paper:2505.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.01359", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:guoxia-wang", "dst": "p2:paper:2410.01359", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinle-zeng", "dst": "p2:paper:2410.01359", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiyuan-xiao", "dst": "p2:paper:2410.01359", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:siming-wu", "dst": "p2:paper:2410.01359", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiabin-yang", "dst": "p2:paper:2410.01359", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lujing-zheng", "dst": "p2:paper:2410.01359", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zeyu-chen", "dst": "p2:paper:2410.01359", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiang-bian", "dst": "p2:paper:2410.01359", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.06834", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:vasileios-titopoulos", "dst": "p2:paper:2510.06834", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kosmas-alexandridis", "dst": "p2:paper:2510.06834", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:giorgos-dimitrakopoulos", "dst": "p2:paper:2510.06834", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.06738", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dongheon-lee", "dst": "p2:paper:2603.06738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:seokju-yun", "dst": "p2:paper:2603.06738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jaegyun-im", "dst": "p2:paper:2603.06738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:youngmin-ro", "dst": "p2:paper:2603.06738", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.00295", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kosmas-alexandridis", "dst": "p2:paper:2511.00295", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:giorgos-dimitrakopoulos", "dst": "p2:paper:2511.00295", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.03317", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:vincent-abbott", "dst": "p2:paper:2412.03317", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gioele-zardini", "dst": "p2:paper:2412.03317", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.00555", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhongchun-zhou", "dst": "p2:paper:2605.00555", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuhang-gu", "dst": "p2:paper:2605.00555", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chengtao-lai", "dst": "p2:paper:2605.00555", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ya-wang", "dst": "p2:paper:2605.00555", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-zhang", "dst": "p2:paper:2605.00555", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.11016", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jinxin-yu", "dst": "p2:paper:2602.11016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yudong-pan", "dst": "p2:paper:2602.11016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mengdi-wang", "dst": "p2:paper:2602.11016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huawei-li", "dst": "p2:paper:2602.11016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yinhe-han", "dst": "p2:paper:2602.11016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaowei-li", "dst": "p2:paper:2602.11016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ying-wang", "dst": "p2:paper:2602.11016", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.25224", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qichen-liao", "dst": "p2:paper:2509.25224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chengqiu-hu", "dst": "p2:paper:2509.25224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fangzheng-miao", "dst": "p2:paper:2509.25224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bao-li", "dst": "p2:paper:2509.25224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiyang-liu", "dst": "p2:paper:2509.25224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junlong-lyu", "dst": "p2:paper:2509.25224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lirui-jiang", "dst": "p2:paper:2509.25224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-wang", "dst": "p2:paper:2509.25224", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.05451", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ted-zadouri", "dst": "p2:paper:2603.05451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:markus-hoehnerbach", "dst": "p2:paper:2603.05451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jay-shah", "dst": "p2:paper:2603.05451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:timmy-liu", "dst": "p2:paper:2603.05451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vijay-thakkar", "dst": "p2:paper:2603.05451", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2607.04302", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hui-dong", "dst": "p2:paper:2607.04302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanzhao-li", "dst": "p2:paper:2607.04302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jie-gao", "dst": "p2:paper:2607.04302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chunlu-li", "dst": "p2:paper:2607.04302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiyuan-zhang", "dst": "p2:paper:2607.04302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yupeng-sun", "dst": "p2:paper:2607.04302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenyuan-chen", "dst": "p2:paper:2607.04302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiqiang-zou", "dst": "p2:paper:2607.04302", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.00028", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mart-llopart-font", "dst": "p2:paper:2604.00028", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:javier-hernando", "dst": "p2:paper:2604.00028", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cristina-espa-a-bonet", "dst": "p2:paper:2604.00028", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2312.11918", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ganesh-bikshandi", "dst": "p2:paper:2312.11918", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jay-shah", "dst": "p2:paper:2312.11918", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.16663", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haoran-lin", "dst": "p2:paper:2410.16663", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xianzhi-yu", "dst": "p2:paper:2410.16663", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kang-zhao", "dst": "p2:paper:2410.16663", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-hou", "dst": "p2:paper:2410.16663", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zongyuan-zhan", "dst": "p2:paper:2410.16663", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stanislav-kamenev", "dst": "p2:paper:2410.16663", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:han-bao", "dst": "p2:paper:2410.16663", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ting-hu", "dst": "p2:paper:2410.16663", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.25306", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sehyeon-oh", "dst": "p2:paper:2604.25306", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongin-kwon", "dst": "p2:paper:2604.25306", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jemin-lee", "dst": "p2:paper:2604.25306", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.07443", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:barna-saha", "dst": "p2:paper:2402.07443", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-ye", "dst": "p2:paper:2402.07443", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2306.01160", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:matteo-pagliardini", "dst": "p2:paper:2306.01160", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniele-paliotta", "dst": "p2:paper:2306.01160", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:martin-jaggi", "dst": "p2:paper:2306.01160", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fran-ois-fleuret", "dst": "p2:paper:2306.01160", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.03294", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dacheng-li", "dst": "p2:paper:2310.03294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rulin-shao", "dst": "p2:paper:2310.03294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anze-xie", "dst": "p2:paper:2310.03294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eric-p-xing", "dst": "p2:paper:2310.03294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuezhe-ma", "dst": "p2:paper:2310.03294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ion-stoica", "dst": "p2:paper:2310.03294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joseph-e-gonzalez", "dst": "p2:paper:2310.03294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-zhang", "dst": "p2:paper:2310.03294", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.05175", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dmitry-rybin", "dst": "p2:paper:2510.05175", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yushun-zhang", "dst": "p2:paper:2510.05175", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ding-tian", "dst": "p2:paper:2510.05175", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhihang-lin", "dst": "p2:paper:2510.05175", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhi-quan-luo", "dst": "p2:paper:2510.05175", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.16032", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yifan-zhu", "dst": "p2:paper:2601.16032", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yekai-pan", "dst": "p2:paper:2601.16032", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-ding", "dst": "p2:paper:2601.16032", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.05496", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:juechu-dong", "dst": "p2:paper:2412.05496", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:boyuan-feng", "dst": "p2:paper:2412.05496", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:driss-guessous", "dst": "p2:paper:2412.05496", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanbo-liang", "dst": "p2:paper:2412.05496", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:horace-he", "dst": "p2:paper:2412.05496", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.15422", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiading-gai", "dst": "p2:paper:2605.15422", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuai-zhang", "dst": "p2:paper:2605.15422", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiang-song", "dst": "p2:paper:2605.15422", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bernie-wang", "dst": "p2:paper:2605.15422", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:george-karypis", "dst": "p2:paper:2605.15422", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2501.06098", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chong-wu", "dst": "p2:paper:2501.06098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:maolin-che", "dst": "p2:paper:2501.06098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:renjie-xu", "dst": "p2:paper:2501.06098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhuoheng-ran", "dst": "p2:paper:2501.06098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hong-yan", "dst": "p2:paper:2501.06098", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.07839", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aleksandar-botev", "dst": "p2:paper:2404.07839", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:soham-de", "dst": "p2:paper:2404.07839", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:samuel-l-smith", "dst": "p2:paper:2404.07839", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anushan-fernando", "dst": "p2:paper:2404.07839", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:george-cristian-muraru", "dst": "p2:paper:2404.07839", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruba-haroun", "dst": "p2:paper:2404.07839", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:leonard-berrada", "dst": "p2:paper:2404.07839", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:razvan-pascanu", "dst": "p2:paper:2404.07839", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.21316", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:khushiyant", "dst": "p2:paper:2603.21316", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:param-thakkar", "dst": "p2:paper:2603.21316", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.01240", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ruthwik-reddy-doodipala", "dst": "p2:paper:2605.01240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pankaj-pandey", "dst": "p2:paper:2605.01240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pratheek-eranki", "dst": "p2:paper:2605.01240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:carolina-torres-rojas", "dst": "p2:paper:2605.01240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:manob-jyoti-saikia", "dst": "p2:paper:2605.01240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ranganatha-sitaram", "dst": "p2:paper:2605.01240", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.01958", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nikolai-lund-k-hne", "dst": "p2:paper:2510.01958", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jesper-jensen", "dst": "p2:paper:2510.01958", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jan-stergaard", "dst": "p2:paper:2510.01958", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zheng-hua-tan", "dst": "p2:paper:2510.01958", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.24067", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yixing-li", "dst": "p2:paper:2503.24067", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruobing-xie", "dst": "p2:paper:2503.24067", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhen-yang", "dst": "p2:paper:2503.24067", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xingwu-sun", "dst": "p2:paper:2503.24067", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuaipeng-li", "dst": "p2:paper:2503.24067", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weidong-han", "dst": "p2:paper:2503.24067", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhanhui-kang", "dst": "p2:paper:2503.24067", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-cheng", "dst": "p2:paper:2503.24067", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.00871", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yunze-liu", "dst": "p2:paper:2410.00871", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:li-yi", "dst": "p2:paper:2410.00871", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.07552", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zepeng-yang", "dst": "p2:paper:2605.07552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junxuan-bai", "dst": "p2:paper:2605.07552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-li", "dst": "p2:paper:2605.07552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ju-dai", "dst": "p2:paper:2605.07552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junjun-pan", "dst": "p2:paper:2605.07552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongfeng-yin", "dst": "p2:paper:2605.07552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bin-li", "dst": "p2:paper:2605.07552", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.14191", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:abhinav-moudgil", "dst": "p2:paper:2604.14191", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ningyuan-huang", "dst": "p2:paper:2604.14191", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eeshan-gunesh-dhekane", "dst": "p2:paper:2604.14191", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pau-rodr-guez", "dst": "p2:paper:2604.14191", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luca-zappella", "dst": "p2:paper:2604.14191", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:federico-danieli", "dst": "p2:paper:2604.14191", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.14757", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiongxiao-xu", "dst": "p2:paper:2404.14757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:canyu-chen", "dst": "p2:paper:2404.14757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yueqing-liang", "dst": "p2:paper:2404.14757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:baixiang-huang", "dst": "p2:paper:2404.14757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guangji-bai", "dst": "p2:paper:2404.14757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liang-zhao", "dst": "p2:paper:2404.14757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kai-shu", "dst": "p2:paper:2404.14757", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2501.18401", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:juan-wen", "dst": "p2:paper:2501.18401", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weiyan-hou", "dst": "p2:paper:2501.18401", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luc-van-gool", "dst": "p2:paper:2501.18401", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:radu-timofte", "dst": "p2:paper:2501.18401", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.17834", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shy-el-cohen", "dst": "p2:paper:2505.17834", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yoni-choukroun", "dst": "p2:paper:2505.17834", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eliya-nachmani", "dst": "p2:paper:2505.17834", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.15237", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:junxiong-wang", "dst": "p2:paper:2408.15237", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniele-paliotta", "dst": "p2:paper:2408.15237", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:avner-may", "dst": "p2:paper:2408.15237", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexander-m-rush", "dst": "p2:paper:2408.15237", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.17296", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xuanyu-lin", "dst": "p2:paper:2507.17296", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaona-zeng", "dst": "p2:paper:2507.17296", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xianwei-zheng", "dst": "p2:paper:2507.17296", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xutao-li", "dst": "p2:paper:2507.17296", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.11131", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:elisha-dayag", "dst": "p2:paper:2605.11131", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nhat-thanh-tran", "dst": "p2:paper:2605.11131", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jack-xin", "dst": "p2:paper:2605.11131", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.19613", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qianxiong-xu", "dst": "p2:paper:2409.19613", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuanyi-liu", "dst": "p2:paper:2409.19613", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lanyun-zhu", "dst": "p2:paper:2409.19613", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guosheng-lin", "dst": "p2:paper:2409.19613", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cheng-long", "dst": "p2:paper:2409.19613", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ziyue-li", "dst": "p2:paper:2409.19613", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rui-zhao", "dst": "p2:paper:2409.19613", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.11178", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:a-enes-doruk", "dst": "p2:paper:2502.11178", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hasan-f-ates", "dst": "p2:paper:2502.11178", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.02944", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kwok-ho-ng", "dst": "p2:paper:2601.02944", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tingting-song", "dst": "p2:paper:2601.02944", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongdong-wu", "dst": "p2:paper:2601.02944", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhihua-xia", "dst": "p2:paper:2601.02944", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.08083", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ali-hatamizadeh", "dst": "p2:paper:2407.08083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jan-kautz", "dst": "p2:paper:2407.08083", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.13135", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jinzhao-su", "dst": "p2:paper:2407.13135", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenhua-huang", "dst": "p2:paper:2407.13135", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.00966", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nikolai-lund-k-hne", "dst": "p2:paper:2507.00966", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jesper-jensen", "dst": "p2:paper:2507.00966", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jan-stergaard", "dst": "p2:paper:2507.00966", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zheng-hua-tan", "dst": "p2:paper:2507.00966", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.12078", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wenlong-wang", "dst": "p2:paper:2602.12078", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fergal-reid", "dst": "p2:paper:2602.12078", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.18031", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:youjin-wang", "dst": "p2:paper:2603.18031", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaqiao-zhao", "dst": "p2:paper:2603.18031", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rong-fu", "dst": "p2:paper:2603.18031", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:run-zhou", "dst": "p2:paper:2603.18031", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruizhe-zhang", "dst": "p2:paper:2603.18031", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiani-liang", "dst": "p2:paper:2603.18031", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:suisuai-cao", "dst": "p2:paper:2603.18031", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:feng-zhou", "dst": "p2:paper:2603.18031", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.22127", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hector-borobia", "dst": "p2:paper:2604.22127", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:elies-segu-mas", "dst": "p2:paper:2604.22127", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guillermina-tormo-carb", "dst": "p2:paper:2604.22127", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.16595", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:boshen-xu", "dst": "p2:paper:2511.16595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zihan-xiao", "dst": "p2:paper:2511.16595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaze-li", "dst": "p2:paper:2511.16595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianzhong-ju", "dst": "p2:paper:2511.16595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenbo-luo", "dst": "p2:paper:2511.16595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jian-luan", "dst": "p2:paper:2511.16595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qin-jin", "dst": "p2:paper:2511.16595", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.19931", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qing-xu", "dst": "p2:paper:2507.19931", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanming-chen", "dst": "p2:paper:2507.19931", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yue-li", "dst": "p2:paper:2507.19931", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ziyu-liu", "dst": "p2:paper:2507.19931", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenye-lou", "dst": "p2:paper:2507.19931", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yixuan-zhang", "dst": "p2:paper:2507.19931", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiangjian-he", "dst": "p2:paper:2507.19931", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.10581", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuanyuan-peng", "dst": "p2:paper:2605.10581", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wen-li", "dst": "p2:paper:2605.10581", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.10353", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yiheng-lyu", "dst": "p2:paper:2512.10353", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lian-xu", "dst": "p2:paper:2512.10353", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:coen-arrow", "dst": "p2:paper:2512.10353", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohammed-bennamoun", "dst": "p2:paper:2512.10353", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:farid-boussaid", "dst": "p2:paper:2512.10353", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:girish-dwivedi", "dst": "p2:paper:2512.10353", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.15703", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiaodong-mei", "dst": "p2:paper:2505.15703", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sheng-wang", "dst": "p2:paper:2505.15703", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jie-cheng", "dst": "p2:paper:2505.15703", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yingbing-chen", "dst": "p2:paper:2505.15703", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dan-xu", "dst": "p2:paper:2505.15703", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.17355", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:taixi-chen", "dst": "p2:paper:2511.17355", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingyun-chen", "dst": "p2:paper:2511.17355", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nancy-guo", "dst": "p2:paper:2511.17355", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.02922", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xinyi-zhang", "dst": "p2:paper:2408.02922", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qiqi-bao", "dst": "p2:paper:2408.02922", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qinpeng-cui", "dst": "p2:paper:2408.02922", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenming-yang", "dst": "p2:paper:2408.02922", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qingmin-liao", "dst": "p2:paper:2408.02922", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.24118", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:md-mozaharul-mottalib", "dst": "p2:paper:2509.24118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thao-ly-t-phan", "dst": "p2:paper:2509.24118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rahmatollah-beheshti", "dst": "p2:paper:2509.24118", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.12570", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jamba-team", "dst": "p2:paper:2408.12570", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:barak-lenz", "dst": "p2:paper:2408.12570", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alan-arazi", "dst": "p2:paper:2408.12570", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:amir-bergman", "dst": "p2:paper:2408.12570", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:avshalom-manevich", "dst": "p2:paper:2408.12570", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:barak-peleg", "dst": "p2:paper:2408.12570", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ben-aviram", "dst": "p2:paper:2408.12570", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-almagor", "dst": "p2:paper:2408.12570", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.01627", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:farzaneh-jafari", "dst": "p2:paper:2408.01627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stefano-berretti", "dst": "p2:paper:2408.01627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anup-basu", "dst": "p2:paper:2408.01627", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.09507", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:bingheng-wu", "dst": "p2:paper:2506.09507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingze-shi", "dst": "p2:paper:2506.09507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yifan-wu", "dst": "p2:paper:2506.09507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nan-tang", "dst": "p2:paper:2506.09507", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuyu-luo", "dst": "p2:paper:2506.09507", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.01972", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:alexandre-le-mercier", "dst": "p2:paper:2601.01972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chris-develder", "dst": "p2:paper:2601.01972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thomas-demeester", "dst": "p2:paper:2601.01972", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.15589", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:miao-sun", "dst": "p2:paper:2603.15589", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alish-kanani", "dst": "p2:paper:2603.15589", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaushik-shroff", "dst": "p2:paper:2603.15589", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:umit-ogras", "dst": "p2:paper:2603.15589", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.02332", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:suhyeong-shin", "dst": "p2:paper:2606.02332", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yeongwook-yang", "dst": "p2:paper:2606.02332", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.18116", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:batool-haider", "dst": "p2:paper:2506.18116", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:atmika-gorti", "dst": "p2:paper:2506.18116", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aman-chadha", "dst": "p2:paper:2506.18116", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:manas-gaur", "dst": "p2:paper:2506.18116", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.15521", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:loukas-triantafyllopoulos", "dst": "p2:paper:2503.15521", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dimitris-kalles", "dst": "p2:paper:2503.15521", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.22416", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:an-xuan-nguyen", "dst": "p2:paper:2605.22416", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.22442", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:abhinaba-basu", "dst": "p2:paper:2604.22442", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.18970", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shriyank-somvanshi", "dst": "p2:paper:2503.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:md-monzurul-islam", "dst": "p2:paper:2503.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mahmuda-sultana-mimi", "dst": "p2:paper:2503.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sazzad-bin-bashar-polock", "dst": "p2:paper:2503.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gaurab-chhetri", "dst": "p2:paper:2503.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anandi-dutta", "dst": "p2:paper:2503.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:amir-rafe", "dst": "p2:paper:2503.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:subasish-das", "dst": "p2:paper:2503.18970", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.06324", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:luca-zancato", "dst": "p2:paper:2407.06324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arjun-seshadri", "dst": "p2:paper:2407.06324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yonatan-dukler", "dst": "p2:paper:2407.06324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aditya-golatkar", "dst": "p2:paper:2407.06324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yantao-shen", "dst": "p2:paper:2407.06324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:benjamin-bowman", "dst": "p2:paper:2407.06324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matthew-trager", "dst": "p2:paper:2407.06324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alessandro-achille", "dst": "p2:paper:2407.06324", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.19861", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:felix-michalak", "dst": "p2:paper:2510.19861", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:steven-abreu", "dst": "p2:paper:2510.19861", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2607.03482", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aleksey-kudelya", "dst": "p2:paper:2607.03482", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rafif-alshawi", "dst": "p2:paper:2607.03482", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexander-shirnin", "dst": "p2:paper:2607.03482", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.01288", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nisrine-ait-khayi", "dst": "p2:paper:2603.01288", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.06617", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:adithya-pratapa", "dst": "p2:paper:2502.06617", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:teruko-mitamura", "dst": "p2:paper:2502.06617", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.16424", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:manoj-parmar", "dst": "p2:paper:2604.16424", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.14825", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yifan-zhao", "dst": "p2:paper:2604.14825", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuchen-yang", "dst": "p2:paper:2604.14825", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matei-budiu", "dst": "p2:paper:2604.14825", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sasa-misailovic", "dst": "p2:paper:2604.14825", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.21956", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:armin-gerami", "dst": "p2:paper:2510.21956", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ramani-duraiswami", "dst": "p2:paper:2510.21956", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.20005", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:guangda-liu", "dst": "p2:paper:2606.20005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiquan-wang", "dst": "p2:paper:2606.20005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chengwei-li", "dst": "p2:paper:2606.20005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenhao-chen", "dst": "p2:paper:2606.20005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jing-lin", "dst": "p2:paper:2606.20005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiwu-yao", "dst": "p2:paper:2606.20005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:danning-ke", "dst": "p2:paper:2606.20005", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenchao-ding", "dst": "p2:paper:2606.20005", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.12110", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:di-liu", "dst": "p2:paper:2605.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruitian-wang", "dst": "p2:paper:2605.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-chen", "dst": "p2:paper:2605.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingliang-gong", "dst": "p2:paper:2605.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongjie-yuan", "dst": "p2:paper:2605.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:han-zhao", "dst": "p2:paper:2605.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-feng", "dst": "p2:paper:2605.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:quan-chen", "dst": "p2:paper:2605.12110", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2607.03012", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dongyeun-lee", "dst": "p2:paper:2607.03012", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:amir-zandieh", "dst": "p2:paper:2607.03012", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vahab-mirrokni", "dst": "p2:paper:2607.03012", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junmo-kim", "dst": "p2:paper:2607.03012", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:insu-han", "dst": "p2:paper:2607.03012", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.24006", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jintao-zhang", "dst": "p2:paper:2509.24006", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoxu-wang", "dst": "p2:paper:2509.24006", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kai-jiang", "dst": "p2:paper:2509.24006", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuo-yang", "dst": "p2:paper:2509.24006", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaiwen-zheng", "dst": "p2:paper:2509.24006", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haocheng-xi", "dst": "p2:paper:2509.24006", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ziteng-wang", "dst": "p2:paper:2509.24006", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongzhou-zhu", "dst": "p2:paper:2509.24006", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.04239", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:carles-gelada", "dst": "p2:paper:2507.04239", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jacob-buckman", "dst": "p2:paper:2507.04239", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sean-zhang", "dst": "p2:paper:2507.04239", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:txus-bach", "dst": "p2:paper:2507.04239", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.05023", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xing-ma", "dst": "p2:paper:2605.05023", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yangjie-zhou", "dst": "p2:paper:2605.05023", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wu-sun", "dst": "p2:paper:2605.05023", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zihan-liu", "dst": "p2:paper:2605.05023", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingwen-leng", "dst": "p2:paper:2605.05023", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yun-lin", "dst": "p2:paper:2605.05023", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shixuan-sun", "dst": "p2:paper:2605.05023", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:minyi-guo", "dst": "p2:paper:2605.05023", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.27124", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:vijay-sadashivaiah", "dst": "p2:paper:2604.27124", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:georgios-dasoulas", "dst": "p2:paper:2604.27124", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:judith-mueller", "dst": "p2:paper:2604.27124", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:soumya-ghosh", "dst": "p2:paper:2604.27124", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.02132", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mansi-choudhary", "dst": "p2:paper:2511.02132", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:karthik-sangaiah", "dst": "p2:paper:2511.02132", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sonali-singh", "dst": "p2:paper:2511.02132", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:muhammad-osama", "dst": "p2:paper:2511.02132", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lisa-wu-wills", "dst": "p2:paper:2511.02132", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ganesh-dasika", "dst": "p2:paper:2511.02132", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.18038", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aditya-k-kamath", "dst": "p2:paper:2410.18038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ramya-prabhu", "dst": "p2:paper:2410.18038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jayashree-mohan", "dst": "p2:paper:2410.18038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:simon-peter", "dst": "p2:paper:2410.18038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ramachandran-ramjee", "dst": "p2:paper:2410.18038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ashish-panwar", "dst": "p2:paper:2410.18038", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2012.02030", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ileana-rugina", "dst": "p2:paper:2012.02030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rumen-dangovski", "dst": "p2:paper:2012.02030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:li-jing", "dst": "p2:paper:2012.02030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:preslav-nakov", "dst": "p2:paper:2012.02030", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marin-solja-i", "dst": "p2:paper:2012.02030", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.21221", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:boxun-xu", "dst": "p2:paper:2604.21221", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuming-du", "dst": "p2:paper:2604.21221", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zichang-liu", "dst": "p2:paper:2604.21221", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:siyu-yang", "dst": "p2:paper:2604.21221", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ziyang-jiang", "dst": "p2:paper:2604.21221", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:siqi-yan", "dst": "p2:paper:2604.21221", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rajasi-saha", "dst": "p2:paper:2604.21221", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:albert-pumarola", "dst": "p2:paper:2604.21221", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.09071", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tharun-adithya-srikrishnan", "dst": "p2:paper:2507.09071", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:deval-shah", "dst": "p2:paper:2507.09071", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:timothy-hein", "dst": "p2:paper:2507.09071", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ahmed-hasssan", "dst": "p2:paper:2507.09071", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stephen-youn", "dst": "p2:paper:2507.09071", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:steven-k-reinhardt", "dst": "p2:paper:2507.09071", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.20813", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yanyi-lyu", "dst": "p2:paper:2605.20813", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:letian-chen", "dst": "p2:paper:2605.20813", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:futing-sun", "dst": "p2:paper:2605.20813", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:miao-zhang", "dst": "p2:paper:2605.20813", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weili-guan", "dst": "p2:paper:2605.20813", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liqiang-nie", "dst": "p2:paper:2605.20813", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.02490", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:huiqiang-jiang", "dst": "p2:paper:2407.02490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yucheng-li", "dst": "p2:paper:2407.02490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chengruidong-zhang", "dst": "p2:paper:2407.02490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qianhui-wu", "dst": "p2:paper:2407.02490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xufang-luo", "dst": "p2:paper:2407.02490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:surin-ahn", "dst": "p2:paper:2407.02490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenhua-han", "dst": "p2:paper:2407.02490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:amir-h-abdi", "dst": "p2:paper:2407.02490", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.16083", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yucheng-li", "dst": "p2:paper:2504.16083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huiqiang-jiang", "dst": "p2:paper:2504.16083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chengruidong-zhang", "dst": "p2:paper:2504.16083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qianhui-wu", "dst": "p2:paper:2504.16083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xufang-luo", "dst": "p2:paper:2504.16083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:surin-ahn", "dst": "p2:paper:2504.16083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:amir-h-abdi", "dst": "p2:paper:2504.16083", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dongsheng-li", "dst": "p2:paper:2504.16083", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.07884", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hongjun-wang", "dst": "p2:paper:2512.07884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yitong-jiang", "dst": "p2:paper:2512.07884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:collin-mccarthy", "dst": "p2:paper:2512.07884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-wehr", "dst": "p2:paper:2512.07884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanrong-ye", "dst": "p2:paper:2512.07884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinhao-li", "dst": "p2:paper:2512.07884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ka-chun-cheung", "dst": "p2:paper:2512.07884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wonmin-byeon", "dst": "p2:paper:2512.07884", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.02883", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wonsuk-jang", "dst": "p2:paper:2603.02883", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thierry-tambe", "dst": "p2:paper:2603.02883", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.23466", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:divakar-kumar-yadav", "dst": "p2:paper:2604.23466", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tian-zhao", "dst": "p2:paper:2604.23466", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:deepak-kumar", "dst": "p2:paper:2604.23466", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.13345", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:saurabhsingh-rajput", "dst": "p2:paper:2601.13345", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexander-brandt", "dst": "p2:paper:2601.13345", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vadim-elisseev", "dst": "p2:paper:2601.13345", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tushar-sharma", "dst": "p2:paper:2601.13345", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1010.1482", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:rio-yokota", "dst": "p2:paper:1010.1482", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lorena-barba", "dst": "p2:paper:1010.1482", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.24169", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:eric-qu", "dst": "p2:paper:2410.24169", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aditi-s-krishnapriyan", "dst": "p2:paper:2410.24169", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.14884", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:susav-shrestha", "dst": "p2:paper:2505.14884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:brad-settlemyer", "dst": "p2:paper:2505.14884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nikoli-dryden", "dst": "p2:paper:2505.14884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:narasimha-reddy", "dst": "p2:paper:2505.14884", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.31500", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:daria-fomina", "dst": "p2:paper:2605.31500", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniil-krasylnikov", "dst": "p2:paper:2605.31500", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexey-boykov", "dst": "p2:paper:2605.31500", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrey-dolgovyazov", "dst": "p2:paper:2605.31500", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vyacheslav-zhdanovskiy", "dst": "p2:paper:2605.31500", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fedor-velikonivtsev", "dst": "p2:paper:2605.31500", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.19269", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:han-guo", "dst": "p2:paper:2605.19269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jack-zhang", "dst": "p2:paper:2605.19269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arjun-menon", "dst": "p2:paper:2605.19269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:driss-guessous", "dst": "p2:paper:2605.19269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vijay-thakkar", "dst": "p2:paper:2605.19269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yoon-kim", "dst": "p2:paper:2605.19269", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.21118", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chi-chih-chang", "dst": "p2:paper:2407.21118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-cheng-lin", "dst": "p2:paper:2407.21118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chien-yu-lin", "dst": "p2:paper:2407.21118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chong-yan-chen", "dst": "p2:paper:2407.21118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-fang-hu", "dst": "p2:paper:2407.21118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pei-shuo-wang", "dst": "p2:paper:2407.21118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ning-chi-huang", "dst": "p2:paper:2407.21118", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luis-ceze", "dst": "p2:paper:2407.21118", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2308.00442", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dongchen-han", "dst": "p2:paper:2308.00442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuran-pan", "dst": "p2:paper:2308.00442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yizeng-han", "dst": "p2:paper:2308.00442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shiji-song", "dst": "p2:paper:2308.00442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gao-huang", "dst": "p2:paper:2308.00442", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.16170", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuan-zhou", "dst": "p2:paper:2411.16170", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qingshan-xu", "dst": "p2:paper:2411.16170", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiequan-cui", "dst": "p2:paper:2411.16170", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junbao-zhou", "dst": "p2:paper:2411.16170", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jing-zhang", "dst": "p2:paper:2411.16170", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:richang-hong", "dst": "p2:paper:2411.16170", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanwang-zhang", "dst": "p2:paper:2411.16170", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.22710", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:naijian-cao", "dst": "p2:paper:2410.22710", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:renjie-he", "dst": "p2:paper:2410.22710", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuchao-dai", "dst": "p2:paper:2410.22710", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingyi-he", "dst": "p2:paper:2410.22710", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2206.10552", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:weixuan-sun", "dst": "p2:paper:2206.10552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhen-qin", "dst": "p2:paper:2206.10552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hui-deng", "dst": "p2:paper:2206.10552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianyuan-wang", "dst": "p2:paper:2206.10552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-zhang", "dst": "p2:paper:2206.10552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaihao-zhang", "dst": "p2:paper:2206.10552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nick-barnes", "dst": "p2:paper:2206.10552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stan-birchfield", "dst": "p2:paper:2206.10552", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2501.16182", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chuanyang-zheng", "dst": "p2:paper:2501.16182", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.20407", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhongpan-tang", "dst": "p2:paper:2508.20407", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.10064", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:armin-gerami", "dst": "p2:paper:2604.10064", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:seyedehanita-madani", "dst": "p2:paper:2604.10064", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ramani-duraiswami", "dst": "p2:paper:2604.10064", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.09316", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yeonju-ro", "dst": "p2:paper:2506.09316", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenyu-zhang", "dst": "p2:paper:2506.09316", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:souvik-kundu", "dst": "p2:paper:2506.09316", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhangyang-wang", "dst": "p2:paper:2506.09316", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aditya-akella", "dst": "p2:paper:2506.09316", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.19528", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haoxu-wang", "dst": "p2:paper:2508.19528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiheng-jiang", "dst": "p2:paper:2508.19528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gang-qiao", "dst": "p2:paper:2508.19528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pengteng-shi", "dst": "p2:paper:2508.19528", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:biao-tian", "dst": "p2:paper:2508.19528", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.15038", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jihao-huang", "dst": "p2:paper:2512.15038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xi-xia", "dst": "p2:paper:2512.15038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiyuan-li", "dst": "p2:paper:2512.15038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianle-liu", "dst": "p2:paper:2512.15038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingke-wang", "dst": "p2:paper:2512.15038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junbo-chen", "dst": "p2:paper:2512.15038", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tengju-ye", "dst": "p2:paper:2512.15038", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2401.00912", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chenhang-he", "dst": "p2:paper:2401.00912", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruihuang-li", "dst": "p2:paper:2401.00912", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guowen-zhang", "dst": "p2:paper:2401.00912", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-zhang", "dst": "p2:paper:2401.00912", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.13683", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:boyuan-cao", "dst": "p2:paper:2601.13683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xingbo-yao", "dst": "p2:paper:2601.13683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chenhui-wang", "dst": "p2:paper:2601.13683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaxin-ye", "dst": "p2:paper:2601.13683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yujie-wei", "dst": "p2:paper:2601.13683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongming-shan", "dst": "p2:paper:2601.13683", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.16063", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yifan-li", "dst": "p2:paper:2603.16063", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:seunghyun-yoon", "dst": "p2:paper:2603.16063", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:viet-dac-lai", "dst": "p2:paper:2603.16063", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:franck-dernoncourt", "dst": "p2:paper:2603.16063", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jason-kuen", "dst": "p2:paper:2603.16063", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-kong", "dst": "p2:paper:2603.16063", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:trung-bui", "dst": "p2:paper:2603.16063", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.18848", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:weinuo-ou", "dst": "p2:paper:2605.18848", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.06294", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wenjie-hu", "dst": "p2:paper:2511.06294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sidun-liu", "dst": "p2:paper:2511.06294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peng-qiao", "dst": "p2:paper:2511.06294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenglun-sun", "dst": "p2:paper:2511.06294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-dou", "dst": "p2:paper:2511.06294", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.07333", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zixuan-xie", "dst": "p2:paper:2605.07333", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyu-liu", "dst": "p2:paper:2605.07333", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:claire-chen", "dst": "p2:paper:2605.07333", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuze-daniel-liu", "dst": "p2:paper:2605.07333", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rohan-chandra", "dst": "p2:paper:2605.07333", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shangtong-zhang", "dst": "p2:paper:2605.07333", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.11685", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yichuan-deng", "dst": "p2:paper:2310.11685", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhao-song", "dst": "p2:paper:2310.11685", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaijun-yuan", "dst": "p2:paper:2310.11685", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianyi-zhou", "dst": "p2:paper:2310.11685", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.11582", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jialong-guo", "dst": "p2:paper:2405.11582", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinghao-chen", "dst": "p2:paper:2405.11582", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yehui-tang", "dst": "p2:paper:2405.11582", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yunhe-wang", "dst": "p2:paper:2405.11582", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.10101", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:morris-yau", "dst": "p2:paper:2410.10101", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ekin-aky-rek", "dst": "p2:paper:2410.10101", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiayuan-mao", "dst": "p2:paper:2410.10101", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joshua-b-tenenbaum", "dst": "p2:paper:2410.10101", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stefanie-jegelka", "dst": "p2:paper:2410.10101", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jacob-andreas", "dst": "p2:paper:2410.10101", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.05230", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiecheng-lu", "dst": "p2:paper:2602.05230", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xu-han", "dst": "p2:paper:2602.05230", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yan-sun", "dst": "p2:paper:2602.05230", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:viresh-pati", "dst": "p2:paper:2602.05230", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yubin-kim", "dst": "p2:paper:2602.05230", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:siddhartha-somani", "dst": "p2:paper:2602.05230", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shihao-yang", "dst": "p2:paper:2602.05230", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.16605", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dongchen-han", "dst": "p2:paper:2405.16605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ziyi-wang", "dst": "p2:paper:2405.16605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhuofan-xia", "dst": "p2:paper:2405.16605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yizeng-han", "dst": "p2:paper:2405.16605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yifan-pu", "dst": "p2:paper:2405.16605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chunjiang-ge", "dst": "p2:paper:2405.16605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-song", "dst": "p2:paper:2405.16605", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shiji-song", "dst": "p2:paper:2405.16605", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.12128", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hanno-ackermann", "dst": "p2:paper:2602.12128", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hong-cai", "dst": "p2:paper:2602.12128", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohsen-ghafoorian", "dst": "p2:paper:2602.12128", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:amirhossein-habibian", "dst": "p2:paper:2602.12128", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.07635", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qihang-fan", "dst": "p2:paper:2411.07635", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huaibo-huang", "dst": "p2:paper:2411.07635", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ran-he", "dst": "p2:paper:2411.07635", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.02882", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:weigao-sun", "dst": "p2:paper:2404.02882", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhen-qin", "dst": "p2:paper:2404.02882", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dong-li", "dst": "p2:paper:2404.02882", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuyang-shen", "dst": "p2:paper:2404.02882", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-qiao", "dst": "p2:paper:2404.02882", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiran-zhong", "dst": "p2:paper:2404.02882", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.00698", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qihang-fan", "dst": "p2:paper:2507.00698", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huaibo-huang", "dst": "p2:paper:2507.00698", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuang-ai", "dst": "p2:paper:2507.00698", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ran-he", "dst": "p2:paper:2507.00698", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.25223", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xunhao-lai", "dst": "p2:paper:2509.25223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jialiang-kang", "dst": "p2:paper:2509.25223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianqiao-lu", "dst": "p2:paper:2509.25223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tong-lin", "dst": "p2:paper:2509.25223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pengyu-zhao", "dst": "p2:paper:2509.25223", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.04761", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:han-guo", "dst": "p2:paper:2506.04761", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:songlin-yang", "dst": "p2:paper:2506.04761", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tarushii-goel", "dst": "p2:paper:2506.04761", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eric-p-xing", "dst": "p2:paper:2506.04761", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yoon-kim", "dst": "p2:paper:2506.04761", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.04347", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:michael-zhang", "dst": "p2:paper:2402.04347", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kush-bhatia", "dst": "p2:paper:2402.04347", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hermann-kumbong", "dst": "p2:paper:2402.04347", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-r", "dst": "p2:paper:2402.04347", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.21957", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aladin-djuhera", "dst": "p2:paper:2604.21957", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haris-gacanin", "dst": "p2:paper:2604.21957", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:holger-boche", "dst": "p2:paper:2604.21957", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.16624", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:meng-lou", "dst": "p2:paper:2507.16624", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yunxiang-fu", "dst": "p2:paper:2507.16624", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yizhou-yu", "dst": "p2:paper:2507.16624", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.05397", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhang-zhang", "dst": "p2:paper:2505.05397", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chao-sun", "dst": "p2:paper:2505.05397", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chao-yue", "dst": "p2:paper:2505.05397", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:da-wen", "dst": "p2:paper:2505.05397", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianze-wang", "dst": "p2:paper:2505.05397", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianghao-leng", "dst": "p2:paper:2505.05397", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.08301", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aditya-chattopadhyay", "dst": "p2:paper:2605.08301", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:elvis-nunez", "dst": "p2:paper:2605.08301", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:prannay-kaul", "dst": "p2:paper:2605.08301", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:benjamin-bowman", "dst": "p2:paper:2605.08301", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:evan-becker", "dst": "p2:paper:2605.08301", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luca-zancato", "dst": "p2:paper:2605.08301", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-thomas", "dst": "p2:paper:2605.08301", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-xia", "dst": "p2:paper:2605.08301", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.04159", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tomoki-honda", "dst": "p2:paper:2410.04159", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shinsuke-sakai", "dst": "p2:paper:2410.04159", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tatsuya-kawahara", "dst": "p2:paper:2410.04159", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.13328", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:elvis-nunez", "dst": "p2:paper:2412.13328", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luca-zancato", "dst": "p2:paper:2412.13328", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:benjamin-bowman", "dst": "p2:paper:2412.13328", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aditya-golatkar", "dst": "p2:paper:2412.13328", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-xia", "dst": "p2:paper:2412.13328", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stefano-soatto", "dst": "p2:paper:2412.13328", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.06069", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jia-wei-chen", "dst": "p2:paper:2406.06069", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-jie-xiong", "dst": "p2:paper:2406.06069", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-bin-gao", "dst": "p2:paper:2406.06069", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.07522", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:liliang-ren", "dst": "p2:paper:2406.07522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-liu", "dst": "p2:paper:2406.07522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yadong-lu", "dst": "p2:paper:2406.07522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yelong-shen", "dst": "p2:paper:2406.07522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-liang", "dst": "p2:paper:2406.07522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weizhu-chen", "dst": "p2:paper:2406.07522", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.03654", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiaochun-lei", "dst": "p2:paper:2506.03654", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:siqi-wu", "dst": "p2:paper:2506.03654", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weilin-wu", "dst": "p2:paper:2506.03654", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zetao-jiang", "dst": "p2:paper:2506.03654", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.02874", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:georgios-pantazopoulos", "dst": "p2:paper:2603.02874", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:malvina-nikandrou", "dst": "p2:paper:2603.02874", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ioannis-konstas", "dst": "p2:paper:2603.02874", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alessandro-suglia", "dst": "p2:paper:2603.02874", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.16495", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jingze-shi", "dst": "p2:paper:2406.16495", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ting-xie", "dst": "p2:paper:2406.16495", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bingheng-wu", "dst": "p2:paper:2406.16495", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chunjun-zheng", "dst": "p2:paper:2406.16495", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kai-wang", "dst": "p2:paper:2406.16495", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.05320", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:avery-hee-woon-ryoo", "dst": "p2:paper:2506.05320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nanda-h-krishna", "dst": "p2:paper:2506.05320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ximeng-mao", "dst": "p2:paper:2506.05320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mehdi-azabou", "dst": "p2:paper:2506.05320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eva-l-dyer", "dst": "p2:paper:2506.05320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matthew-g-perich", "dst": "p2:paper:2506.05320", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guillaume-lajoie", "dst": "p2:paper:2506.05320", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.00259", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:stefan-alexandru-jura", "dst": "p2:paper:2509.00259", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mihai-udrescu", "dst": "p2:paper:2509.00259", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexandru-topirceanu", "dst": "p2:paper:2509.00259", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.21330", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haoyang-wu", "dst": "p2:paper:2506.21330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tsun-hsuan-wang", "dst": "p2:paper:2506.21330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mathias-lechner", "dst": "p2:paper:2506.21330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ramin-hasani", "dst": "p2:paper:2506.21330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jennifer-a-eckhoff", "dst": "p2:paper:2506.21330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:paul-pak", "dst": "p2:paper:2506.21330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ozanan-r-meireles", "dst": "p2:paper:2506.21330", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guy-rosman", "dst": "p2:paper:2506.21330", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.11890", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yunxiang-fu", "dst": "p2:paper:2412.11890", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:meng-lou", "dst": "p2:paper:2412.11890", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yizhou-yu", "dst": "p2:paper:2412.11890", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.15459", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xinqi-liu", "dst": "p2:paper:2411.15459", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:li-zhou", "dst": "p2:paper:2411.15459", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zikun-zhou", "dst": "p2:paper:2411.15459", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianqiu-chen", "dst": "p2:paper:2411.15459", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenyu-he", "dst": "p2:paper:2411.15459", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.16955", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yalda-zafari", "dst": "p2:paper:2507.16955", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:roaa-elalfy", "dst": "p2:paper:2507.16955", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohamed-mabrok", "dst": "p2:paper:2507.16955", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:somaya-al-maadeed", "dst": "p2:paper:2507.16955", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tamer-khattab", "dst": "p2:paper:2507.16955", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:essam-a-rashed", "dst": "p2:paper:2507.16955", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.23126", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiaobin-hu", "dst": "p2:paper:2606.23126", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoyang-he", "dst": "p2:paper:2606.23126", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bo-yin", "dst": "p2:paper:2606.23126", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-he", "dst": "p2:paper:2606.23126", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-xie", "dst": "p2:paper:2606.23126", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiangning-zhang", "dst": "p2:paper:2606.23126", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-gang-jiang", "dst": "p2:paper:2606.23126", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuicheng-yan", "dst": "p2:paper:2606.23126", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.00862", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hyun-kyu-ko", "dst": "p2:paper:2510.00862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:youbin-kim", "dst": "p2:paper:2510.00862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jihyeon-park", "dst": "p2:paper:2510.00862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dongheok-park", "dst": "p2:paper:2510.00862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gyeongjin-kang", "dst": "p2:paper:2510.00862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wonjun-cho", "dst": "p2:paper:2510.00862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hyung-yi", "dst": "p2:paper:2510.00862", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eunbyung-park", "dst": "p2:paper:2510.00862", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.08859", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:john-cooper", "dst": "p2:paper:2603.08859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ilias-diakonikolas", "dst": "p2:paper:2603.08859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingchen-ma", "dst": "p2:paper:2603.08859", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:frederic-sala", "dst": "p2:paper:2603.08859", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.18757", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haochen-li", "dst": "p2:paper:2603.18757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rui-zhang", "dst": "p2:paper:2603.18757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hantao-yao", "dst": "p2:paper:2603.18757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xin-zhang", "dst": "p2:paper:2603.18757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yifan-hao", "dst": "p2:paper:2603.18757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaohui-peng", "dst": "p2:paper:2603.18757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongwei-zhao", "dst": "p2:paper:2603.18757", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ling-li", "dst": "p2:paper:2603.18757", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.11503", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yanan-liu", "dst": "p2:paper:2512.11503", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-liu", "dst": "p2:paper:2512.11503", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-zhang", "dst": "p2:paper:2512.11503", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dan-xu", "dst": "p2:paper:2512.11503", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hossein-rahmani", "dst": "p2:paper:2512.11503", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohammed-bennamoun", "dst": "p2:paper:2512.11503", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qiuhong-ke", "dst": "p2:paper:2512.11503", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.05489", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hugo-pitorro", "dst": "p2:paper:2407.05489", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pavlo-vasylenko", "dst": "p2:paper:2407.05489", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marcos-treviso", "dst": "p2:paper:2407.05489", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andr-f-t-martins", "dst": "p2:paper:2407.05489", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.26912", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hyunji-lee", "dst": "p2:paper:2510.26912", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenhao-yu", "dst": "p2:paper:2510.26912", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongming-zhang", "dst": "p2:paper:2510.26912", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaixin-ma", "dst": "p2:paper:2510.26912", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiyeon-kim", "dst": "p2:paper:2510.26912", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dong-yu", "dst": "p2:paper:2510.26912", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:minjoon-seo", "dst": "p2:paper:2510.26912", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.08872", "dst": "p2:axis:attention", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hu-cui", "dst": "p2:paper:2511.08872", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenqiang-hua", "dst": "p2:paper:2511.08872", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:renjing-huang", "dst": "p2:paper:2511.08872", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shurui-jia", "dst": "p2:paper:2511.08872", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tessai-hayama", "dst": "p2:paper:2511.08872", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2109.04318", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:you-han", "dst": "p2:paper:2109.04318", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:achintya-gopal", "dst": "p2:paper:2109.04318", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liwen-ouyang", "dst": "p2:paper:2109.04318", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aaron-key", "dst": "p2:paper:2109.04318", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.19009", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:syed-mhamudul-hasan", "dst": "p2:paper:2403.19009", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abdur-r-shahid", "dst": "p2:paper:2403.19009", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ahmed-imteaj", "dst": "p2:paper:2403.19009", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2204.05149", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:david-patterson", "dst": "p2:paper:2204.05149", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joseph-gonzalez", "dst": "p2:paper:2204.05149", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:urs-h-lzle", "dst": "p2:paper:2204.05149", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:quoc-le", "dst": "p2:paper:2204.05149", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-liang", "dst": "p2:paper:2204.05149", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lluis-miquel-munguia", "dst": "p2:paper:2204.05149", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-rothchild", "dst": "p2:paper:2204.05149", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-so", "dst": "p2:paper:2204.05149", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2011.12443", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kyle-tilbury", "dst": "p2:paper:2011.12443", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jesse-hoey", "dst": "p2:paper:2011.12443", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.19724", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:saleem-abdul-fattah-ahmed-al-dajani", "dst": "p2:paper:2407.19724", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-keyes", "dst": "p2:paper:2407.19724", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2305.11164", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:joel-casta-o", "dst": "p2:paper:2305.11164", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:silverio-mart-nez-fern-ndez", "dst": "p2:paper:2305.11164", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xavier-franch", "dst": "p2:paper:2305.11164", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:justus-bogner", "dst": "p2:paper:2305.11164", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.02950", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhenxiao-fu", "dst": "p2:paper:2410.02950", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fan-chen", "dst": "p2:paper:2410.02950", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shan-zhou", "dst": "p2:paper:2410.02950", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haitong-li", "dst": "p2:paper:2410.02950", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-jiang", "dst": "p2:paper:2410.02950", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.17972", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:talha-mehboob", "dst": "p2:paper:2310.17972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:noman-bashir", "dst": "p2:paper:2310.17972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jesus-omana-iglesias", "dst": "p2:paper:2310.17972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-zink", "dst": "p2:paper:2310.17972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-irwin", "dst": "p2:paper:2310.17972", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2102.07627", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xinchi-qiu", "dst": "p2:paper:2102.07627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:titouan-parcollet", "dst": "p2:paper:2102.07627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:javier-fernandez-marques", "dst": "p2:paper:2102.07627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pedro-porto-buarque-de-gusmao", "dst": "p2:paper:2102.07627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yan-gao", "dst": "p2:paper:2102.07627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-j-beutel", "dst": "p2:paper:2102.07627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:taner-topal", "dst": "p2:paper:2102.07627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:akhil-mathur", "dst": "p2:paper:2102.07627", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2206.03227", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:altanai-bisht", "dst": "p2:paper:2206.03227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arielle-wilson", "dst": "p2:paper:2206.03227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zachary-jeffreys", "dst": "p2:paper:2206.03227", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shadrokh-samavi", "dst": "p2:paper:2206.03227", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1911.11658", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:victor-kristof", "dst": "p2:paper:1911.11658", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:valentin-quelquejay-lecl-re", "dst": "p2:paper:1911.11658", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:robin-zbinden", "dst": "p2:paper:1911.11658", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lucas-maystre", "dst": "p2:paper:1911.11658", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matthias-grossglauser", "dst": "p2:paper:1911.11658", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:patrick-thiran", "dst": "p2:paper:1911.11658", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.14393", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ahmad-faiz", "dst": "p2:paper:2309.14393", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sotaro-kaneda", "dst": "p2:paper:2309.14393", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruhan-wang", "dst": "p2:paper:2309.14393", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rita-osi", "dst": "p2:paper:2309.14393", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:prateek-sharma", "dst": "p2:paper:2309.14393", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fan-chen", "dst": "p2:paper:2309.14393", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-jiang", "dst": "p2:paper:2309.14393", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.14092", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:soumyendu-sarkar", "dst": "p2:paper:2403.14092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:avisek-naug", "dst": "p2:paper:2403.14092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ricardo-luna", "dst": "p2:paper:2403.14092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:antonio-guillen", "dst": "p2:paper:2403.14092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vineet-gundecha", "dst": "p2:paper:2403.14092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sahand-ghorbanpour", "dst": "p2:paper:2403.14092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sajad-mousavi", "dst": "p2:paper:2403.14092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dejan-markovikj", "dst": "p2:paper:2403.14092", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.10984", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:fan-chen", "dst": "p2:paper:2403.10984", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shahzeen-attari", "dst": "p2:paper:2403.10984", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gayle-buck", "dst": "p2:paper:2403.10984", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-jiang", "dst": "p2:paper:2403.10984", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2203.02202", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:raghavendra-selvan", "dst": "p2:paper:2203.02202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nikhil-bhagwat", "dst": "p2:paper:2203.02202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lasse-f-wolff-anthony", "dst": "p2:paper:2203.02202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:benjamin-kanding", "dst": "p2:paper:2203.02202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:erik-b-dam", "dst": "p2:paper:2203.02202", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1911.08354", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kadan-lottick", "dst": "p2:paper:1911.08354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:silvia-susai", "dst": "p2:paper:1911.08354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sorelle-a-friedler", "dst": "p2:paper:1911.08354", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jonathan-p-wilson", "dst": "p2:paper:1911.08354", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.05615", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lei-jiang", "dst": "p2:paper:2605.05615", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:adrian-ildefonso", "dst": "p2:paper:2605.05615", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-loveless", "dst": "p2:paper:2605.05615", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fan-chen", "dst": "p2:paper:2605.05615", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.02347", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qingzhong-li", "dst": "p2:paper:2604.02347", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yue-hu", "dst": "p2:paper:2604.02347", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhou-long", "dst": "p2:paper:2604.02347", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qingchang-ma", "dst": "p2:paper:2604.02347", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hui-ma", "dst": "p2:paper:2604.02347", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinhai-sa", "dst": "p2:paper:2604.02347", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.07853", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:andrew-antonopoulos", "dst": "p2:paper:2409.07853", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.11071", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:andrew-antonopoulos", "dst": "p2:paper:2409.11071", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.04642", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ashok-mondal", "dst": "p2:paper:2404.04642", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:satyam-singh", "dst": "p2:paper:2404.04642", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2002.05651", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:peter-henderson", "dst": "p2:paper:2002.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jieru-hu", "dst": "p2:paper:2002.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joshua-romoff", "dst": "p2:paper:2002.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:emma-brunskill", "dst": "p2:paper:2002.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dan-jurafsky", "dst": "p2:paper:2002.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joelle-pineau", "dst": "p2:paper:2002.05651", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.14505", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jaime-gonz-lez-gonz-lez", "dst": "p2:paper:2405.14505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:silvia-garc-a-m-ndez", "dst": "p2:paper:2405.14505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francisco-de-arriba-p-rez", "dst": "p2:paper:2405.14505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francisco-j-gonz-lez-casta-o", "dst": "p2:paper:2405.14505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:scar-barba-seara", "dst": "p2:paper:2405.14505", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2301.11899", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shvetank-prakash", "dst": "p2:paper:2301.11899", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matthew-stewart", "dst": "p2:paper:2301.11899", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:colby-banbury", "dst": "p2:paper:2301.11899", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mark-mazumder", "dst": "p2:paper:2301.11899", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pete-warden", "dst": "p2:paper:2301.11899", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:brian-plancher", "dst": "p2:paper:2301.11899", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vijay-janapa-reddi", "dst": "p2:paper:2301.11899", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2302.08476", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:alexandra-sasha-luccioni", "dst": "p2:paper:2302.08476", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alex-hernandez-garcia", "dst": "p2:paper:2302.08476", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.13001", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lukas-wegmeth", "dst": "p2:paper:2509.13001", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tobias-vente", "dst": "p2:paper:2509.13001", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alan-said", "dst": "p2:paper:2509.13001", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joeran-beel", "dst": "p2:paper:2509.13001", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2206.10380", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:stefano-savazzi", "dst": "p2:paper:2206.10380", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vittorio-rampa", "dst": "p2:paper:2206.10380", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sanaz-kianoush", "dst": "p2:paper:2206.10380", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mehdi-bennis", "dst": "p2:paper:2206.10380", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2107.06946", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:rakshit-naidu", "dst": "p2:paper:2107.06946", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:harshita-diddee", "dst": "p2:paper:2107.06946", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ajinkya-mulay", "dst": "p2:paper:2107.06946", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aleti-vardhan", "dst": "p2:paper:2107.06946", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:krithika-ramesh", "dst": "p2:paper:2107.06946", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ahmed-zamzam", "dst": "p2:paper:2107.06946", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.22092", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:raphael-fischer", "dst": "p2:paper:2509.22092", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2208.00406", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:semen-budennyy", "dst": "p2:paper:2208.00406", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vladimir-lazarev", "dst": "p2:paper:2208.00406", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nikita-zakharenko", "dst": "p2:paper:2208.00406", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexey-korovin", "dst": "p2:paper:2208.00406", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:olga-plosskaya", "dst": "p2:paper:2208.00406", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:denis-dimitrov", "dst": "p2:paper:2208.00406", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vladimir-arkhipkin", "dst": "p2:paper:2208.00406", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ivan-oseledets", "dst": "p2:paper:2208.00406", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.17683", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lara-hassan", "dst": "p2:paper:2511.17683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohamed-elzeftawy", "dst": "p2:paper:2511.17683", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abdulrahman-mahmoud", "dst": "p2:paper:2511.17683", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.08836", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:damien-fovet", "dst": "p2:paper:2507.08836", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shashank-chamoli", "dst": "p2:paper:2507.08836", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sarah-oury", "dst": "p2:paper:2507.08836", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:srishti-singhal", "dst": "p2:paper:2507.08836", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.13516", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tom-almog", "dst": "p2:paper:2509.13516", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.02754", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:pragati-kumari", "dst": "p2:paper:2604.02754", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:novarun-deb", "dst": "p2:paper:2604.02754", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.17442", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:marco-avolio", "dst": "p2:paper:2602.17442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:potito-aghilar", "dst": "p2:paper:2602.17442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sabino-roccotelli", "dst": "p2:paper:2602.17442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vito-walter-anelli", "dst": "p2:paper:2602.17442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chiara-mallamaci", "dst": "p2:paper:2602.17442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vincenzo-paparella", "dst": "p2:paper:2602.17442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marco-valentini", "dst": "p2:paper:2602.17442", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alejandro-bellog-n", "dst": "p2:paper:2602.17442", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.18012", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:pragati-kumari", "dst": "p2:paper:2602.18012", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:novarun-deb", "dst": "p2:paper:2602.18012", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.26712", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:andres-alonso-robisco", "dst": "p2:paper:2603.26712", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:carlos-esparcia", "dst": "p2:paper:2603.26712", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francisco-jare-o", "dst": "p2:paper:2603.26712", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.00343", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:austin-tapp", "dst": "p2:paper:2602.00343", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:holger-r-roth", "dst": "p2:paper:2602.00343", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ziyue-xu", "dst": "p2:paper:2602.00343", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abhijeet-parida", "dst": "p2:paper:2602.00343", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hareem-nisar", "dst": "p2:paper:2602.00343", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marius-george-linguraru", "dst": "p2:paper:2602.00343", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.00893", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kc-aashish", "dst": "p2:paper:2601.00893", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:md-zakir-hossain-zamil", "dst": "p2:paper:2601.00893", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:md-shafiqul-islam-mridul", "dst": "p2:paper:2601.00893", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lamia-akter", "dst": "p2:paper:2601.00893", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:farmina-sharmin", "dst": "p2:paper:2601.00893", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eftekhar-hossain-ayon", "dst": "p2:paper:2601.00893", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:md-maruf-bin-reza", "dst": "p2:paper:2601.00893", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ali-hassan", "dst": "p2:paper:2601.00893", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.19063", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:przemys-aw-spyra", "dst": "p2:paper:2509.19063", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.03054", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ciro-benito-raggio", "dst": "p2:paper:2512.03054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lucia-migliorelli", "dst": "p2:paper:2512.03054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nils-skupien", "dst": "p2:paper:2512.03054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mathias-krohmer-zabaleta", "dst": "p2:paper:2512.03054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:oliver-blanck", "dst": "p2:paper:2512.03054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francesco-cicone", "dst": "p2:paper:2512.03054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:giuseppe-lucio-cascini", "dst": "p2:paper:2512.03054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:paolo-zaffino", "dst": "p2:paper:2512.03054", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.14331", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wentao-yu", "dst": "p2:paper:2605.14331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vincent-w-s-wong", "dst": "p2:paper:2605.14331", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1611.07151", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mohammad-motamedi", "dst": "p2:paper:1611.07151", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-fong", "dst": "p2:paper:1611.07151", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:soheil-ghiasi", "dst": "p2:paper:1611.07151", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.09322", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yavar-taheri-yeganeh", "dst": "p2:paper:2406.09322", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mohsen-jafari", "dst": "p2:paper:2406.09322", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrea-matta", "dst": "p2:paper:2406.09322", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.12598", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ryan-quach", "dst": "p2:paper:2506.12598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yidi-wang", "dst": "p2:paper:2506.12598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ali-jahanshahi", "dst": "p2:paper:2506.12598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-wong", "dst": "p2:paper:2506.12598", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hyoseung-kim", "dst": "p2:paper:2506.12598", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.12590", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jihoon-park", "dst": "p2:paper:2508.12590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:seungeun-oh", "dst": "p2:paper:2508.12590", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:seong-lyun-kim", "dst": "p2:paper:2508.12590", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.29629", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ziyang-jia", "dst": "p2:paper:2606.29629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sara-rashidi-golrouye", "dst": "p2:paper:2606.29629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:laxmi-bhuyan", "dst": "p2:paper:2606.29629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:benjamin-kubwimana", "dst": "p2:paper:2606.29629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:devashree-tripathy", "dst": "p2:paper:2606.29629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zexin-li", "dst": "p2:paper:2606.29629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cong-liu", "dst": "p2:paper:2606.29629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-wong", "dst": "p2:paper:2606.29629", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2005.02544", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:young-geun-kim", "dst": "p2:paper:2005.02544", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:carole-jean-wu", "dst": "p2:paper:2005.02544", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.04865", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ziyang-zhang", "dst": "p2:paper:2503.04865", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-zhao", "dst": "p2:paper:2503.04865", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ming-ching-chang", "dst": "p2:paper:2503.04865", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:changyao-lin", "dst": "p2:paper:2503.04865", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jie-liu", "dst": "p2:paper:2503.04865", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.19209", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zheng-lin", "dst": "p2:paper:2404.19209", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bin-guo", "dst": "p2:paper:2404.19209", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sicong-liu", "dst": "p2:paper:2404.19209", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wentao-zhou", "dst": "p2:paper:2404.19209", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yasan-ding", "dst": "p2:paper:2404.19209", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-zhang", "dst": "p2:paper:2404.19209", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiwen-yu", "dst": "p2:paper:2404.19209", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.00298", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiacheng-yao", "dst": "p2:paper:2503.00298", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-xu", "dst": "p2:paper:2503.00298", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guangxu-zhu", "dst": "p2:paper:2503.00298", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaibin-huang", "dst": "p2:paper:2503.00298", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuguang-cui", "dst": "p2:paper:2503.00298", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.21908", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ziyang-zhang", "dst": "p2:paper:2603.21908", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zheshun-wu", "dst": "p2:paper:2603.21908", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jie-liu", "dst": "p2:paper:2603.21908", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luca-mottola", "dst": "p2:paper:2603.21908", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.18706", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chetna-singhal", "dst": "p2:paper:2503.18706", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yassine-hadjadj-aoul", "dst": "p2:paper:2503.18706", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.16627", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:arshia-kermani", "dst": "p2:paper:2502.16627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ehsan-zeraatkar", "dst": "p2:paper:2502.16627", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:habib-irani", "dst": "p2:paper:2502.16627", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.19257", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zekai-sun", "dst": "p2:paper:2405.19257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiuxian-guan", "dst": "p2:paper:2405.19257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junming-wang", "dst": "p2:paper:2405.19257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoze-song", "dst": "p2:paper:2405.19257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuhao-qing", "dst": "p2:paper:2405.19257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianxiang-shen", "dst": "p2:paper:2405.19257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dong-huang", "dst": "p2:paper:2405.19257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fangming-liu", "dst": "p2:paper:2405.19257", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.07036", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hasanul-mahmud", "dst": "p2:paper:2403.07036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peng-kang", "dst": "p2:paper:2403.07036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kevin-desai", "dst": "p2:paper:2403.07036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:palden-lama", "dst": "p2:paper:2403.07036", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sushil-prasad", "dst": "p2:paper:2403.07036", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2206.04685", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiangjie-li", "dst": "p2:paper:2206.04685", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chenfei-lou", "dst": "p2:paper:2206.04685", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhengping-zhu", "dst": "p2:paper:2206.04685", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuchi-chen", "dst": "p2:paper:2206.04685", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yingtao-shen", "dst": "p2:paper:2206.04685", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yehan-ma", "dst": "p2:paper:2206.04685", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:an-zou", "dst": "p2:paper:2206.04685", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.27032", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:katelyn-crumpacker", "dst": "p2:paper:2604.27032", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dimitrios-nikolopoulos", "dst": "p2:paper:2604.27032", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1805.07978", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:seongsik-park", "dst": "p2:paper:1805.07978", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jaehee-jang", "dst": "p2:paper:1805.07978", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:seijoon-kim", "dst": "p2:paper:1805.07978", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sungroh-yoon", "dst": "p2:paper:1805.07978", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2202.02015", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:joonghyun-song", "dst": "p2:paper:2202.02015", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiwon-shin", "dst": "p2:paper:2202.02015", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanseok-kim", "dst": "p2:paper:2202.02015", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:woo-seok-choi", "dst": "p2:paper:2202.02015", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2105.11848", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tao-luo", "dst": "p2:paper:2105.11848", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wai-teng-tang", "dst": "p2:paper:2105.11848", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matthew-kay-fei-lee", "dst": "p2:paper:2105.11848", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chuping-qu", "dst": "p2:paper:2105.11848", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weng-fai-wong", "dst": "p2:paper:2105.11848", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rick-goh", "dst": "p2:paper:2105.11848", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.00738", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:andy-he", "dst": "p2:paper:2405.00738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:darren-key", "dst": "p2:paper:2405.00738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mason-bulling", "dst": "p2:paper:2405.00738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrew-chang", "dst": "p2:paper:2405.00738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:skyler-shapiro", "dst": "p2:paper:2405.00738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:everett-lee", "dst": "p2:paper:2405.00738", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1810.02068", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:cheng-fu", "dst": "p2:paper:1810.02068", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shilin-zhu", "dst": "p2:paper:1810.02068", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-su", "dst": "p2:paper:1810.02068", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ching-en-lee", "dst": "p2:paper:1810.02068", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jishen-zhao", "dst": "p2:paper:1810.02068", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1910.05340", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:skanda-koppula", "dst": "p2:paper:1910.05340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lois-orosa", "dst": "p2:paper:1910.05340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abdullah-giray-ya-l-k", "dst": "p2:paper:1910.05340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:roknoddin-azizi", "dst": "p2:paper:1910.05340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:taha-shahroodi", "dst": "p2:paper:1910.05340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:konstantinos-kanellopoulos", "dst": "p2:paper:1910.05340", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:onur-mutlu", "dst": "p2:paper:1910.05340", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1907.12475", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kai-yang", "dst": "p2:paper:1907.12475", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuanming-shi", "dst": "p2:paper:1907.12475", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-yu", "dst": "p2:paper:1907.12475", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhi-ding", "dst": "p2:paper:1907.12475", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.05640", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shengyu-duan", "dst": "p2:paper:2502.05640", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rishad-shafik", "dst": "p2:paper:2502.05640", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alex-yakovlev", "dst": "p2:paper:2502.05640", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.23166", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nursultan-amanzhol", "dst": "p2:paper:2511.23166", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jurn-gyu-park", "dst": "p2:paper:2511.23166", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.03194", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:james-malkin", "dst": "p2:paper:2309.03194", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cian-o-donnell", "dst": "p2:paper:2309.03194", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:conor-houghton", "dst": "p2:paper:2309.03194", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:laurence-aitchison", "dst": "p2:paper:2309.03194", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2306.09789", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:francesco-daghero", "dst": "p2:paper:2306.09789", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alessio-burrello", "dst": "p2:paper:2306.09789", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:enrico-macii", "dst": "p2:paper:2306.09789", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:paolo-montuschi", "dst": "p2:paper:2306.09789", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:massimo-poncino", "dst": "p2:paper:2306.09789", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniele-jahier-pagliari", "dst": "p2:paper:2306.09789", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2108.12648", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:m-matuszewski", "dst": "p2:paper:2108.12648", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:a-opala", "dst": "p2:paper:2108.12648", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:r-mirek", "dst": "p2:paper:2108.12648", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:m-furman", "dst": "p2:paper:2108.12648", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:m-kr-l", "dst": "p2:paper:2108.12648", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:k-tyszka", "dst": "p2:paper:2108.12648", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:t-c-h-liew", "dst": "p2:paper:2108.12648", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:d-ballarini", "dst": "p2:paper:2108.12648", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2205.15062", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chen-li", "dst": "p2:paper:2205.15062", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:antonios-tsourdos", "dst": "p2:paper:2205.15062", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weisi-guo", "dst": "p2:paper:2205.15062", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2307.00368", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dario-lazzaro", "dst": "p2:paper:2307.00368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:antonio-emanuele-cin", "dst": "p2:paper:2307.00368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:maura-pintor", "dst": "p2:paper:2307.00368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ambra-demontis", "dst": "p2:paper:2307.00368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:battista-biggio", "dst": "p2:paper:2307.00368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fabio-roli", "dst": "p2:paper:2307.00368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marcello-pelillo", "dst": "p2:paper:2307.00368", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2307.05520", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:santiago-del-rey", "dst": "p2:paper:2307.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-s-cruz", "dst": "p2:paper:2307.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xavier-franch", "dst": "p2:paper:2307.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:silverio-mart-nez-fern-ndez", "dst": "p2:paper:2307.05520", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2111.12861", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ayman-moawad", "dst": "p2:paper:2111.12861", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:krishna-murthy-gurumurthy", "dst": "p2:paper:2111.12861", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:omer-verbas", "dst": "p2:paper:2111.12861", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhijian-li", "dst": "p2:paper:2111.12861", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ehsan-islam", "dst": "p2:paper:2111.12861", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vincent-freyermuth", "dst": "p2:paper:2111.12861", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aymeric-rousseau", "dst": "p2:paper:2111.12861", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2207.01595", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nuno-oliveira", "dst": "p2:paper:2207.01595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:norberto-sousa", "dst": "p2:paper:2207.01595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:isabel-pra-a", "dst": "p2:paper:2207.01595", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.06195", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:taoran-wang", "dst": "p2:paper:2603.06195", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanhui-li", "dst": "p2:paper:2603.06195", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingliang-ma", "dst": "p2:paper:2603.06195", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lin-chen", "dst": "p2:paper:2603.06195", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuming-zhou", "dst": "p2:paper:2603.06195", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.08644", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:punit-kumar", "dst": "p2:paper:2511.08644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:asif-imran", "dst": "p2:paper:2511.08644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tevfik-kosar", "dst": "p2:paper:2511.08644", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2501.06099", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mohammad-noorchenarboo", "dst": "p2:paper:2501.06099", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:katarina-grolinger", "dst": "p2:paper:2501.06099", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2108.13465", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:bo-li", "dst": "p2:paper:2108.13465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyang-jiang", "dst": "p2:paper:2108.13465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:donglin-bai", "dst": "p2:paper:2108.13465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuge-zhang", "dst": "p2:paper:2108.13465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ningxin-zheng", "dst": "p2:paper:2108.13465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuanyi-dong", "dst": "p2:paper:2108.13465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-liu", "dst": "p2:paper:2108.13465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuqing-yang", "dst": "p2:paper:2108.13465", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2212.00582", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:danilo-carastan-dos-santos", "dst": "p2:paper:2212.00582", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2203.08630", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shiliang-zhang", "dst": "p2:paper:2203.08630", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dyako-fatih", "dst": "p2:paper:2203.08630", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fahmi-abdulqadir", "dst": "p2:paper:2203.08630", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tobias-schwarz", "dst": "p2:paper:2203.08630", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuehui-ma", "dst": "p2:paper:2203.08630", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2107.02621", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:constance-douwes", "dst": "p2:paper:2107.02621", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:philippe-esling", "dst": "p2:paper:2107.02621", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jean-pierre-briot", "dst": "p2:paper:2107.02621", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1810.10090", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:biyi-fang", "dst": "p2:paper:1810.10090", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiao-zeng", "dst": "p2:paper:1810.10090", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mi-zhang", "dst": "p2:paper:1810.10090", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2210.06015", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:pedram-bakhtiarifard", "dst": "p2:paper:2210.06015", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christian-igel", "dst": "p2:paper:2210.06015", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:raghavendra-selvan", "dst": "p2:paper:2210.06015", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2207.06883", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ronald-davis", "dst": "p2:paper:2207.06883", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zaijun-chen", "dst": "p2:paper:2207.06883", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ryan-hamerly", "dst": "p2:paper:2207.06883", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dirk-englund", "dst": "p2:paper:2207.06883", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2206.01609", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:carlos-muli", "dst": "p2:paper:2206.01609", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sangyoung-park", "dst": "p2:paper:2206.01609", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingming-liu", "dst": "p2:paper:2206.01609", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.08763", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:constance-douwes", "dst": "p2:paper:2409.08763", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:romain-serizel", "dst": "p2:paper:2409.08763", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2212.01698", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ren-caspart", "dst": "p2:paper:2212.01698", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sebastian-ziegler", "dst": "p2:paper:2212.01698", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arvid-weyrauch", "dst": "p2:paper:2212.01698", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:holger-obermaier", "dst": "p2:paper:2212.01698", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:simon-raffeiner", "dst": "p2:paper:2212.01698", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:leon-pascal-schuhmacher", "dst": "p2:paper:2212.01698", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jan-scholtyssek", "dst": "p2:paper:2212.01698", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:darya-trofimova", "dst": "p2:paper:2212.01698", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.14107", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:robert-spencer", "dst": "p2:paper:2410.14107", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:surangika-ranathunga", "dst": "p2:paper:2410.14107", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mikael-boulic", "dst": "p2:paper:2410.14107", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andries-van-heerden", "dst": "p2:paper:2410.14107", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:teo-susnjak", "dst": "p2:paper:2410.14107", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2303.01980", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:vanessa-mehlin", "dst": "p2:paper:2303.01980", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sigurd-schacht", "dst": "p2:paper:2303.01980", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:carsten-lanquillon", "dst": "p2:paper:2303.01980", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2207.11953", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:viorica-rozina-chifu", "dst": "p2:paper:2207.11953", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cristina-bianca-pop", "dst": "p2:paper:2207.11953", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:emil-st-chifu", "dst": "p2:paper:2207.11953", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:horatiu-barleanu", "dst": "p2:paper:2207.11953", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.17110", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:abhishek-maity", "dst": "p2:paper:2601.17110", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:viraj-tukarul", "dst": "p2:paper:2601.17110", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2210.01625", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:seyyidahmed-lahmer", "dst": "p2:paper:2210.01625", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aria-khoshsirat", "dst": "p2:paper:2210.01625", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michele-rossi", "dst": "p2:paper:2210.01625", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrea-zanella", "dst": "p2:paper:2210.01625", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2304.00897", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:johannes-getzner", "dst": "p2:paper:2304.00897", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bertrand-charpentier", "dst": "p2:paper:2304.00897", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stephan-g-nnemann", "dst": "p2:paper:2304.00897", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1906.04278", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jie-liu", "dst": "p2:paper:1906.04278", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiawen-liu", "dst": "p2:paper:1906.04278", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wan-du", "dst": "p2:paper:1906.04278", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dong-li", "dst": "p2:paper:1906.04278", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.14421", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shourya-bose", "dst": "p2:paper:2411.14421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yijiang-li", "dst": "p2:paper:2411.14421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:amy-van-sant", "dst": "p2:paper:2411.14421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-zhang", "dst": "p2:paper:2411.14421", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kibaek-kim", "dst": "p2:paper:2411.14421", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.06522", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shreyank-n-gowda", "dst": "p2:paper:2310.06522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyue-hao", "dst": "p2:paper:2310.06522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gen-li", "dst": "p2:paper:2310.06522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shashank-narayana-gowda", "dst": "p2:paper:2310.06522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaobo-jin", "dst": "p2:paper:2310.06522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:laura-sevilla-lara", "dst": "p2:paper:2310.06522", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.08151", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:charles-edison-tripp", "dst": "p2:paper:2403.08151", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jordan-perr-sauer", "dst": "p2:paper:2403.08151", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jamil-gafur", "dst": "p2:paper:2403.08151", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:amabarish-nag", "dst": "p2:paper:2403.08151", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:avi-purkayastha", "dst": "p2:paper:2403.08151", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sagi-zisman", "dst": "p2:paper:2403.08151", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:erik-a-bensen", "dst": "p2:paper:2403.08151", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.16929", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tingwei-chen", "dst": "p2:paper:2406.16929", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yantao-wang", "dst": "p2:paper:2406.16929", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanzhi-chen", "dst": "p2:paper:2406.16929", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zijian-zhao", "dst": "p2:paper:2406.16929", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinhao-li", "dst": "p2:paper:2406.16929", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nicola-piovesan", "dst": "p2:paper:2406.16929", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guangxu-zhu", "dst": "p2:paper:2406.16929", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qingjiang-shi", "dst": "p2:paper:2406.16929", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2007.03828", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:a-l-peirson", "dst": "p2:paper:2007.03828", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:r-w-romani", "dst": "p2:paper:2007.03828", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:h-l-marshall", "dst": "p2:paper:2007.03828", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:j-f-steiner", "dst": "p2:paper:2007.03828", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:l-baldini", "dst": "p2:paper:2007.03828", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2205.12961", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:eva-memmel", "dst": "p2:paper:2205.12961", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:clara-menzen", "dst": "p2:paper:2205.12961", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jetze-schuurmans", "dst": "p2:paper:2205.12961", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:frederiek-wesel", "dst": "p2:paper:2205.12961", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kim-batselier", "dst": "p2:paper:2205.12961", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.12262", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ripal-ranpara", "dst": "p2:paper:2506.12262", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2303.13972", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tim-yarally", "dst": "p2:paper:2303.13972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-s-cruz", "dst": "p2:paper:2303.13972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-feitosa", "dst": "p2:paper:2303.13972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:june-sallou", "dst": "p2:paper:2303.13972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arie-van-deursen", "dst": "p2:paper:2303.13972", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.04736", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qijiong-liu", "dst": "p2:paper:2403.04736", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jieming-zhu", "dst": "p2:paper:2403.04736", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:quanyu-dai", "dst": "p2:paper:2403.04736", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiao-ming-wu", "dst": "p2:paper:2403.04736", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.14707", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuxin-chen", "dst": "p2:paper:2606.14707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-gao", "dst": "p2:paper:2606.14707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chujie-zou", "dst": "p2:paper:2606.14707", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.07317", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ashmita-sampatsing", "dst": "p2:paper:2505.07317", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sophie-vos", "dst": "p2:paper:2505.07317", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:emma-beauxis-aussalet", "dst": "p2:paper:2505.07317", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:justus-bogner", "dst": "p2:paper:2505.07317", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.13192", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kai-huang", "dst": "p2:paper:2309.13192", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanyun-yin", "dst": "p2:paper:2309.13192", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:heng-huang", "dst": "p2:paper:2309.13192", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-gao", "dst": "p2:paper:2309.13192", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2401.06195", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:soyed-tuhin-ahmed", "dst": "p2:paper:2401.06195", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kamal-danouchi", "dst": "p2:paper:2401.06195", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guillaume-prenat", "dst": "p2:paper:2401.06195", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lorena-anghel", "dst": "p2:paper:2401.06195", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mehdi-b-tahoori", "dst": "p2:paper:2401.06195", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2204.02766", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:roberto-verdecchia", "dst": "p2:paper:2204.02766", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-s-cruz", "dst": "p2:paper:2204.02766", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:june-sallou", "dst": "p2:paper:2204.02766", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michelle-lin", "dst": "p2:paper:2204.02766", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:james-wickenden", "dst": "p2:paper:2204.02766", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:estelle-hotellier", "dst": "p2:paper:2204.02766", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.17451", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nienke-nijkamp", "dst": "p2:paper:2405.17451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:june-sallou", "dst": "p2:paper:2405.17451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:niels-van-der-heijden", "dst": "p2:paper:2405.17451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-s-cruz", "dst": "p2:paper:2405.17451", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.01752", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:khairun-saddami", "dst": "p2:paper:2408.01752", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yudha-nurdin", "dst": "p2:paper:2408.01752", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mutia-zahramita", "dst": "p2:paper:2408.01752", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:muhammad-shahreeza-safiruz", "dst": "p2:paper:2408.01752", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2307.09964", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:silverio-mart-nez-fern-ndez", "dst": "p2:paper:2307.09964", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xavier-franch", "dst": "p2:paper:2307.09964", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francisco-dur-n", "dst": "p2:paper:2307.09964", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.02250", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tao-yu", "dst": "p2:paper:2509.02250", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaixuan-huang", "dst": "p2:paper:2509.02250", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tengsheng-wang", "dst": "p2:paper:2509.02250", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jihong-li", "dst": "p2:paper:2509.02250", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shunqing-zhang", "dst": "p2:paper:2509.02250", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuangfeng-han", "dst": "p2:paper:2509.02250", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoyun-wang", "dst": "p2:paper:2509.02250", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qunsong-zeng", "dst": "p2:paper:2509.02250", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.08069", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:pedro-pereira", "dst": "p2:paper:2411.08069", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:paulo-mendes", "dst": "p2:paper:2411.08069", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jo-o-vitorino", "dst": "p2:paper:2411.08069", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eva-maia", "dst": "p2:paper:2411.08069", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:isabel-pra-a", "dst": "p2:paper:2411.08069", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2103.15429", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:robert-schwarzenberg", "dst": "p2:paper:2103.15429", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nils-feldhus", "dst": "p2:paper:2103.15429", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sebastian-m-ller", "dst": "p2:paper:2103.15429", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.02914", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:rafiullah-omar", "dst": "p2:paper:2407.02914", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:justus-bogner", "dst": "p2:paper:2407.02914", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:henry-muccini", "dst": "p2:paper:2407.02914", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:patricia-lago", "dst": "p2:paper:2407.02914", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:silverio-mart-nez-fern-ndez", "dst": "p2:paper:2407.02914", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xavier-franch", "dst": "p2:paper:2407.02914", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.00924", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ernesto-l-estevanell-valladares", "dst": "p2:paper:2508.00924", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:suilan-estevez-velarde", "dst": "p2:paper:2508.00924", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yoan-guti-rrez", "dst": "p2:paper:2508.00924", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andr-s-montoyo", "dst": "p2:paper:2508.00924", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruslan-mitkov", "dst": "p2:paper:2508.00924", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.12010", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mohammed-alswaitti", "dst": "p2:paper:2402.12010", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:roberto-verdecchia", "dst": "p2:paper:2402.12010", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gr-goire-danoy", "dst": "p2:paper:2402.12010", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pascal-bouvry", "dst": "p2:paper:2402.12010", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:johnatan-pecero", "dst": "p2:paper:2402.12010", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.07001", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:farzaneh-pourahmadi", "dst": "p2:paper:2512.07001", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:olivier-corradi", "dst": "p2:paper:2512.07001", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pierre-pinson", "dst": "p2:paper:2512.07001", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.00240", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:md-muhtasim-munif-fahim", "dst": "p2:paper:2602.00240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:soyda-humyra-yesmin", "dst": "p2:paper:2602.00240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:saiful-islam", "dst": "p2:paper:2602.00240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:md-palash-bin-faruque", "dst": "p2:paper:2602.00240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:md-a-salam", "dst": "p2:paper:2602.00240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:md-mahfuz-uddin", "dst": "p2:paper:2602.00240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:samiul-islam", "dst": "p2:paper:2602.00240", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tofayel-ahmed", "dst": "p2:paper:2602.00240", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.21418", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mariela-m-nina", "dst": "p2:paper:2603.21418", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:caio-veloso-costa", "dst": "p2:paper:2603.21418", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lilian-berton", "dst": "p2:paper:2603.21418", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:didier-a-vega-oliveros", "dst": "p2:paper:2603.21418", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.02810", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hemang-jain", "dst": "p2:paper:2510.02810", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shailender-goyal", "dst": "p2:paper:2510.02810", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:divyansh-pandey", "dst": "p2:paper:2510.02810", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:karthik-vaidhyanathan", "dst": "p2:paper:2510.02810", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2307.11434", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tim-yarally", "dst": "p2:paper:2307.11434", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-s-cruz", "dst": "p2:paper:2307.11434", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-feitosa", "dst": "p2:paper:2307.11434", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:june-sallou", "dst": "p2:paper:2307.11434", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arie-van-deursen", "dst": "p2:paper:2307.11434", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2312.05795", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:maolin-wang", "dst": "p2:paper:2312.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yao-zhao", "dst": "p2:paper:2312.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiajia-liu", "dst": "p2:paper:2312.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingdong-chen", "dst": "p2:paper:2312.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chenyi-zhuang", "dst": "p2:paper:2312.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinjie-gu", "dst": "p2:paper:2312.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruocheng-guo", "dst": "p2:paper:2312.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiangyu-zhao", "dst": "p2:paper:2312.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2305.08197", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ayman-elhalwagy", "dst": "p2:paper:2305.08197", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tatiana-kalganova", "dst": "p2:paper:2305.08197", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2106.07597", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:colby-banbury", "dst": "p2:paper:2106.07597", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vijay-janapa-reddi", "dst": "p2:paper:2106.07597", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peter-torelli", "dst": "p2:paper:2106.07597", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jeremy-holleman", "dst": "p2:paper:2106.07597", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nat-jeffries", "dst": "p2:paper:2106.07597", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:csaba-kiraly", "dst": "p2:paper:2106.07597", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pietro-montino", "dst": "p2:paper:2106.07597", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-kanter", "dst": "p2:paper:2106.07597", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.12032", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:arya-tschand", "dst": "p2:paper:2410.12032", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arun-tejusve-raghunath-rajan", "dst": "p2:paper:2410.12032", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sachin-idgunji", "dst": "p2:paper:2410.12032", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anirban-ghosh", "dst": "p2:paper:2410.12032", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jeremy-holleman", "dst": "p2:paper:2410.12032", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:csaba-kiraly", "dst": "p2:paper:2410.12032", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pawan-ambalkar", "dst": "p2:paper:2410.12032", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ritika-borkar", "dst": "p2:paper:2410.12032", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1911.02549", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:vijay-janapa-reddi", "dst": "p2:paper:1911.02549", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christine-cheng", "dst": "p2:paper:1911.02549", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-kanter", "dst": "p2:paper:1911.02549", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peter-mattson", "dst": "p2:paper:1911.02549", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guenther-schmuelling", "dst": "p2:paper:1911.02549", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:carole-jean-wu", "dst": "p2:paper:1911.02549", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:brian-anderson", "dst": "p2:paper:1911.02549", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:maximilien-breughe", "dst": "p2:paper:1911.02549", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.16791", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:grigori-fursin", "dst": "p2:paper:2406.16791", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.27704", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:robi-paul", "dst": "p2:paper:2606.27704", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-zuzak", "dst": "p2:paper:2606.27704", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2206.00302", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:matteo-risso", "dst": "p2:paper:2206.00302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alessio-burrello", "dst": "p2:paper:2206.00302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luca-benini", "dst": "p2:paper:2206.00302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:enrico-macii", "dst": "p2:paper:2206.00302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:massimo-poncino", "dst": "p2:paper:2206.00302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniele-jahier-pagliari", "dst": "p2:paper:2206.00302", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2008.07141", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhixiang-ren", "dst": "p2:paper:2008.07141", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongheng-liu", "dst": "p2:paper:2008.07141", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianhui-shi", "dst": "p2:paper:2008.07141", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-xie", "dst": "p2:paper:2008.07141", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yue-zhou", "dst": "p2:paper:2008.07141", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jidong-zhai", "dst": "p2:paper:2008.07141", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:youhui-zhang", "dst": "p2:paper:2008.07141", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yunquan-zhang", "dst": "p2:paper:2008.07141", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2105.09187", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:adri-n-castell", "dst": "p2:paper:2105.09187", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sergio-barrachina", "dst": "p2:paper:2105.09187", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:manuel-f-dolz", "dst": "p2:paper:2105.09187", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:enrique-s-quintana-ort", "dst": "p2:paper:2105.09187", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pau-san-juan", "dst": "p2:paper:2105.09187", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.07217", "dst": "p2:axis:energy", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:alessio-burrello", "dst": "p2:paper:2310.07217", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matteo-risso", "dst": "p2:paper:2310.07217", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:beatrice-alessandra-motetti", "dst": "p2:paper:2310.07217", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:enrico-macii", "dst": "p2:paper:2310.07217", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luca-benini", "dst": "p2:paper:2310.07217", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniele-jahier-pagliari", "dst": "p2:paper:2310.07217", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2207.08536", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zequn-qin", "dst": "p2:paper:2207.08536", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingyu-chen", "dst": "p2:paper:2207.08536", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chao-chen", "dst": "p2:paper:2207.08536", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaozhi-chen", "dst": "p2:paper:2207.08536", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xi-li", "dst": "p2:paper:2207.08536", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.05257", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chunyong-hu", "dst": "p2:paper:2309.05257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hang-zheng", "dst": "p2:paper:2309.05257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kun-li", "dst": "p2:paper:2309.05257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianyun-xu", "dst": "p2:paper:2309.05257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weibo-mao", "dst": "p2:paper:2309.05257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:maochun-luo", "dst": "p2:paper:2309.05257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lingxuan-wang", "dst": "p2:paper:2309.05257", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingxia-chen", "dst": "p2:paper:2309.05257", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.15465", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lukas-st-cker", "dst": "p2:paper:2309.15465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:philipp-heidenreich", "dst": "p2:paper:2309.15465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jason-rambach", "dst": "p2:paper:2309.15465", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:didier-stricker", "dst": "p2:paper:2309.15465", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.05623", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:trung-tien-dong", "dst": "p2:paper:2603.05623", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dev-thakkar", "dst": "p2:paper:2603.05623", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arman-sargolzaei", "dst": "p2:paper:2603.05623", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaomin-lin", "dst": "p2:paper:2603.05623", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.06008", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:donghao-qiao", "dst": "p2:paper:2310.06008", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:farhana-zulkernine", "dst": "p2:paper:2310.06008", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.03381", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:maryem-fadili", "dst": "p2:paper:2507.03381", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:louis-lecrosnier", "dst": "p2:paper:2507.03381", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:steve-pechberti", "dst": "p2:paper:2507.03381", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:redouane-khemmar", "dst": "p2:paper:2507.03381", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2303.17099", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hongxiang-cai", "dst": "p2:paper:2303.17099", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zeyuan-zhang", "dst": "p2:paper:2303.17099", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenyu-zhou", "dst": "p2:paper:2303.17099", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ziyin-li", "dst": "p2:paper:2303.17099", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenbo-ding", "dst": "p2:paper:2303.17099", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiuhua-zhao", "dst": "p2:paper:2303.17099", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2306.04540", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xi-zhu", "dst": "p2:paper:2306.04540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiya-cao", "dst": "p2:paper:2306.04540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiwei-dong", "dst": "p2:paper:2306.04540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:caifa-zhou", "dst": "p2:paper:2306.04540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qiangbo-liu", "dst": "p2:paper:2306.04540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-li", "dst": "p2:paper:2306.04540", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongliang-wang", "dst": "p2:paper:2306.04540", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.00637", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:arindam-das", "dst": "p2:paper:2402.00637", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sudarshan-paul", "dst": "p2:paper:2402.00637", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:niko-scholz", "dst": "p2:paper:2402.00637", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:akhilesh-kumar-malviya", "dst": "p2:paper:2402.00637", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ganesh-sistu", "dst": "p2:paper:2402.00637", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ujjwal-bhattacharya", "dst": "p2:paper:2402.00637", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ciar-n-eising", "dst": "p2:paper:2402.00637", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2104.10490", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:anthony-hu", "dst": "p2:paper:2104.10490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zak-murez", "dst": "p2:paper:2104.10490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nikhil-mohan", "dst": "p2:paper:2104.10490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sof-a-dudas", "dst": "p2:paper:2104.10490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jeffrey-hawke", "dst": "p2:paper:2104.10490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vijay-badrinarayanan", "dst": "p2:paper:2104.10490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:roberto-cipolla", "dst": "p2:paper:2104.10490", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alex-kendall", "dst": "p2:paper:2104.10490", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2205.13542", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhijian-liu", "dst": "p2:paper:2205.13542", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haotian-tang", "dst": "p2:paper:2205.13542", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexander-amini", "dst": "p2:paper:2205.13542", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyu-yang", "dst": "p2:paper:2205.13542", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huizi-mao", "dst": "p2:paper:2205.13542", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniela-rus", "dst": "p2:paper:2205.13542", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:song-han", "dst": "p2:paper:2205.13542", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.11119", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:minsu-kim", "dst": "p2:paper:2309.11119", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:giseop-kim", "dst": "p2:paper:2309.11119", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kyong-hwan-jin", "dst": "p2:paper:2309.11119", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sunwook-choi", "dst": "p2:paper:2309.11119", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2305.15883", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lukas-st-cker", "dst": "p2:paper:2305.15883", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shashank-mishra", "dst": "p2:paper:2305.15883", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:philipp-heidenreich", "dst": "p2:paper:2305.15883", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jason-rambach", "dst": "p2:paper:2305.15883", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:didier-stricker", "dst": "p2:paper:2305.15883", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.24688", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yun-zhang", "dst": "p2:paper:2510.24688", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhaoliang-zheng", "dst": "p2:paper:2510.24688", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:johnson-liu", "dst": "p2:paper:2510.24688", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiyu-huang", "dst": "p2:paper:2510.24688", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zewei-zhou", "dst": "p2:paper:2510.24688", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zonglin-meng", "dst": "p2:paper:2510.24688", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianhui-cai", "dst": "p2:paper:2510.24688", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaqi-ma", "dst": "p2:paper:2510.24688", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2308.06530", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:miaoyu-li", "dst": "p2:paper:2308.06530", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yachao-zhang", "dst": "p2:paper:2308.06530", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xu-ma", "dst": "p2:paper:2308.06530", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanyun-qu", "dst": "p2:paper:2308.06530", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yun-fu", "dst": "p2:paper:2308.06530", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.07268", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuxin-li", "dst": "p2:paper:2410.07268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yiheng-li", "dst": "p2:paper:2410.07268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xulei-yang", "dst": "p2:paper:2410.07268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mengying-yu", "dst": "p2:paper:2410.07268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zihang-huang", "dst": "p2:paper:2410.07268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaojun-wu", "dst": "p2:paper:2410.07268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chai-kiat-yeo", "dst": "p2:paper:2410.07268", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2206.13294", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:florent-bartoccioni", "dst": "p2:paper:2206.13294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:loi-zablocki", "dst": "p2:paper:2206.13294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrei-bursuc", "dst": "p2:paper:2206.13294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:patrick-p-rez", "dst": "p2:paper:2206.13294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matthieu-cord", "dst": "p2:paper:2206.13294", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:karteek-alahari", "dst": "p2:paper:2206.13294", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.13350", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:torben-teepe", "dst": "p2:paper:2310.13350", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:philipp-wolters", "dst": "p2:paper:2310.13350", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:johannes-gilg", "dst": "p2:paper:2310.13350", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fabian-herzog", "dst": "p2:paper:2310.13350", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gerhard-rigoll", "dst": "p2:paper:2310.13350", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2209.05324", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hongyang-li", "dst": "p2:paper:2209.05324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chonghao-sima", "dst": "p2:paper:2209.05324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jifeng-dai", "dst": "p2:paper:2209.05324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenhai-wang", "dst": "p2:paper:2209.05324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lewei-lu", "dst": "p2:paper:2209.05324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huijie-wang", "dst": "p2:paper:2209.05324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jia-zeng", "dst": "p2:paper:2209.05324", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiqi-li", "dst": "p2:paper:2209.05324", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.15241", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:junbo-yin", "dst": "p2:paper:2403.15241", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianbing-shen", "dst": "p2:paper:2403.15241", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:runnan-chen", "dst": "p2:paper:2403.15241", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-li", "dst": "p2:paper:2403.15241", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruigang-yang", "dst": "p2:paper:2403.15241", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pascal-frossard", "dst": "p2:paper:2403.15241", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenguan-wang", "dst": "p2:paper:2403.15241", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.19082", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiawei-hou", "dst": "p2:paper:2512.19082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peng-yang", "dst": "p2:paper:2512.19082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiangxiang-dai", "dst": "p2:paper:2512.19082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingliu-liu", "dst": "p2:paper:2512.19082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:conghao-zhou", "dst": "p2:paper:2512.19082", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.13311", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kavin-chandrasekaran", "dst": "p2:paper:2411.13311", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sorin-grigorescu", "dst": "p2:paper:2411.13311", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gijs-dubbelman", "dst": "p2:paper:2411.13311", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pavol-jancura", "dst": "p2:paper:2411.13311", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.08180", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ye-li", "dst": "p2:paper:2309.08180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenchao-yang", "dst": "p2:paper:2309.08180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dekun-lin", "dst": "p2:paper:2309.08180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qianlei-wang", "dst": "p2:paper:2309.08180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhe-cui", "dst": "p2:paper:2309.08180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaolin-qin", "dst": "p2:paper:2309.08180", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.10577", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhe-huang", "dst": "p2:paper:2405.10577", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yizhe-zhao", "dst": "p2:paper:2405.10577", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-xiao", "dst": "p2:paper:2405.10577", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chenyan-wu", "dst": "p2:paper:2405.10577", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lingting-ge", "dst": "p2:paper:2405.10577", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2306.03810", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shubhankar-borse", "dst": "p2:paper:2306.03810", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:senthil-yogamani", "dst": "p2:paper:2306.03810", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marvin-klingner", "dst": "p2:paper:2306.03810", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:varun-ravi", "dst": "p2:paper:2306.03810", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hong-cai", "dst": "p2:paper:2306.03810", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abdulaziz-almuzairee", "dst": "p2:paper:2306.03810", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fatih-porikli", "dst": "p2:paper:2306.03810", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.08644", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:junho-koh", "dst": "p2:paper:2507.08644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:youngwoo-lee", "dst": "p2:paper:2507.08644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jungho-kim", "dst": "p2:paper:2507.08644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dongyoung-lee", "dst": "p2:paper:2507.08644", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-won-choi", "dst": "p2:paper:2507.08644", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2210.06778", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shubhankar-borse", "dst": "p2:paper:2210.06778", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marvin-klingner", "dst": "p2:paper:2210.06778", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:varun-ravi-kumar", "dst": "p2:paper:2210.06778", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hong-cai", "dst": "p2:paper:2210.06778", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abdulaziz-almuzairee", "dst": "p2:paper:2210.06778", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:senthil-yogamani", "dst": "p2:paper:2210.06778", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fatih-porikli", "dst": "p2:paper:2210.06778", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.09077", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mariusz-wisniewski", "dst": "p2:paper:2411.09077", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zeeshan-a-rana", "dst": "p2:paper:2411.09077", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ivan-petrunin", "dst": "p2:paper:2411.09077", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alan-holt", "dst": "p2:paper:2411.09077", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stephen-harman", "dst": "p2:paper:2411.09077", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2212.01436", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:muhammad-asif-khan", "dst": "p2:paper:2212.01436", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hamid-menouar", "dst": "p2:paper:2212.01436", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:osama-muhammad-khalid", "dst": "p2:paper:2212.01436", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:adnan-abu-dayya", "dst": "p2:paper:2212.01436", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2007.07396", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:fredrik-svanstrom", "dst": "p2:paper:2007.07396", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cristofer-englund", "dst": "p2:paper:2007.07396", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fernando-alonso-fernandez", "dst": "p2:paper:2007.07396", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2111.12389", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:fatih-cagatay-akyon", "dst": "p2:paper:2111.12389", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ogulcan-eryuksel", "dst": "p2:paper:2111.12389", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kamil-anil-ozfuttu", "dst": "p2:paper:2111.12389", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sinan-onur-altinuc", "dst": "p2:paper:2111.12389", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.07259", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiguang-he", "dst": "p2:paper:2402.07259", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aymen-fakhreddine", "dst": "p2:paper:2402.07259", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:george-c-alexandropoulos", "dst": "p2:paper:2402.07259", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2306.06797", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jaskaran-singh", "dst": "p2:paper:2306.06797", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.18624", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:stefan-gl-ge", "dst": "p2:paper:2406.18624", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matthias-nyfeler", "dst": "p2:paper:2406.18624", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ahmad-aghaebrahimian", "dst": "p2:paper:2406.18624", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nicola-ramagnano", "dst": "p2:paper:2406.18624", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christof-sch-pbach", "dst": "p2:paper:2406.18624", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.06265", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kuan-dai", "dst": "p2:paper:2603.06265", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongxin-zhang", "dst": "p2:paper:2603.06265", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sheng-zhong", "dst": "p2:paper:2603.06265", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-zhou", "dst": "p2:paper:2603.06265", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.05633", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tamara-r-lenhard", "dst": "p2:paper:2411.05633", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andreas-weinmann", "dst": "p2:paper:2411.05633", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kai-franke", "dst": "p2:paper:2411.05633", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tobias-koch", "dst": "p2:paper:2411.05633", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.16099", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:gabriele-magrini", "dst": "p2:paper:2409.16099", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:federico-becattini", "dst": "p2:paper:2409.16099", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pietro-pala", "dst": "p2:paper:2409.16099", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alberto-del-bimbo", "dst": "p2:paper:2409.16099", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:antonio-porta", "dst": "p2:paper:2409.16099", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2307.10326", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiangkun-gong", "dst": "p2:paper:2307.10326", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-yan", "dst": "p2:paper:2307.10326", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:deyong-kong", "dst": "p2:paper:2307.10326", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:deren-li", "dst": "p2:paper:2307.10326", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.03331", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:amirreza-rouhi", "dst": "p2:paper:2508.03331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sneh-patel", "dst": "p2:paper:2508.03331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:noah-mccarthy", "dst": "p2:paper:2508.03331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:siddiqa-khan", "dst": "p2:paper:2508.03331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hadi-khorsand", "dst": "p2:paper:2508.03331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaleb-lefkowitz", "dst": "p2:paper:2508.03331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-k-han", "dst": "p2:paper:2508.03331", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2406.11641", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tamara-r-lenhard", "dst": "p2:paper:2406.11641", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andreas-weinmann", "dst": "p2:paper:2406.11641", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stefan-j-ger", "dst": "p2:paper:2406.11641", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tobias-koch", "dst": "p2:paper:2406.11641", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2202.09097", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aryan-sharma", "dst": "p2:paper:2202.09097", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nitik-jain", "dst": "p2:paper:2202.09097", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mangal-kothari", "dst": "p2:paper:2202.09097", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2111.01888", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:fredrik-svanstr-m", "dst": "p2:paper:2111.01888", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fernando-alonso-fernandez", "dst": "p2:paper:2111.01888", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cristofer-englund", "dst": "p2:paper:2111.01888", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.19119", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:palatip-jopanya", "dst": "p2:paper:2509.19119", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:diana-p-m-osorio", "dst": "p2:paper:2509.19119", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.07115", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hanqing-guo", "dst": "p2:paper:2503.07115", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiuxiu-lin", "dst": "p2:paper:2503.07115", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shiyu-zhao", "dst": "p2:paper:2503.07115", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.06998", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zinat-behdad", "dst": "p2:paper:2512.06998", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ozan-alp-topal", "dst": "p2:paper:2512.06998", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cicek-cavdar", "dst": "p2:paper:2512.06998", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.04477", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ali-mohamoud", "dst": "p2:paper:2405.04477", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:johan-van-de-pol", "dst": "p2:paper:2405.04477", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanno-hildmann", "dst": "p2:paper:2405.04477", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rob-van-heijster", "dst": "p2:paper:2405.04477", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:beatrice-masini", "dst": "p2:paper:2405.04477", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:martijn-van-den-heuvel", "dst": "p2:paper:2405.04477", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:amber-van-keeken", "dst": "p2:paper:2405.04477", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1808.00259", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:adrian-carrio", "dst": "p2:paper:1808.00259", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sai-vemprala", "dst": "p2:paper:1808.00259", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andres-ripoll", "dst": "p2:paper:1808.00259", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:srikanth-saripalli", "dst": "p2:paper:1808.00259", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pascual-campoy", "dst": "p2:paper:1808.00259", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.17831", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuan-fang", "dst": "p2:paper:2508.17831", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fangzhan-shi", "dst": "p2:paper:2508.17831", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xijia-wei", "dst": "p2:paper:2508.17831", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qingchao-chen", "dst": "p2:paper:2508.17831", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kevin-chetty", "dst": "p2:paper:2508.17831", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:simon-julier", "dst": "p2:paper:2508.17831", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.08319", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dapinder-kaur", "dst": "p2:paper:2601.08319", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:neeraj-battish", "dst": "p2:paper:2601.08319", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arnav-bhavsar", "dst": "p2:paper:2601.08319", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shashi-poddar", "dst": "p2:paper:2601.08319", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.04564", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:gabriele-magrini", "dst": "p2:paper:2508.04564", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lorenzo-berlincioni", "dst": "p2:paper:2508.04564", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luca-cultrera", "dst": "p2:paper:2508.04564", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:federico-becattini", "dst": "p2:paper:2508.04564", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pietro-pala", "dst": "p2:paper:2508.04564", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2308.09899", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:junyang-zhang", "dst": "p2:paper:2308.09899", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.25942", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:knut-peterson", "dst": "p2:paper:2605.25942", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zaid-mayers", "dst": "p2:paper:2605.25942", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:azmain-yousuf", "dst": "p2:paper:2605.25942", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:priontu-chowdhury", "dst": "p2:paper:2605.25942", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:asher-zaczepinski", "dst": "p2:paper:2605.25942", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:solmaz-arezoomandan", "dst": "p2:paper:2605.25942", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:reihaneh-maarefdoust", "dst": "p2:paper:2605.25942", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-han", "dst": "p2:paper:2605.25942", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1805.05138", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:henrik-ryd-n", "dst": "p2:paper:1805.05138", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sakib-bin-redhwan", "dst": "p2:paper:1805.05138", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xingqin-lin", "dst": "p2:paper:1805.05138", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.00830", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ogulcan-eryuksel", "dst": "p2:paper:2407.00830", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kamil-anil-ozfuttu", "dst": "p2:paper:2407.00830", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fatih-cagatay-akyon", "dst": "p2:paper:2407.00830", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kadir-sahin", "dst": "p2:paper:2407.00830", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:efe-buyukborekci", "dst": "p2:paper:2407.00830", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:devrim-cavusoglu", "dst": "p2:paper:2407.00830", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sinan-altinuc", "dst": "p2:paper:2407.00830", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2210.08423", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tushar-sangam", "dst": "p2:paper:2210.08423", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ishan-rajendrakumar-dave", "dst": "p2:paper:2210.08423", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:waqas-sultani", "dst": "p2:paper:2210.08423", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mubarak-shah", "dst": "p2:paper:2210.08423", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.05292", "dst": "p2:axis:defense", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:purbaditya-bhattacharya", "dst": "p2:paper:2502.05292", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:patrick-nowak", "dst": "p2:paper:2502.05292", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2311.03742", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xinhao-xiang", "dst": "p2:paper:2311.03742", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:simon-dr-ger", "dst": "p2:paper:2311.03742", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiawei-zhang", "dst": "p2:paper:2311.03742", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2203.11496", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xuyang-bai", "dst": "p2:paper:2203.11496", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zeyu-hu", "dst": "p2:paper:2203.11496", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinge-zhu", "dst": "p2:paper:2203.11496", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qingqiu-huang", "dst": "p2:paper:2203.11496", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yilun-chen", "dst": "p2:paper:2203.11496", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hongbo-fu", "dst": "p2:paper:2203.11496", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chiew-lan-tai", "dst": "p2:paper:2203.11496", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.07084", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yiran-qin", "dst": "p2:paper:2309.07084", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chaoqun-wang", "dst": "p2:paper:2309.07084", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zijian-kang", "dst": "p2:paper:2309.07084", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ningning-ma", "dst": "p2:paper:2309.07084", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhen-li", "dst": "p2:paper:2309.07084", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruimao-zhang", "dst": "p2:paper:2309.07084", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.11804", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zixuan-yin", "dst": "p2:paper:2309.11804", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:han-sun", "dst": "p2:paper:2309.11804", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ningzhong-liu", "dst": "p2:paper:2309.11804", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huiyu-zhou", "dst": "p2:paper:2309.11804", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaquan-shen", "dst": "p2:paper:2309.11804", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2312.01468", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:bo-yang", "dst": "p2:paper:2312.01468", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoyu-ji", "dst": "p2:paper:2312.01468", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zizhi-jin", "dst": "p2:paper:2312.01468", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yushi-cheng", "dst": "p2:paper:2312.01468", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenyuan-xu", "dst": "p2:paper:2312.01468", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.02738", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yihao-huang", "dst": "p2:paper:2402.02738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaiyuan-yu", "dst": "p2:paper:2402.02738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qing-guo", "dst": "p2:paper:2402.02738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:felix-juefei-xu", "dst": "p2:paper:2402.02738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaojun-jia", "dst": "p2:paper:2402.02738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianlin-li", "dst": "p2:paper:2402.02738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:geguang-pu", "dst": "p2:paper:2402.02738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-liu", "dst": "p2:paper:2402.02738", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.03884", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:saket-s-chaturvedi", "dst": "p2:paper:2405.03884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lan-zhang", "dst": "p2:paper:2405.03884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenbin-zhang", "dst": "p2:paper:2405.03884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pan-he", "dst": "p2:paper:2405.03884", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoyong-yuan", "dst": "p2:paper:2405.03884", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.08374", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhongyu-xia", "dst": "p2:paper:2509.08374", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hansong-yang", "dst": "p2:paper:2509.08374", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongtao-wang", "dst": "p2:paper:2509.08374", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2011.00652", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:guojun-wang", "dst": "p2:paper:2011.00652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bin-tian", "dst": "p2:paper:2011.00652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yachen-zhang", "dst": "p2:paper:2011.00652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:long-chen", "dst": "p2:paper:2011.00652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dongpu-cao", "dst": "p2:paper:2011.00652", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jian-wu", "dst": "p2:paper:2011.00652", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2303.11040", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yinpeng-dong", "dst": "p2:paper:2303.11040", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:caixin-kang", "dst": "p2:paper:2303.11040", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinlai-zhang", "dst": "p2:paper:2303.11040", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zijian-zhu", "dst": "p2:paper:2303.11040", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yikai-wang", "dst": "p2:paper:2303.11040", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiao-yang", "dst": "p2:paper:2303.11040", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hang-su", "dst": "p2:paper:2303.11040", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xingxing-wei", "dst": "p2:paper:2303.11040", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2401.02702", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ziying-song", "dst": "p2:paper:2401.02702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guoxin-zhang", "dst": "p2:paper:2401.02702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-xie", "dst": "p2:paper:2401.02702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lin-liu", "dst": "p2:paper:2401.02702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:caiyan-jia", "dst": "p2:paper:2401.02702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaoqing-xu", "dst": "p2:paper:2401.02702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhepeng-wang", "dst": "p2:paper:2401.02702", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2311.07152", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:junjie-huang", "dst": "p2:paper:2311.07152", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yun-ye", "dst": "p2:paper:2311.07152", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhujin-liang", "dst": "p2:paper:2311.07152", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-shan", "dst": "p2:paper:2311.07152", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dalong-du", "dst": "p2:paper:2311.07152", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.07284", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hongcheng-zhang", "dst": "p2:paper:2403.07284", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liu-liang", "dst": "p2:paper:2403.07284", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pengxin-zeng", "dst": "p2:paper:2403.07284", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiao-song", "dst": "p2:paper:2403.07284", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhe-wang", "dst": "p2:paper:2403.07284", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2303.03595", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xin-li", "dst": "p2:paper:2303.03595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tao-ma", "dst": "p2:paper:2303.03595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuenan-hou", "dst": "p2:paper:2303.03595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:botian-shi", "dst": "p2:paper:2303.03595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuchen-yang", "dst": "p2:paper:2303.03595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:youquan-liu", "dst": "p2:paper:2303.03595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xingjiao-wu", "dst": "p2:paper:2303.03595", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qin-chen", "dst": "p2:paper:2303.03595", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.01562", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sara-shoouri", "dst": "p2:paper:2508.01562", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:morteza-tavakoli-taba", "dst": "p2:paper:2508.01562", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hun-seok-kim", "dst": "p2:paper:2508.01562", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2209.10733", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xinli-xu", "dst": "p2:paper:2209.10733", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaocong-dong", "dst": "p2:paper:2209.10733", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lihe-ding", "dst": "p2:paper:2209.10733", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jie-wang", "dst": "p2:paper:2209.10733", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tingfa-xu", "dst": "p2:paper:2209.10733", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianan-li", "dst": "p2:paper:2209.10733", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.13647", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yushen-he", "dst": "p2:paper:2504.13647", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-zhao", "dst": "p2:paper:2504.13647", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianchen-deng", "dst": "p2:paper:2504.13647", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zipeng-fang", "dst": "p2:paper:2504.13647", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weidong-chen", "dst": "p2:paper:2504.13647", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2303.16818", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haimei-zhao", "dst": "p2:paper:2303.16818", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qiming-zhang", "dst": "p2:paper:2303.16818", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shanshan-zhao", "dst": "p2:paper:2303.16818", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhe-chen", "dst": "p2:paper:2303.16818", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jing-zhang", "dst": "p2:paper:2303.16818", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dacheng-tao", "dst": "p2:paper:2303.16818", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.16224", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jijun-wang", "dst": "p2:paper:2507.16224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yan-wu", "dst": "p2:paper:2507.16224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yujian-mo", "dst": "p2:paper:2507.16224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junqiao-zhao", "dst": "p2:paper:2507.16224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-yan", "dst": "p2:paper:2507.16224", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yinghao-hu", "dst": "p2:paper:2507.16224", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2212.07560", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yiming-hou", "dst": "p2:paper:2212.07560", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mahdi-rezaei", "dst": "p2:paper:2212.07560", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:richard-romano", "dst": "p2:paper:2212.07560", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.11677", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:till-beemelmanns", "dst": "p2:paper:2402.11677", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:quan-zhang", "dst": "p2:paper:2402.11677", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christian-geller", "dst": "p2:paper:2402.11677", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lutz-eckstein", "dst": "p2:paper:2402.11677", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.20530", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mingqian-ji", "dst": "p2:paper:2508.20530", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jian-yang", "dst": "p2:paper:2508.20530", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shanshan-zhang", "dst": "p2:paper:2508.20530", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.18613", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuzhi-wu", "dst": "p2:paper:2509.18613", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:li-xiao", "dst": "p2:paper:2509.18613", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-liu", "dst": "p2:paper:2509.18613", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guangfeng-jiang", "dst": "p2:paper:2509.18613", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xianggen-xia", "dst": "p2:paper:2509.18613", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2302.14522", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:benjamin-sick", "dst": "p2:paper:2302.14522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-walter", "dst": "p2:paper:2302.14522", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jochen-abhau", "dst": "p2:paper:2302.14522", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1806.06261", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hiliwi-leake-kidane", "dst": "p2:paper:1806.06261", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2210.15316", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:gopi-krishna-erabati", "dst": "p2:paper:2210.15316", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:helder-araujo", "dst": "p2:paper:2210.15316", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.19972", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhen-yang", "dst": "p2:paper:2409.19972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanpeng-dong", "dst": "p2:paper:2409.19972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiayu-wang", "dst": "p2:paper:2409.19972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:heng-wang", "dst": "p2:paper:2409.19972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lichao-ma", "dst": "p2:paper:2409.19972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zijian-cui", "dst": "p2:paper:2409.19972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qi-liu", "dst": "p2:paper:2409.19972", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoran-pei", "dst": "p2:paper:2409.19972", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.12426", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wei-liu", "dst": "p2:paper:2409.12426", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaqi-zhu", "dst": "p2:paper:2409.12426", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guirong-zhuo", "dst": "p2:paper:2409.12426", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wufei-fu", "dst": "p2:paper:2409.12426", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zonglin-meng", "dst": "p2:paper:2409.12426", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yishi-lu", "dst": "p2:paper:2409.12426", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:min-hua", "dst": "p2:paper:2409.12426", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:feng-qiao", "dst": "p2:paper:2409.12426", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.18025", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aditri-paul", "dst": "p2:paper:2508.18025", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:archan-paul", "dst": "p2:paper:2508.18025", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2202.09124", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:masahiro-yasuda", "dst": "p2:paper:2202.09124", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yasunori-ohishi", "dst": "p2:paper:2202.09124", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shoichiro-saito", "dst": "p2:paper:2202.09124", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:noboru-harada", "dst": "p2:paper:2202.09124", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.04629", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:duy-tho-le", "dst": "p2:paper:2404.04629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hengcan-shi", "dst": "p2:paper:2404.04629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianfei-cai", "dst": "p2:paper:2404.04629", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hamid-rezatofighi", "dst": "p2:paper:2404.04629", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2109.06404", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ziyuan-zhong", "dst": "p2:paper:2109.06404", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhisheng-hu", "dst": "p2:paper:2109.06404", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shengjian-guo", "dst": "p2:paper:2109.06404", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xinyang-zhang", "dst": "p2:paper:2109.06404", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenyu-zhong", "dst": "p2:paper:2109.06404", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:baishakhi-ray", "dst": "p2:paper:2109.06404", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.14780", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shounak-sural", "dst": "p2:paper:2404.14780", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nishad-sahu", "dst": "p2:paper:2404.14780", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ragunathan-rajkumar", "dst": "p2:paper:2404.14780", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2501.05997", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sanjay-kumar", "dst": "p2:paper:2501.05997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hiep-truong", "dst": "p2:paper:2501.05997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sushil-sharma", "dst": "p2:paper:2501.05997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ganesh-sistu", "dst": "p2:paper:2501.05997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tony-scanlan", "dst": "p2:paper:2501.05997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eoin-grua", "dst": "p2:paper:2501.05997", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ciar-n-eising", "dst": "p2:paper:2501.05997", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.02329", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zijian-huang", "dst": "p2:paper:2403.02329", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenda-chu", "dst": "p2:paper:2403.02329", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:linyi-li", "dst": "p2:paper:2403.02329", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chejian-xu", "dst": "p2:paper:2403.02329", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bo-li", "dst": "p2:paper:2403.02329", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2607.03915", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ryan-wen-liua", "dst": "p2:paper:2607.03915", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junxiong-lianga", "dst": "p2:paper:2607.03915", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoyu-wanga", "dst": "p2:paper:2607.03915", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mengwei-baoa", "dst": "p2:paper:2607.03915", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.29126", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuwen-zhu", "dst": "p2:paper:2603.29126", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:feiyang-qi", "dst": "p2:paper:2603.29126", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhengzhe-xiang", "dst": "p2:paper:2603.29126", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2401.14314", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xinyu-gao", "dst": "p2:paper:2401.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhijie-wang", "dst": "p2:paper:2401.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-feng", "dst": "p2:paper:2401.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-ma", "dst": "p2:paper:2401.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenyu-chen", "dst": "p2:paper:2401.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:baowen-xu", "dst": "p2:paper:2401.14314", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.23003", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhengkai-huang", "dst": "p2:paper:2510.23003", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yikun-wang", "dst": "p2:paper:2510.23003", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chenyu-hui", "dst": "p2:paper:2510.23003", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaocheng", "dst": "p2:paper:2510.23003", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.21841", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shahriar-rahman-khan", "dst": "p2:paper:2604.21841", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:raiful-hasan", "dst": "p2:paper:2604.21841", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2306.03454", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xinyu-gao", "dst": "p2:paper:2306.03454", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhijie-wang", "dst": "p2:paper:2306.03454", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yang-feng", "dst": "p2:paper:2306.03454", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lei-ma", "dst": "p2:paper:2306.03454", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenyu-chen", "dst": "p2:paper:2306.03454", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:baowen-xu", "dst": "p2:paper:2306.03454", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.19769", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shulan-ruan", "dst": "p2:paper:2506.19769", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rongwei-wang", "dst": "p2:paper:2506.19769", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuchen-shen", "dst": "p2:paper:2506.19769", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:huijie-liu", "dst": "p2:paper:2506.19769", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:baihui-xiao", "dst": "p2:paper:2506.19769", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-shi", "dst": "p2:paper:2506.19769", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kun-zhang", "dst": "p2:paper:2506.19769", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenya-huang", "dst": "p2:paper:2506.19769", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.22947", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yi-tao", "dst": "p2:paper:2510.22947", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhen-gao", "dst": "p2:paper:2510.22947", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fangquan-ye", "dst": "p2:paper:2510.22947", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jingbo-xu", "dst": "p2:paper:2510.22947", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tao-song", "dst": "p2:paper:2510.22947", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weidong-li", "dst": "p2:paper:2510.22947", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yu-su", "dst": "p2:paper:2510.22947", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lu-peng", "dst": "p2:paper:2510.22947", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.13420", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:haoxiang-tian", "dst": "p2:paper:2504.13420", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenqiang-ding", "dst": "p2:paper:2504.13420", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xingshuo-han", "dst": "p2:paper:2504.13420", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guoquan-wu", "dst": "p2:paper:2504.13420", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:an-guo", "dst": "p2:paper:2504.13420", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junqi-zhang-wei-chen", "dst": "p2:paper:2504.13420", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-wei", "dst": "p2:paper:2504.13420", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tianwei-zhang", "dst": "p2:paper:2504.13420", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2106.09249", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yulong-cao", "dst": "p2:paper:2106.09249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ningfei-wang", "dst": "p2:paper:2106.09249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chaowei-xiao", "dst": "p2:paper:2106.09249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dawei-yang", "dst": "p2:paper:2106.09249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jin-fang", "dst": "p2:paper:2106.09249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ruigang-yang", "dst": "p2:paper:2106.09249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qi-alfred-chen", "dst": "p2:paper:2106.09249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mingyan-liu", "dst": "p2:paper:2106.09249", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2012.12397", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ming-liang", "dst": "p2:paper:2012.12397", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bin-yang", "dst": "p2:paper:2012.12397", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yun-chen", "dst": "p2:paper:2012.12397", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rui-hu", "dst": "p2:paper:2012.12397", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:raquel-urtasun", "dst": "p2:paper:2012.12397", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2010.04837", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:iljoo-baek", "dst": "p2:paper:2010.04837", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tzu-chieh-tai", "dst": "p2:paper:2010.04837", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:manoj-bhat", "dst": "p2:paper:2010.04837", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:karun-ellango", "dst": "p2:paper:2010.04837", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tarang-shah", "dst": "p2:paper:2010.04837", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kamal-fuseini", "dst": "p2:paper:2010.04837", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ragunathan", "dst": "p2:paper:2010.04837", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rajkumar", "dst": "p2:paper:2010.04837", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2204.01146", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tianchen-ji", "dst": "p2:paper:2204.01146", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arun-narenthiran-sivakumar", "dst": "p2:paper:2204.01146", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:girish-chowdhary", "dst": "p2:paper:2204.01146", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:katherine-driggs-campbell", "dst": "p2:paper:2204.01146", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.03171", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zeyang-zheng", "dst": "p2:paper:2504.03171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arman-hosseini", "dst": "p2:paper:2504.03171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dong-chen", "dst": "p2:paper:2504.03171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:omid-shoghli", "dst": "p2:paper:2504.03171", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arsalan-heydarian", "dst": "p2:paper:2504.03171", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.14592", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:wenqiao-li", "dst": "p2:paper:2412.14592", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bozhong-zheng", "dst": "p2:paper:2412.14592", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaohao-xu", "dst": "p2:paper:2412.14592", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinye-gan", "dst": "p2:paper:2412.14592", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fading-lu", "dst": "p2:paper:2412.14592", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiang-li", "dst": "p2:paper:2412.14592", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:na-ni", "dst": "p2:paper:2412.14592", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zheng-tian", "dst": "p2:paper:2412.14592", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.01974", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chenyang-yan", "dst": "p2:paper:2602.01974", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mats-bengtsson", "dst": "p2:paper:2602.01974", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2304.13390", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hongwei-liu", "dst": "p2:paper:2304.13390", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jian-yang", "dst": "p2:paper:2304.13390", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianfeng-zhang", "dst": "p2:paper:2304.13390", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dongheng-shao", "dst": "p2:paper:2304.13390", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jielong-guo", "dst": "p2:paper:2304.13390", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaobo-li", "dst": "p2:paper:2304.13390", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuan-tang", "dst": "p2:paper:2304.13390", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xian-wei", "dst": "p2:paper:2304.13390", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2409.04979", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zhiwei-lin", "dst": "p2:paper:2409.04979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhe-liu", "dst": "p2:paper:2409.04979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongtao-wang", "dst": "p2:paper:2409.04979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:le-zhang", "dst": "p2:paper:2409.04979", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ce-zhu", "dst": "p2:paper:2409.04979", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2103.07825", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xu-dong", "dst": "p2:paper:2103.07825", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:binnan-zhuang", "dst": "p2:paper:2103.07825", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yunxiang-mao", "dst": "p2:paper:2103.07825", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:langechuan-liu", "dst": "p2:paper:2103.07825", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.06165", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:huawei-sun", "dst": "p2:paper:2404.06165", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-feng", "dst": "p2:paper:2404.06165", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gianfranco-mauro", "dst": "p2:paper:2404.06165", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:julius-ott", "dst": "p2:paper:2404.06165", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:georg-stettinger", "dst": "p2:paper:2404.06165", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lorenzo-servadei", "dst": "p2:paper:2404.06165", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:robert-wille", "dst": "p2:paper:2404.06165", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2304.10410", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shanliang-yao", "dst": "p2:paper:2304.10410", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:runwei-guan", "dst": "p2:paper:2304.10410", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoyu-huang", "dst": "p2:paper:2304.10410", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhuoxiao-li", "dst": "p2:paper:2304.10410", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiangyu-sha", "dst": "p2:paper:2304.10410", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-yue", "dst": "p2:paper:2304.10410", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eng-gee-lim", "dst": "p2:paper:2304.10410", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hyungjoon-seo", "dst": "p2:paper:2304.10410", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.06670", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuting-wan", "dst": "p2:paper:2603.06670", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liguo-sun", "dst": "p2:paper:2603.06670", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiuwu-hao", "dst": "p2:paper:2603.06670", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pin-lv", "dst": "p2:paper:2603.06670", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.31096", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:geonho-bang", "dst": "p2:paper:2606.31096", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:geunju-baek", "dst": "p2:paper:2606.31096", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dongyoung-lee", "dst": "p2:paper:2606.31096", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wonjun-jeong", "dst": "p2:paper:2606.31096", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-won-choi", "dst": "p2:paper:2606.31096", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2307.06505", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shanliang-yao", "dst": "p2:paper:2307.06505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:runwei-guan", "dst": "p2:paper:2307.06505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhaodong-wu", "dst": "p2:paper:2307.06505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yi-ni", "dst": "p2:paper:2307.06505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zile-huang", "dst": "p2:paper:2307.06505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ryan-wen-liu", "dst": "p2:paper:2307.06505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-yue", "dst": "p2:paper:2307.06505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weiping-ding", "dst": "p2:paper:2307.06505", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2107.05150", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ramin-nabati", "dst": "p2:paper:2107.05150", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:landon-harris", "dst": "p2:paper:2107.05150", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hairong-qi", "dst": "p2:paper:2107.05150", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.12725", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiaomeng-chu", "dst": "p2:paper:2412.12725", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiajun-deng", "dst": "p2:paper:2412.12725", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guoliang-you", "dst": "p2:paper:2412.12725", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yifan-duan", "dst": "p2:paper:2412.12725", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:houqiang-li", "dst": "p2:paper:2412.12725", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yanyong-zhang", "dst": "p2:paper:2412.12725", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.11489", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zijian-gu", "dst": "p2:paper:2412.11489", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianwei-ma", "dst": "p2:paper:2412.11489", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yan-huang", "dst": "p2:paper:2412.11489", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:honghao-wei", "dst": "p2:paper:2412.11489", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhanye-chen", "dst": "p2:paper:2412.11489", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hui-zhang", "dst": "p2:paper:2412.11489", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-hong", "dst": "p2:paper:2412.11489", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2607.04098", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:fuyuan-ai", "dst": "p2:paper:2607.04098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuchen-tan", "dst": "p2:paper:2607.04098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiehui-chen", "dst": "p2:paper:2607.04098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiwei-xu", "dst": "p2:paper:2607.04098", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chunyi-song", "dst": "p2:paper:2607.04098", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.15016", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hongsi-liu", "dst": "p2:paper:2411.15016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-liu", "dst": "p2:paper:2411.15016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guangfeng-jiang", "dst": "p2:paper:2411.15016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xin-jin", "dst": "p2:paper:2411.15016", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2303.04302", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:felipe-manfio-barbosa", "dst": "p2:paper:2303.04302", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fernando-santos-os-rio", "dst": "p2:paper:2303.04302", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.12918", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ahmet-i-nan", "dst": "p2:paper:2604.12918", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zg-r-erkent", "dst": "p2:paper:2604.12918", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.16368", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:linhua-kong", "dst": "p2:paper:2504.16368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dongxia-chang", "dst": "p2:paper:2504.16368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lian-liu", "dst": "p2:paper:2504.16368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zisen-kong", "dst": "p2:paper:2504.16368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pengyuan-li", "dst": "p2:paper:2504.16368", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yao-zhao", "dst": "p2:paper:2504.16368", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2208.03849", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kshitiz-bansal", "dst": "p2:paper:2208.03849", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:keshav-rungta", "dst": "p2:paper:2208.03849", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dinesh-bharadia", "dst": "p2:paper:2208.03849", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2009.08428", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ramin-nabati", "dst": "p2:paper:2009.08428", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hairong-qi", "dst": "p2:paper:2009.08428", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.19860", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:philipp-wolters", "dst": "p2:paper:2411.19860", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:johannes-gilg", "dst": "p2:paper:2411.19860", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:torben-teepe", "dst": "p2:paper:2411.19860", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fabian-herzog", "dst": "p2:paper:2411.19860", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:felix-fent", "dst": "p2:paper:2411.19860", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gerhard-rigoll", "dst": "p2:paper:2411.19860", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.19314", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:chen-chou-lo", "dst": "p2:paper:2601.19314", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:patrick-vandewalle", "dst": "p2:paper:2601.19314", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2603.21987", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nour-alhuda-albashir", "dst": "p2:paper:2603.21987", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lars-pernickel", "dst": "p2:paper:2603.21987", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:danial-hamoud", "dst": "p2:paper:2603.21987", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:idriss-gouigah", "dst": "p2:paper:2603.21987", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eren-erdal-aksoy", "dst": "p2:paper:2603.21987", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2602.20632", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiaokai-bai", "dst": "p2:paper:2602.20632", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lianqing-zheng", "dst": "p2:paper:2602.20632", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:si-yuan-cao", "dst": "p2:paper:2602.20632", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaohan-zhang", "dst": "p2:paper:2602.20632", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhe-wu", "dst": "p2:paper:2602.20632", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:beinan-yu", "dst": "p2:paper:2602.20632", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fang-wang", "dst": "p2:paper:2602.20632", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jie-bai", "dst": "p2:paper:2602.20632", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.08074", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:christof-leitgeb", "dst": "p2:paper:2604.08074", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thomas-puchleitner", "dst": "p2:paper:2604.08074", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:max-peter-ronecker", "dst": "p2:paper:2604.08074", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-watzenig", "dst": "p2:paper:2604.08074", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.13937", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sheng-yao-kuan", "dst": "p2:paper:2407.13937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jen-hao-cheng", "dst": "p2:paper:2407.13937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hsiang-wei-huang", "dst": "p2:paper:2407.13937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenhao-chai", "dst": "p2:paper:2407.13937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cheng-yen-yang", "dst": "p2:paper:2407.13937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hugo-latapie", "dst": "p2:paper:2407.13937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gaowen-liu", "dst": "p2:paper:2407.13937", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bing-fei-wu", "dst": "p2:paper:2407.13937", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.10567", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:philipp-wolters", "dst": "p2:paper:2508.10567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:johannes-gilg", "dst": "p2:paper:2508.10567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:torben-teepe", "dst": "p2:paper:2508.10567", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gerhard-rigoll", "dst": "p2:paper:2508.10567", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.22054", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:baorui-ma", "dst": "p2:paper:2601.22054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiahui-yang", "dst": "p2:paper:2601.22054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:donglin-di", "dst": "p2:paper:2601.22054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuancheng-zhang", "dst": "p2:paper:2601.22054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianxun-cui", "dst": "p2:paper:2601.22054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-li", "dst": "p2:paper:2601.22054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yan-xie", "dst": "p2:paper:2601.22054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wei-chen", "dst": "p2:paper:2601.22054", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.13571", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:bingxue-xu", "dst": "p2:paper:2604.13571", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:emil-hedemalm", "dst": "p2:paper:2604.13571", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ajinkya-khoche", "dst": "p2:paper:2604.13571", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:patric-jensfelt", "dst": "p2:paper:2604.13571", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2104.14682", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aleksandr-kim", "dst": "p2:paper:2104.14682", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aljo-a-o-ep", "dst": "p2:paper:2104.14682", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:laura-leal-taix", "dst": "p2:paper:2104.14682", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.13689", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:qing-li", "dst": "p2:paper:2408.13689", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:runze-gan", "dst": "p2:paper:2408.13689", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:simon-godsill", "dst": "p2:paper:2408.13689", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.02532", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tara-sadjadpour", "dst": "p2:paper:2310.02532", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rares-ambrus", "dst": "p2:paper:2310.02532", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jeannette-bohg", "dst": "p2:paper:2310.02532", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2302.14807", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mohamed-nagy", "dst": "p2:paper:2302.14807", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:majid-khonji", "dst": "p2:paper:2302.14807", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jorge-dias", "dst": "p2:paper:2302.14807", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sajid-javed", "dst": "p2:paper:2302.14807", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.03702", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:depanshu-sani", "dst": "p2:paper:2411.03702", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:saket-anand", "dst": "p2:paper:2411.03702", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.14013", "dst": "p2:axis:fusion", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:tim-hansen", "dst": "p2:paper:2604.14013", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arturo-gomez-chavez", "dst": "p2:paper:2604.14013", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ilya-shimchik", "dst": "p2:paper:2604.14013", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andreas-birk", "dst": "p2:paper:2604.14013", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2103.08049", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nicolas-delfosse", "dst": "p2:paper:2103.08049", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vivien-londe", "dst": "p2:paper:2103.08049", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-beverland", "dst": "p2:paper:2103.08049", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.07057", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:min-ye", "dst": "p2:paper:2512.07057", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dave-wecker", "dst": "p2:paper:2512.07057", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nicolas-delfosse", "dst": "p2:paper:2512.07057", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.08817", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hanwen-yao", "dst": "p2:paper:2412.08817", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mert-g-kduman", "dst": "p2:paper:2412.08817", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:henry-d-pfister", "dst": "p2:paper:2412.08817", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.05080", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sam-j-griffiths", "dst": "p2:paper:2504.05080", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:asmae-benhemou", "dst": "p2:paper:2504.05080", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dan-e-browne", "dst": "p2:paper:2504.05080", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1204.4223", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yixuan-xie", "dst": "p2:paper:1204.4223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-li", "dst": "p2:paper:1204.4223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:robert-malaney", "dst": "p2:paper:1204.4223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinhong-yuan", "dst": "p2:paper:1204.4223", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2205.06125", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:julien-du-crest", "dst": "p2:paper:2205.06125", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mehdi-mhalla", "dst": "p2:paper:2205.06125", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:valentin-savin", "dst": "p2:paper:2205.06125", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.08177", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mert-g-kduman", "dst": "p2:paper:2411.08177", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hanwen-yao", "dst": "p2:paper:2411.08177", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:henry-d-pfister", "dst": "p2:paper:2411.08177", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.01035", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:daniel-b-scones", "dst": "p2:paper:2605.01035", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:arshpreet-singh-maan", "dst": "p2:paper:2605.01035", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:valentin-savin", "dst": "p2:paper:2605.01035", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francisco-garcia-herrero", "dst": "p2:paper:2605.01035", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2308.13377", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:julien-du-crest", "dst": "p2:paper:2308.13377", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francisco-garcia-herrero", "dst": "p2:paper:2308.13377", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mehdi-mhalla", "dst": "p2:paper:2308.13377", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:valentin-savin", "dst": "p2:paper:2308.13377", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:javier-valls", "dst": "p2:paper:2308.13377", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.04769", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shouzhen-gu", "dst": "p2:paper:2508.04769", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mehdi-soleimanifar", "dst": "p2:paper:2508.04769", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.17758", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:anqi-gong", "dst": "p2:paper:2310.17758", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sebastian-cammerer", "dst": "p2:paper:2310.17758", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joseph-m-renes", "dst": "p2:paper:2310.17758", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.14060", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:arshpreet-singh-maan", "dst": "p2:paper:2510.14060", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francisco-garcia-herrero", "dst": "p2:paper:2510.14060", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexandru-paler", "dst": "p2:paper:2510.14060", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:valentin-savin", "dst": "p2:paper:2510.14060", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2005.07016", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:joschka-roffe", "dst": "p2:paper:2005.07016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-r-white", "dst": "p2:paper:2005.07016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:simon-burton", "dst": "p2:paper:2005.07016", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:earl-t-campbell", "dst": "p2:paper:2005.07016", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2004.07935", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shai-evra", "dst": "p2:paper:2004.07935", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tali-kaufman", "dst": "p2:paper:2004.07935", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gilles-z-mor", "dst": "p2:paper:2004.07935", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.00254", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ming-wang", "dst": "p2:paper:2507.00254", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ang-li", "dst": "p2:paper:2507.00254", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:frank-mueller", "dst": "p2:paper:2507.00254", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.07868", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:anirudh-krishna", "dst": "p2:paper:2310.07868", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:inbal-livni-navon", "dst": "p2:paper:2310.07868", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mary-wootters", "dst": "p2:paper:2310.07868", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1202.0357", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yixuan-xie", "dst": "p2:paper:1202.0357", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-li", "dst": "p2:paper:1202.0357", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:robert-malaney", "dst": "p2:paper:1202.0357", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jinhong-yuan", "dst": "p2:paper:1202.0357", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1207.0732", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jacob-farinholt", "dst": "p2:paper:1207.0732", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.08824", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kenta-kasai", "dst": "p2:paper:2601.08824", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2308.08208", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sisi-miao", "dst": "p2:paper:2308.08208", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexander-schnerring", "dst": "p2:paper:2308.08208", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haizheng-li", "dst": "p2:paper:2308.08208", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:laurent-schmalen", "dst": "p2:paper:2308.08208", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.17268", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:arda-aydin", "dst": "p2:paper:2606.17268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:itzhak-tamo", "dst": "p2:paper:2606.17268", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexander-barg", "dst": "p2:paper:2606.17268", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.04634", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:koki-okada", "dst": "p2:paper:2511.04634", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kenta-kasai", "dst": "p2:paper:2511.04634", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1904.02703", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:pavel-panteleev", "dst": "p2:paper:1904.02703", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gleb-kalachev", "dst": "p2:paper:1904.02703", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1712.08578", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:vivien-londe", "dst": "p2:paper:1712.08578", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anthony-leverrier", "dst": "p2:paper:1712.08578", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:0712.4115", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:salah-a-aly", "dst": "p2:paper:0712.4115", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2208.01002", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nicholas-connolly", "dst": "p2:paper:2208.01002", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vivien-londe", "dst": "p2:paper:2208.01002", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anthony-leverrier", "dst": "p2:paper:2208.01002", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nicolas-delfosse", "dst": "p2:paper:2208.01002", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.13281", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lorenzo-valentini", "dst": "p2:paper:2511.13281", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:diego-forlivesi", "dst": "p2:paper:2511.13281", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrea-talarico", "dst": "p2:paper:2511.13281", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marco-chiani", "dst": "p2:paper:2511.13281", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.01532", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:antonio-demarti-iolius", "dst": "p2:paper:2402.01532", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:josu-etxezarreta-martinez", "dst": "p2:paper:2402.01532", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2206.06557", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shouzhen-gu", "dst": "p2:paper:2206.06557", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-a-pattison", "dst": "p2:paper:2206.06557", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eugene-tang", "dst": "p2:paper:2206.06557", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.01738", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:stergios-koutsioumpas", "dst": "p2:paper:2503.01738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hasan-sayginel", "dst": "p2:paper:2503.01738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mark-webster", "dst": "p2:paper:2503.01738", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dan-e-browne", "dst": "p2:paper:2503.01738", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2311.11167", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yue-zhao", "dst": "p2:paper:2311.11167", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2110.10378", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ian-convy", "dst": "p2:paper:2110.10378", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haoran-liao", "dst": "p2:paper:2110.10378", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:song-zhang", "dst": "p2:paper:2110.10378", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sahil-patel", "dst": "p2:paper:2110.10378", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:william-p-livingston", "dst": "p2:paper:2110.10378", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ho-nam-nguyen", "dst": "p2:paper:2110.10378", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:irfan-siddiqi", "dst": "p2:paper:2110.10378", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:k-birgitta-whaley", "dst": "p2:paper:2110.10378", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.07223", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:eromanga-adermann", "dst": "p2:paper:2601.07223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:haiyue-kang", "dst": "p2:paper:2601.07223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:martin-sevior", "dst": "p2:paper:2601.07223", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:muhammad-usman", "dst": "p2:paper:2601.07223", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2202.00555", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:david-f-locher", "dst": "p2:paper:2202.00555", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lorenzo-cardarelli", "dst": "p2:paper:2202.00555", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:markus-m-ller", "dst": "p2:paper:2202.00555", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.11552", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nico-meyer", "dst": "p2:paper:2506.11552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-mutschler", "dst": "p2:paper:2506.11552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andreas-maier", "dst": "p2:paper:2506.11552", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-d-scherer", "dst": "p2:paper:2506.11552", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.21707", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:anirudh-lanka", "dst": "p2:paper:2506.21707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shashank-hegde", "dst": "p2:paper:2506.21707", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:todd-a-brun", "dst": "p2:paper:2506.21707", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.08592", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:shun-ryuzaki", "dst": "p2:paper:2606.08592", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hideo-mukai", "dst": "p2:paper:2606.08592", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.19971", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:gengyuan-hu", "dst": "p2:paper:2502.19971", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wanli-ouyang", "dst": "p2:paper:2502.19971", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chao-yang-lu", "dst": "p2:paper:2502.19971", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chen-lin", "dst": "p2:paper:2502.19971", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:han-sen-zhong", "dst": "p2:paper:2502.19971", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1812.08451", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hendrik-poulsen-nautrup", "dst": "p2:paper:1812.08451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nicolas-delfosse", "dst": "p2:paper:1812.08451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:vedran-dunjko", "dst": "p2:paper:1812.08451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hans-j-briegel", "dst": "p2:paper:1812.08451", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nicolai-friis", "dst": "p2:paper:1812.08451", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1912.10063", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hongxiang-chen", "dst": "p2:paper:1912.10063", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-vasmer", "dst": "p2:paper:1912.10063", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nikolas-p-breuckmann", "dst": "p2:paper:1912.10063", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:edward-grant", "dst": "p2:paper:1912.10063", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1711.02249", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:peter-d-johnson", "dst": "p2:paper:1711.02249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jonathan-romero", "dst": "p2:paper:1711.02249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jonathan-olson", "dst": "p2:paper:1711.02249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yudong-cao", "dst": "p2:paper:1711.02249", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:al-n-aspuru-guzik", "dst": "p2:paper:1711.02249", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.19651", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jerome-lenssen", "dst": "p2:paper:2504.19651", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexandru-paler", "dst": "p2:paper:2504.19651", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.12482", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yue-yin", "dst": "p2:paper:2511.12482", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tailong-xiao", "dst": "p2:paper:2511.12482", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoyang-deng", "dst": "p2:paper:2511.12482", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ming-he", "dst": "p2:paper:2511.12482", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianping-fan", "dst": "p2:paper:2511.12482", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guihua-zeng", "dst": "p2:paper:2511.12482", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2507.12253", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:archisman-ghosh", "dst": "p2:paper:2507.12253", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:avimita-chatterjee", "dst": "p2:paper:2507.12253", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:swaroop-ghosh", "dst": "p2:paper:2507.12253", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2503.21374", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hanyan-cao", "dst": "p2:paper:2503.21374", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:feng-pan", "dst": "p2:paper:2503.21374", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dongyang-feng", "dst": "p2:paper:2503.21374", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yijia-wang", "dst": "p2:paper:2503.21374", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pan-zhang", "dst": "p2:paper:2503.21374", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2202.08600", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:josu-etxezarreta-martinez", "dst": "p2:paper:2202.08600", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2311.16082", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hanrui-wang", "dst": "p2:paper:2311.16082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pengyu-liu", "dst": "p2:paper:2311.16082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kevin-shao", "dst": "p2:paper:2311.16082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dantong-li", "dst": "p2:paper:2311.16082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiaqi-gu", "dst": "p2:paper:2311.16082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-z-pan", "dst": "p2:paper:2311.16082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongshan-ding", "dst": "p2:paper:2311.16082", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:song-han", "dst": "p2:paper:2311.16082", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.22724", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:changwon-lee", "dst": "p2:paper:2510.22724", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tak-hur", "dst": "p2:paper:2510.22724", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-k-park", "dst": "p2:paper:2510.22724", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2412.20380", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:zihao-wang", "dst": "p2:paper:2412.20380", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hao-tang", "dst": "p2:paper:2412.20380", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2208.05879", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:liangyu-chen", "dst": "p2:paper:2208.05879", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hang-xi-li", "dst": "p2:paper:2208.05879", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yong-lu", "dst": "p2:paper:2208.05879", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-w-warren", "dst": "p2:paper:2208.05879", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christian-j-kri-an", "dst": "p2:paper:2208.05879", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sandoko-kosen", "dst": "p2:paper:2208.05879", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marcus-rommel", "dst": "p2:paper:2208.05879", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shahnawaz-ahmed", "dst": "p2:paper:2208.05879", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.12046", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ge-yan", "dst": "p2:paper:2605.12046", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shanchuan-li", "dst": "p2:paper:2605.12046", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxuan-du", "dst": "p2:paper:2605.12046", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.17230", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hanyan-cao", "dst": "p2:paper:2605.17230", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ge-yan", "dst": "p2:paper:2605.17230", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxuan-du", "dst": "p2:paper:2605.17230", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:feng-pan", "dst": "p2:paper:2605.17230", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1810.03787", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:iris-cong", "dst": "p2:paper:1810.03787", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:soonwon-choi", "dst": "p2:paper:1810.03787", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mikhail-d-lukin", "dst": "p2:paper:1810.03787", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.16242", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:karan-kendre", "dst": "p2:paper:2509.16242", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.28162", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nico-meyer", "dst": "p2:paper:2605.28162", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-mutschler", "dst": "p2:paper:2605.28162", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dominik-seu", "dst": "p2:paper:2605.28162", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andreas-maier", "dst": "p2:paper:2605.28162", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:daniel-d-scherer", "dst": "p2:paper:2605.28162", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2307.09463", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:victor-yon", "dst": "p2:paper:2307.09463", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fr-d-ric-marcotte", "dst": "p2:paper:2307.09463", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pierre-antoine-mouny", "dst": "p2:paper:2307.09463", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:gebremedhin-a-dagnew", "dst": "p2:paper:2307.09463", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bohdan-kulchytskyy", "dst": "p2:paper:2307.09463", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sophie-rochette", "dst": "p2:paper:2307.09463", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yann-beilliard", "dst": "p2:paper:2307.09463", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dominique-drouin", "dst": "p2:paper:2307.09463", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.18562", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yihua-chengyu", "dst": "p2:paper:2601.18562", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:richard-meister", "dst": "p2:paper:2601.18562", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:conor-carty", "dst": "p2:paper:2601.18562", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sheng-ku-lin", "dst": "p2:paper:2601.18562", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:roberto-bondesan", "dst": "p2:paper:2601.18562", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1908.01092", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sahar-daraeizadeh", "dst": "p2:paper:1908.01092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shavindra-p-premaratne", "dst": "p2:paper:1908.01092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoyu-song", "dst": "p2:paper:1908.01092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marek-perkowski", "dst": "p2:paper:1908.01092", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:anne-y-matsuura", "dst": "p2:paper:1908.01092", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2202.05741", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ramon-overwater", "dst": "p2:paper:2202.05741", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:masoud-babaie", "dst": "p2:paper:2202.05741", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fabio-sebastiano", "dst": "p2:paper:2202.05741", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.08758", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:david-dentelski", "dst": "p2:paper:2606.08758", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.09921", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kai-zhang", "dst": "p2:paper:2601.09921", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhengzhong-yi", "dst": "p2:paper:2601.09921", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaojun-guo", "dst": "p2:paper:2601.09921", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:linghang-kong", "dst": "p2:paper:2601.09921", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:situ-wang", "dst": "p2:paper:2601.09921", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoyu-zhan", "dst": "p2:paper:2601.09921", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tan-he", "dst": "p2:paper:2601.09921", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:weiping-lin", "dst": "p2:paper:2601.09921", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.22741", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:evan-peters", "dst": "p2:paper:2505.22741", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1705.07855", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:p-baireuther", "dst": "p2:paper:1705.07855", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:t-e-o-brien", "dst": "p2:paper:1705.07855", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:b-tarasinski", "dst": "p2:paper:1705.07855", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:c-w-j-beenakker", "dst": "p2:paper:1705.07855", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1705.00857", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:savvas-varsamopoulos", "dst": "p2:paper:1705.00857", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ben-criger", "dst": "p2:paper:1705.00857", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:koen-bertels", "dst": "p2:paper:1705.00857", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.01741", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ameya-s-bhave", "dst": "p2:paper:2511.01741", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:navnil-choudhury", "dst": "p2:paper:2511.01741", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kanad-basu", "dst": "p2:paper:2511.01741", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2502.20269", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:lukas-b-deker", "dst": "p2:paper:2502.20269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luc-j-b-kusters", "dst": "p2:paper:2502.20269", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:markus-m-ller", "dst": "p2:paper:2502.20269", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2606.22194", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:dominik-seip", "dst": "p2:paper:2606.22194", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luis-colmenarez", "dst": "p2:paper:2606.22194", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:markus-schmitt", "dst": "p2:paper:2606.22194", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:markus-m-ller", "dst": "p2:paper:2606.22194", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.03815", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kai-zhang", "dst": "p2:paper:2509.03815", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:situ-wang", "dst": "p2:paper:2509.03815", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:linghang-kong", "dst": "p2:paper:2509.03815", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fang-zhang", "dst": "p2:paper:2509.03815", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhengfeng-ji", "dst": "p2:paper:2509.03815", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianxin-chen", "dst": "p2:paper:2509.03815", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.04892", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xiaohan-yang", "dst": "p2:paper:2605.04892", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuandong-sun", "dst": "p2:paper:2605.04892", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiyi-wu", "dst": "p2:paper:2605.04892", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiawei-zhang", "dst": "p2:paper:2605.04892", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ji-jiang", "dst": "p2:paper:2605.04892", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiayu-linpeng", "dst": "p2:paper:2605.04892", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxuan-zhou", "dst": "p2:paper:2605.04892", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ji-chu", "dst": "p2:paper:2605.04892", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1710.09489", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nikolas-p-breuckmann", "dst": "p2:paper:1710.09489", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaotong-ni", "dst": "p2:paper:1710.09489", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.08358", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:andi-gu", "dst": "p2:paper:2604.08358", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:j-pablo-bonilla-ataides", "dst": "p2:paper:2604.08358", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mikhail-d-lukin", "dst": "p2:paper:2604.08358", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:susanne-f-yelin", "dst": "p2:paper:2604.08358", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.16113", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:spiro-gicev", "dst": "p2:paper:2506.16113", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lloyd-c-l-hollenberg", "dst": "p2:paper:2506.16113", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:muhammad-usman", "dst": "p2:paper:2506.16113", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2511.17460", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yuejie-xin", "dst": "p2:paper:2511.17460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sean-l-m-van-der-meer", "dst": "p2:paper:2511.17460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marc-serra-peralta", "dst": "p2:paper:2511.17460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tim-h-f-vroomans", "dst": "p2:paper:2511.17460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:matvey-finkel", "dst": "p2:paper:2511.17460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hendrik-m-veen", "dst": "p2:paper:2511.17460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mark-w-beekman", "dst": "p2:paper:2511.17460", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:leonardo-dicarlo", "dst": "p2:paper:2511.17460", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.03783", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ryota-ikeda", "dst": "p2:paper:2508.03783", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2607.01473", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:weiping-lin", "dst": "p2:paper:2607.01473", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shaojun-guo", "dst": "p2:paper:2607.01473", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuwei-ma", "dst": "p2:paper:2607.01473", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhengzhong-yi", "dst": "p2:paper:2607.01473", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kai-zhang", "dst": "p2:paper:2607.01473", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jiahao-bei", "dst": "p2:paper:2607.01473", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianbin-cai", "dst": "p2:paper:2607.01473", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sirui-cao", "dst": "p2:paper:2607.01473", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.04526", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:ryota-nakai", "dst": "p2:paper:2510.04526", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hayato-goto", "dst": "p2:paper:2510.04526", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1903.10254", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:joschka-roffe", "dst": "p2:paper:1903.10254", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stefan-zohren", "dst": "p2:paper:1903.10254", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dominic-horsman", "dst": "p2:paper:1903.10254", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nicholas-chancellor", "dst": "p2:paper:1903.10254", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2303.00054", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:francesco-battistel", "dst": "p2:paper:2303.00054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-chamberland", "dst": "p2:paper:2303.00054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kauser-johar", "dst": "p2:paper:2303.00054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ramon-w-j-overwater", "dst": "p2:paper:2303.00054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fabio-sebastiano", "dst": "p2:paper:2303.00054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luka-skoric", "dst": "p2:paper:2303.00054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yosuke-ueno", "dst": "p2:paper:2303.00054", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:muhammad-usman", "dst": "p2:paper:2303.00054", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.30765", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yaojian-chen", "dst": "p2:paper:2605.30765", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chun-yang-luan", "dst": "p2:paper:2605.30765", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:peilin-zheng", "dst": "p2:paper:2605.30765", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xianghong-zeng", "dst": "p2:paper:2605.30765", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jia-yi-hou", "dst": "p2:paper:2605.30765", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhuo-fu", "dst": "p2:paper:2605.30765", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yirong-jin", "dst": "p2:paper:2605.30765", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fei-wang", "dst": "p2:paper:2605.30765", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.05202", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:laura-caune", "dst": "p2:paper:2410.05202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:luka-skoric", "dst": "p2:paper:2410.05202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:nick-s-blunt", "dst": "p2:paper:2410.05202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:archibald-ruban", "dst": "p2:paper:2410.05202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jimmy-mcdaniel", "dst": "p2:paper:2410.05202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joseph-a-valery", "dst": "p2:paper:2410.05202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrew-d-patterson", "dst": "p2:paper:2410.05202", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexander-v-gramolin", "dst": "p2:paper:2410.05202", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2108.06569", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:poulami-das", "dst": "p2:paper:2108.06569", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aditya-locharla", "dst": "p2:paper:2108.06569", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cody-jones", "dst": "p2:paper:2108.06569", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2404.03136", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:narges-alavisamani", "dst": "p2:paper:2404.03136", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:suhas-vittal", "dst": "p2:paper:2404.03136", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ramin-ayanzadeh", "dst": "p2:paper:2404.03136", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:poulami-das", "dst": "p2:paper:2404.03136", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:moinuddin-qureshi", "dst": "p2:paper:2404.03136", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2601.16123", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:samuel-stein", "dst": "p2:paper:2601.16123", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shuwen-kan", "dst": "p2:paper:2601.16123", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:chenxu-liu", "dst": "p2:paper:2601.16123", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:adrian-harkness", "dst": "p2:paper:2601.16123", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sean-garner", "dst": "p2:paper:2601.16123", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zefan-du", "dst": "p2:paper:2601.16123", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yufei-ding", "dst": "p2:paper:2601.16123", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ying-mao", "dst": "p2:paper:2601.16123", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.13687", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:rajeev-acharya", "dst": "p2:paper:2408.13687", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:laleh-aghababaie-beni", "dst": "p2:paper:2408.13687", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:igor-aleiner", "dst": "p2:paper:2408.13687", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:trond-i-andersen", "dst": "p2:paper:2408.13687", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:markus-ansmann", "dst": "p2:paper:2408.13687", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:frank-arute", "dst": "p2:paper:2408.13687", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kunal-arya", "dst": "p2:paper:2408.13687", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:abraham-asfaw", "dst": "p2:paper:2408.13687", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.25222", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:riki-toshio", "dst": "p2:paper:2510.25222", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaito-kishi", "dst": "p2:paper:2510.25222", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jun-fujisaki", "dst": "p2:paper:2510.25222", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hirotaka-oshima", "dst": "p2:paper:2510.25222", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shintaro-sato", "dst": "p2:paper:2510.25222", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:keisuke-fujii", "dst": "p2:paper:2510.25222", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2605.03180", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:alexander-knapen", "dst": "p2:paper:2605.03180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:junyi-luo", "dst": "p2:paper:2605.03180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guanchen-tao", "dst": "p2:paper:2605.03180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yuxuan-wang", "dst": "p2:paper:2605.03180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tomas-bruno", "dst": "p2:paper:2605.03180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qirui-zhang", "dst": "p2:paper:2605.03180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dennis-sylvester", "dst": "p2:paper:2605.03180", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mehdi-saligane", "dst": "p2:paper:2605.03180", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.16228", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:maurice-d-hanisch", "dst": "p2:paper:2411.16228", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:bence-het-nyi", "dst": "p2:paper:2411.16228", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:james-r-wootton", "dst": "p2:paper:2411.16228", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2311.12503", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:arshpreet-singh-maan", "dst": "p2:paper:2311.12503", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexandru-paler", "dst": "p2:paper:2311.12503", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2107.07505", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:c-ryan-anderson", "dst": "p2:paper:2107.07505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:j-g-bohnet", "dst": "p2:paper:2107.07505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:k-lee", "dst": "p2:paper:2107.07505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:d-gresh", "dst": "p2:paper:2107.07505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:a-hankin", "dst": "p2:paper:2107.07505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:j-p-gaebler", "dst": "p2:paper:2107.07505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:d-francois", "dst": "p2:paper:2107.07505", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:a-chernoguzov", "dst": "p2:paper:2107.07505", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2604.21866", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:don-winter", "dst": "p2:paper:2604.21866", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thiago-l-m-guedes", "dst": "p2:paper:2604.21866", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:markus-m-ller", "dst": "p2:paper:2604.21866", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2407.11523", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:jiahan-chen", "dst": "p2:paper:2407.11523", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhengzhong-yi", "dst": "p2:paper:2407.11523", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhipeng-liang", "dst": "p2:paper:2407.11523", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xuan-wang", "dst": "p2:paper:2407.11523", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2506.08331", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:pan-zhang", "dst": "p2:paper:2506.08331", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.11805", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:namitha-liyanage", "dst": "p2:paper:2504.11805", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yue-wu", "dst": "p2:paper:2504.11805", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:emmet-houghton", "dst": "p2:paper:2504.11805", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lin-zhong", "dst": "p2:paper:2504.11805", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.06756", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yi-tian", "dst": "p2:paper:2509.06756", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:y-zheng", "dst": "p2:paper:2509.06756", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaoting-wang", "dst": "p2:paper:2509.06756", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ching-yi-lai", "dst": "p2:paper:2509.06756", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2508.15743", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:stergios-koutsioumpas", "dst": "p2:paper:2508.15743", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:tamas-noszko", "dst": "p2:paper:2508.15743", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hasan-sayginel", "dst": "p2:paper:2508.15743", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mark-webster", "dst": "p2:paper:2508.15743", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:joschka-roffe", "dst": "p2:paper:2508.15743", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2305.15767", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:mengyu-zhang", "dst": "p2:paper:2305.15767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiangyu-ren", "dst": "p2:paper:2305.15767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:guanglei-xi", "dst": "p2:paper:2305.15767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhenxing-zhang", "dst": "p2:paper:2305.15767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:qiaonian-yu", "dst": "p2:paper:2305.15767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fuming-liu", "dst": "p2:paper:2305.15767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hualiang-zhang", "dst": "p2:paper:2305.15767", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shengyu-zhang", "dst": "p2:paper:2305.15767", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.01353", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sophia-fuhui-lin", "dst": "p2:paper:2403.01353", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eric-c-peterson", "dst": "p2:paper:2403.01353", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:krishanu-sankar", "dst": "p2:paper:2403.01353", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:prasahnt-sivarajah", "dst": "p2:paper:2403.01353", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.03954", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:kai-zhang", "dst": "p2:paper:2509.03954", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jubo-xu", "dst": "p2:paper:2509.03954", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fang-zhang", "dst": "p2:paper:2509.03954", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:linghang-kong", "dst": "p2:paper:2509.03954", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhengfeng-ji", "dst": "p2:paper:2509.03954", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianxin-chen", "dst": "p2:paper:2509.03954", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.05795", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:seok-hyung-lee", "dst": "p2:paper:2510.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lucas-h-english", "dst": "p2:paper:2510.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stephen-d-bartlett", "dst": "p2:paper:2510.05795", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2410.03073", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yue-wu", "dst": "p2:paper:2410.03073", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:namitha-liyanage", "dst": "p2:paper:2410.03073", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lin-zhong", "dst": "p2:paper:2410.03073", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2307.03280", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:boris-m-varbanov", "dst": "p2:paper:2307.03280", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marc-serra-peralta", "dst": "p2:paper:2307.03280", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-byfield", "dst": "p2:paper:2307.03280", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:barbara-m-terhal", "dst": "p2:paper:2307.03280", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2402.04834", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:aviad-kaufmann", "dst": "p2:paper:2402.04834", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:itai-arad", "dst": "p2:paper:2402.04834", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2306.16476", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:asmae-benhemou", "dst": "p2:paper:2306.16476", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kaavya-sahay", "dst": "p2:paper:2306.16476", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lingling-lao", "dst": "p2:paper:2306.16476", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:benjamin-j-brown", "dst": "p2:paper:2306.16476", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2505.13599", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:marc-serra-peralta", "dst": "p2:paper:2505.13599", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:mackenzie-h-shaw", "dst": "p2:paper:2505.13599", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:barbara-m-terhal", "dst": "p2:paper:2505.13599", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1901.10847", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:savvas-varsamopoulos", "dst": "p2:paper:1901.10847", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:koen-bertels", "dst": "p2:paper:1901.10847", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:carmen-g-almudever", "dst": "p2:paper:1901.10847", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2509.10164", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hoshitaro-ohnishi", "dst": "p2:paper:2509.10164", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hideo-mukai", "dst": "p2:paper:2509.10164", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2110.05854", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:spiro-gicev", "dst": "p2:paper:2110.05854", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lloyd-c-l-hollenberg", "dst": "p2:paper:2110.05854", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:muhammad-usman", "dst": "p2:paper:2110.05854", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1801.01879", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:andrew-s-darmawan", "dst": "p2:paper:1801.01879", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:david-poulin", "dst": "p2:paper:1801.01879", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1411.3028", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:fern-h-e-watson", "dst": "p2:paper:1411.3028", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hussain-anwar", "dst": "p2:paper:1411.3028", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:dan-e-browne", "dst": "p2:paper:1411.3028", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2510.11593", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:seong-joon-park", "dst": "p2:paper:2510.11593", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hee-youl-kwak", "dst": "p2:paper:2510.11593", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yongjune-kim", "dst": "p2:paper:2510.11593", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2209.09219", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:xinyu-tan", "dst": "p2:paper:2209.09219", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:fang-zhang", "dst": "p2:paper:2209.09219", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:rui-chao", "dst": "p2:paper:2209.09219", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yaoyun-shi", "dst": "p2:paper:2209.09219", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jianxin-chen", "dst": "p2:paper:2209.09219", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2403.08706", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:andrew-s-darmawan", "dst": "p2:paper:2403.08706", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2203.04948", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:oscar-higgott", "dst": "p2:paper:2203.04948", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thomas-c-bohdanowicz", "dst": "p2:paper:2203.04948", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:aleksander-kubica", "dst": "p2:paper:2203.04948", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:steven-t-flammia", "dst": "p2:paper:2203.04948", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:earl-t-campbell", "dst": "p2:paper:2203.04948", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.07433", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:nadine-meister", "dst": "p2:paper:2405.07433", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-a-pattison", "dst": "p2:paper:2405.07433", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:john-preskill", "dst": "p2:paper:2405.07433", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2504.13043", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:john-blue", "dst": "p2:paper:2504.13043", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:harshil-avlani", "dst": "p2:paper:2504.13043", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhiyang-he", "dst": "p2:paper:2504.13043", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:liu-ziyin", "dst": "p2:paper:2504.13043", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:isaac-l-chuang", "dst": "p2:paper:2504.13043", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2212.11632", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:antonio-demarti-iolius", "dst": "p2:paper:2212.11632", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:josu-etxezarreta-martinez", "dst": "p2:paper:2212.11632", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:patricio-fuentes", "dst": "p2:paper:2212.11632", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pedro-m-crespo", "dst": "p2:paper:2212.11632", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.05785", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:yimu-bao", "dst": "p2:paper:2411.05785", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sajant-anand", "dst": "p2:paper:2411.05785", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2310.05900", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:johannes-bausch", "dst": "p2:paper:2310.05900", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrew-w-senior", "dst": "p2:paper:2310.05900", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:francisco-j-h-heras", "dst": "p2:paper:2310.05900", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:thomas-edlich", "dst": "p2:paper:2310.05900", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alex-davies", "dst": "p2:paper:2310.05900", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:michael-newman", "dst": "p2:paper:2310.05900", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:cody-jones", "dst": "p2:paper:2310.05900", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:kevin-satzinger", "dst": "p2:paper:2310.05900", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2411.18090", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:hao-wang", "dst": "p2:paper:2411.18090", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:erjia-xiao", "dst": "p2:paper:2411.18090", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:wenbo-mu", "dst": "p2:paper:2411.18090", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:songhuan-he", "dst": "p2:paper:2411.18090", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:zhongyi-ni", "dst": "p2:paper:2411.18090", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lingfeng-zhang", "dst": "p2:paper:2411.18090", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:xiaokun-zhan", "dst": "p2:paper:2411.18090", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:yifei-cui", "dst": "p2:paper:2411.18090", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1405.4883", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:sergey-bravyi", "dst": "p2:paper:1405.4883", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:martin-suchara", "dst": "p2:paper:1405.4883", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:alexander-vargo", "dst": "p2:paper:1405.4883", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2110.10896", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:debasmita-bhoumik", "dst": "p2:paper:2110.10896", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:pinaki-sen", "dst": "p2:paper:2110.10896", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:ritajit-majumdar", "dst": "p2:paper:2110.10896", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:susmita-sur-kolay", "dst": "p2:paper:2110.10896", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:latesh-kumar-k-j", "dst": "p2:paper:2110.10896", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sundaraja-sitharama-iyengar", "dst": "p2:paper:2110.10896", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2309.10331", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:alex-fischer", "dst": "p2:paper:2309.10331", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:akimasa-miyake", "dst": "p2:paper:2309.10331", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2405.01151", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:diego-forlivesi", "dst": "p2:paper:2405.01151", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:lorenzo-valentini", "dst": "p2:paper:2405.01151", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:marco-chiani", "dst": "p2:paper:2405.01151", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:1812.08186", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:david-k-tuckett", "dst": "p2:paper:1812.08186", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:andrew-s-darmawan", "dst": "p2:paper:1812.08186", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:christopher-t-chubb", "dst": "p2:paper:1812.08186", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:sergey-bravyi", "dst": "p2:paper:1812.08186", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:stephen-d-bartlett", "dst": "p2:paper:1812.08186", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:steven-t-flammia", "dst": "p2:paper:1812.08186", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.14255", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:long-d-h-my", "dst": "p2:paper:2512.14255", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:shao-hen-chiew", "dst": "p2:paper:2512.14255", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:jing-hao-chai", "dst": "p2:paper:2512.14255", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:hui-khoon-ng", "dst": "p2:paper:2512.14255", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2408.12135", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:cody-jones", "dst": "p2:paper:2408.12135", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2512.08914", "dst": "p2:axis:qec", "rel": "paper-in-axis"}
{"type": "edge", "src": "p2:person:david-zenati", "dst": "p2:paper:2512.08914", "rel": "authored-by"}
{"type": "edge", "src": "p2:person:eliya-nachmani", "dst": "p2:paper:2512.08914", "rel": "authored-by"}
{"type": "edge", "src": "p2:paper:2303.17580", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2308.00352", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2304.03442", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2305.16291", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2308.09687", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2305.10601", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2310.06770", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2311.12983", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2308.03688", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2302.04761", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2303.11366", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2304.05128", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2310.08560", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2308.11432", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2309.07864", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2405.10467", "dst": "p2:axis:agents", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2002.05651", "dst": "p2:axis:energy", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2104.10350", "dst": "p2:axis:energy", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2309.14393", "dst": "p2:axis:energy", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2306.16863", "dst": "p2:axis:energy", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2311.03378", "dst": "p2:axis:energy", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:1802.06441", "dst": "p2:axis:qec", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:1811.07835", "dst": "p2:axis:qec", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2310.05900", "dst": "p2:axis:qec", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2310.05867", "dst": "p2:axis:qec", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2101.08946", "dst": "p2:axis:qec", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2103.02202", "dst": "p2:axis:qec", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2001.11427", "dst": "p2:axis:qec", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:1705.09334", "dst": "p2:axis:qec", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:1903.11027", "dst": "p2:axis:fusion", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2205.13542", "dst": "p2:axis:fusion", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2104.10490", "dst": "p2:axis:fusion", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:1901.03642", "dst": "p2:axis:fusion", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:1912.04838", "dst": "p2:axis:fusion", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:1901.08248", "dst": "p2:axis:fusion", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2411.13676", "dst": "p2:axis:attention", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2406.07887", "dst": "p2:axis:attention", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:paper:2405.16712", "dst": "p2:axis:attention", "rel": "anchor-paper-in-axis"}
{"type": "edge", "src": "p2:person:harrison_chase", "dst": "p2:axis:agents", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:chi_wang", "dst": "p2:axis:agents", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:omar_khattab", "dst": "p2:axis:agents", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:shunyu_yao", "dst": "p2:axis:agents", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:joon_sung_park", "dst": "p2:axis:agents", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:carlos_guestrin", "dst": "p2:axis:agents", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:charles_packer", "dst": "p2:axis:agents", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:sasha_luccioni", "dst": "p2:axis:energy", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:emma_strubell", "dst": "p2:axis:energy", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:roy_schwartz", "dst": "p2:axis:energy", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:mosharaf_chowdhury", "dst": "p2:axis:energy", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:lasse_wolff_anthony", "dst": "p2:axis:energy", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:oscar_higgott", "dst": "p2:axis:qec", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:craig_gidney", "dst": "p2:axis:qec", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:johannes_bausch", "dst": "p2:axis:qec", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:david_poulin", "dst": "p2:axis:qec", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:song_han", "dst": "p2:axis:fusion", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:zhijian_liu", "dst": "p2:axis:fusion", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:tri_dao_p2", "dst": "p2:axis:attention", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:albert_gu", "dst": "p2:axis:attention", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:soham_de", "dst": "p2:axis:attention", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:person:opher_lieber", "dst": "p2:axis:attention", "rel": "person-leads-axis"}
{"type": "edge", "src": "p2:org:langchain_org", "dst": "p2:axis:agents", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:crewai_org", "dst": "p2:axis:agents", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:ai21_labs", "dst": "p2:axis:attention", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:letta_org", "dst": "p2:axis:agents", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:stanford_nlp_dspy", "dst": "p2:axis:agents", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:ml_energy_org", "dst": "p2:axis:energy", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:codecarbon_org", "dst": "p2:axis:energy", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:green_software_foundation", "dst": "p2:axis:energy", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:mlcommons_power", "dst": "p2:axis:energy", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:google_quantum_ai", "dst": "p2:axis:qec", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:riverlane", "dst": "p2:axis:qec", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:aws_braket_qec", "dst": "p2:axis:qec", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:errorcorrectionzoo", "dst": "p2:axis:qec", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:mit_han_lab", "dst": "p2:axis:fusion", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:dao_ailab", "dst": "p2:axis:attention", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:org:goomba_lab", "dst": "p2:axis:attention", "rel": "org-leads-axis"}
{"type": "edge", "src": "p2:benchmark:swe_bench_ds", "dst": "p2:axis:agents", "rel": "benchmark-for-axis"}
{"type": "edge", "src": "p2:benchmark:gaia_ds", "dst": "p2:axis:agents", "rel": "benchmark-for-axis"}
{"type": "edge", "src": "p2:benchmark:agentbench_ds", "dst": "p2:axis:agents", "rel": "benchmark-for-axis"}
{"type": "edge", "src": "p2:benchmark:webarena_ds", "dst": "p2:axis:agents", "rel": "benchmark-for-axis"}
{"type": "edge", "src": "p2:benchmark:toolbench_ds", "dst": "p2:axis:agents", "rel": "benchmark-for-axis"}
{"type": "edge", "src": "p2:benchmark:ml_energy_leaderboard", "dst": "p2:axis:energy", "rel": "benchmark-for-axis"}
{"type": "edge", "src": "p2:dataset:nuscenes_ds", "dst": "p2:axis:fusion", "rel": "dataset-for-axis"}
{"type": "edge", "src": "p2:dataset:waymo_open_ds", "dst": "p2:axis:fusion", "rel": "dataset-for-axis"}
{"type": "edge", "src": "p2:dataset:kitti_ds", "dst": "p2:axis:fusion", "rel": "dataset-for-axis"}
{"type": "edge", "src": "p2:dataset:anti_uav_ds", "dst": "p2:axis:defense", "rel": "dataset-for-axis"}
{"type": "edge", "src": "p2:dataset:nuscenes_radar", "dst": "p2:axis:fusion", "rel": "dataset-for-axis"}
{"type": "edge", "src": "p2:benchmark:longbench_p2", "dst": "p2:axis:attention", "rel": "benchmark-for-axis"}