{ "title": "Ropedia Xperience-10M Task Suite Project Packet", "version": "2026-06-01", "scope_status": { "validated_data": "one public Xperience-10M sample episode", "aligned_frames": 5821, "sliding_windows": 1161, "current_feature_dimensions": 8378, "core_task_count": 12, "neural_head_count": 12, "direction_extension_probe_count": 4, "raw_xperience10m_data_in_repo": false, "audio_feature_status": "Audio is present in the sample MP4 streams and shown in the figures, but the current baseline feature vector does not include an extracted audio block.", "qwen3_omni_32_episode_claim": false, "qwen3_omni_status": "Setup-stage until at least 32 valid episodes are available and held-out episode evaluation finishes." }, "reading_path": [ { "step": 1, "question": "What is the current project scope?", "primary_artifacts": [ "PROJECT_STATUS.md", "docs/data/project_status.json", "RESEARCH_ROADMAP.md", "docs/data/research_roadmap.json", "EVIDENCE_CONTRACT.md", "ARTIFACT_GUIDE.md", "EVALUATION_PROTOCOL.md", "FIGURE_INDEX.md", "SOURCE_ALIGNMENT_AUDIT.md", "XPERIENCE10M_DATASET_CARD_ALIGNMENT.md", "docs/data/evidence_contract.json", "docs/data/artifact_index.json", "docs/data/brand_assets.json", "docs/data/evaluation_protocol.json", "docs/data/figure_index.json", "docs/data/source_alignment_audit.json", "docs/data/xperience10m_dataset_card_alignment.json", "docs/data/mirror_parity.json", "docs/data/publication_audit.json", "docs/data/scope_claims_audit.json", "docs/data/website_integrity.json" ], "readout": "The project status table and roadmap give the compact current-state summary. Single-episode task engineering, metrics, visualizations, public website integrity, mirror parity, and scale-up status checks are implemented; cross-episode generalization and 32-episode Qwen3-Omni metrics are later milestones." }, { "step": 2, "question": "What do the official Xperience-10M dataset and sample cards say?", "primary_artifacts": [ "XPERIENCE10M_DATASET_CARD_ALIGNMENT.md", "docs/data/xperience10m_dataset_card_alignment.json", "https://huggingface.co/datasets/ropedia-ai/xperience-10m", "https://huggingface.co/datasets/ropedia-ai/xperience-10m-sample" ], "readout": "The full upstream dataset is a manually gated large-scale 4D multimodal egocentric source. The public sample card records the sample license, HOMIE Toolkit path, and Rerun 0.29.0 visualization path. This repo validates one public sample episode and lists the current project coverage." }, { "step": 3, "question": "Are source facts consistently presented?", "primary_artifacts": [ "SOURCE_ALIGNMENT_AUDIT.md", "docs/data/source_alignment_audit.json", "scripts/validate_source_alignment.py" ], "readout": "The source-alignment report checks full-dataset metadata, API-listing notes, public sample license/tooling, and project coverage across repo docs, website, and HF cards." }, { "step": 4, "question": "How exactly are the tasks evaluated?", "primary_artifacts": [ "EVALUATION_PROTOCOL.md", "docs/data/evaluation_protocol.json", "scripts/build_evaluation_protocol.py" ], "readout": "The protocol fixes the 20-frame window unit, chronological split, train-only normalization, leakage controls, per-task input/target/metric contracts, and current limitations." }, { "step": 5, "question": "How can the public pipeline be reproduced?", "primary_artifacts": [ "REPRODUCIBILITY.md", "docs/data/reproducibility_matrix.json", "notes/reproducibility_audit.md" ], "readout": "The public sample pipeline has explicit commands, expected outputs, and a prior exact-match reproduction check over the committed metrics." }, { "step": 6, "question": "What is inside one model input?", "primary_artifacts": [ "results/episode_task_suite/windows.csv", "results/episode_task_suite/feature_manifest.json", "results/episode_task_suite/available_modalities.json", "docs/data/modality_atlas.json" ], "readout": "The current model input is an 8,378-dimensional aligned window vector with explicit feature-block boundaries, and the readable atlas shows each public-sample modality without raw data redistribution." }, { "step": 7, "question": "Do the task metrics have committed evidence?", "primary_artifacts": [ "results/episode_task_suite/summary_report.json", "results/episode_task_suite/neural_mlp/", "docs/data/summary_metrics.json" ], "readout": "Each of the 12 tasks has minimal-head metrics and a matching neural MLP result over the same window contracts." }, { "step": 8, "question": "What is the staged scale-up path?", "primary_artifacts": [ "RESEARCH_ROADMAP.md", "docs/data/research_roadmap.json", "results/omni_finetune/DATA_ACCESS_STATUS.md", "results/omni_finetune/MULTI_EPISODE_ACCESS_STATUS.md", "scripts/omni/discover_xperience10m_sources.py" ], "readout": "The next milestone is a 32-episode held-out-episode Qwen3-Omni LoRA pilot after gated Xperience-10M access is available." } ], "project_status": "PROJECT_STATUS.md", "project_status_json": "docs/data/project_status.json", "research_roadmap": "RESEARCH_ROADMAP.md", "research_roadmap_json": "docs/data/research_roadmap.json", "evaluation_protocol": "EVALUATION_PROTOCOL.md", "evaluation_protocol_json": "docs/data/evaluation_protocol.json", "source_alignment_audit": "SOURCE_ALIGNMENT_AUDIT.md", "source_alignment_audit_json": "docs/data/source_alignment_audit.json", "artifact_guide": "ARTIFACT_GUIDE.md", "artifact_index": "docs/data/artifact_index.json", "brand_assets": "docs/data/brand_assets.json", "figure_index": "FIGURE_INDEX.md", "figure_index_json": "docs/data/figure_index.json", "reproducibility_matrix": "docs/data/reproducibility_matrix.json", "public_surfaces": { "github_repo": "https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite", "github_pages": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/", "hf_space": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite", "hf_static_app": "https://cy0307-ropedia-xperience-10m-task-suite.static.hf.space/", "hf_artifacts": "https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts", "hf_model_baselines": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines" }, "current_reading_notes": [ "Cross-environment generalization is evaluated in the later multi-episode stage.", "The Qwen3-Omni setup run is separate from the planned 32-episode fine-tune.", "Feature-vector reconstruction is separate from pixel-depth, mesh, NeRF, or Gaussian reconstruction.", "Raw Xperience-10M data is not redistributed in this repo." ] }