Project Brief

This project presents Ropedia Xperience-10M through two public evidence lines. Line 1 turns one public sample episode into a concrete 20-task embodied-AI task lab. Line 2 compares selected 128-episode public-safe artifacts across aligned baselines, Qwen3-Omni v6, Cosmos3-Super, and Cosmos3-Nano.

Research Intent

The public sample is treated as a small but real research system, while the selected-128 line shows the first same-split scale-up comparison. The project does not blend those two evidence types. A reader should be able to trace one model input, understand each task, reproduce the public-sample results, compare the 128-episode method rows, and see what remains before stronger model-quality claims.

Capability Map

Capability	Evidence in this project
Data understanding	`feature_manifest.json`, `available_modalities.json`, modality atlas, episode-window HF viewer
Task design	20 unified task contracts, task cards, case-study walkthroughs, and four research-direction extension probes
Evaluation rigor	chronological split, per-task metrics, predictions, confusion matrices, leakage notes, and generated takeaways
Scale-up planning	Final verified 96/16/16 Qwen3-Omni v6 diagnostic row, same-split 128-episode baseline alignment, Cosmos3-Nano compatibility diagnostics, Cosmos3-Super diagnostics, and policy-model candidates after action-space conversion

What Exists Now

Evidence view	Current artifact
Line 1 data unit	1 public sample episode, 5,821 frames, 1,161 synchronized 20-frame windows
Line 2 data unit	Selected 96/16/16 split over 128 source episodes, 34,269 Qwen3-Omni v6 multiscale windows, and public-safe processed features linked to official gated episode paths
Modalities	Video-derived features, audio, depth, pose/SLAM, mocap, IMU, calibration, and language-derived features
Task suite	20 embodied-AI task contracts with inputs, targets, metrics, predictions, and setup alignment
Line 1 models	Minimal linear/ridge/logistic baselines plus compact PyTorch MLP heads for the unified 20-task public-sample suite
Line 2 methods	Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, and Cosmos3-Nano Future Window; 140/140 selected-128 scores, including 6 marked compact-proxy cells
Research map	Four Ropedia research directions with direct, proxy, diagnostic, and extension-task coverage
Qwen3 lineage	Qwen3-Omni v1-v6 are run versions inside Line 2: v1-v4 are pipeline-hardening/ablation evidence, v5 is the pinned prior multiscale release, and v6 is the current 20-task Qwen3-Omni row

How To Read It

Start with PUBLIC_READER_MAP.md if you need to choose between GitHub, the website, Hugging Face artifacts, baseline weights, model-result repos, or release-health files.
Start with the website or this brief to understand the project shape.
Open RESEARCH_ROADMAP.md to see how the work scales from the public sample to multi-episode modeling.
Open EVALUATION_PROTOCOL.md before comparing task scores.
Use RESEARCH_TAKEAWAYS.md for the current metric interpretation.
Inspect results/episode_task_suite/feature_manifest.json to understand one model input.
Use TASK_SUITE_20.md and docs/data/task_suite_20.json to read the unified 20-task suite; the historical docs/data/tier2_task_suite.json path stores the tasks 13-20 result bundle.
Use QWEN3_OMNI_RUN_LINEAGE.md and docs/data/qwen3_omni_run_lineage.json to read v1-v6 correctly.
Use docs/data/omni_finetune_verified_result.json for the current multi-episode Qwen3-Omni v6 result.

What This Enables

Line 1 is enough to build and verify task definitions, feature contracts, metrics, visualization, and baseline code. It is not enough to measure final general embodied-AI model quality. Line 2 verifies the selected-128 held-out comparison surface and the Qwen3-Omni v6 diagnostic row; the next research stage is action/subtask error analysis, stronger structured-output training, and policy-target conversion before larger backbone claims.

Best Entry Points

Entry point	Link
Public reader map	https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/PUBLIC_READER_MAP.md
Visual dashboard	https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/
Interactive HF Space	https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite
Derived artifacts	https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts
Baseline model bundle	https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines
Official Xperience-10M dataset	https://huggingface.co/datasets/ropedia-ai/xperience-10m