Robotics
PyTorch
Cosmos
xperience10m_task_baseline_suite
embodied-ai
multimodal
xperience-10m
baseline
evaluation
qwen3-omni
Instructions to use cy0307/ropedia-xperience-10m-task-baselines with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use cy0307/ropedia-xperience-10m-task-baselines with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| { | |
| "title": "Ropedia Xperience-10M Project Brief", | |
| "summary": "A concise first-reader brief for the public-sample embodied-AI task lab, the first Qwen3-Omni diagnostic pilot, and the multi-model scale-up path.", | |
| "research_intent": "Treat the public Xperience-10M sample as a small but real research system, then connect it to verified multi-episode experiments without presenting weak diagnostic results as final model quality.", | |
| "capability_map": [ | |
| { | |
| "capability": "Data understanding", | |
| "evidence": "feature_manifest.json, available_modalities.json, modality atlas, and the episode-window HF viewer" | |
| }, | |
| { | |
| "capability": "Task design", | |
| "evidence": "12 task contracts, task cards, case-study walkthroughs, and four research-direction extension probes" | |
| }, | |
| { | |
| "capability": "Evaluation rigor", | |
| "evidence": "chronological split, per-task metrics, predictions, confusion matrices, leakage notes, and generated takeaways" | |
| }, | |
| { | |
| "capability": "Scale-up planning", | |
| "evidence": "final verified 96/16/16 Qwen3-Omni diagnostic result, same-split 128-episode baseline alignment, Cosmos3-Nano compatibility branch, and policy-model candidates after action-space conversion" | |
| } | |
| ], | |
| "current_artifacts": [ | |
| { | |
| "layer": "Data unit", | |
| "status": "1 public sample episode, 5,821 frames, 1,161 synchronized 20-frame windows" | |
| }, | |
| { | |
| "layer": "Modalities", | |
| "status": "Video-derived features, audio, depth, pose/SLAM, mocap, IMU, calibration, and language-derived features" | |
| }, | |
| { | |
| "layer": "Task suite", | |
| "status": "12 embodied-AI task contracts with inputs, targets, metrics, predictions, and case-study walkthroughs" | |
| }, | |
| { | |
| "layer": "Models", | |
| "status": "Minimal linear/ridge/logistic baselines plus compact PyTorch MLP heads for the same 12 tasks" | |
| }, | |
| { | |
| "layer": "Research map", | |
| "status": "Four Ropedia research directions with direct, proxy, diagnostic, and extension-task coverage" | |
| }, | |
| { | |
| "layer": "Scale-up path", | |
| "status": "A selected 96/16/16 Qwen3-Omni LoRA final diagnostic result is verified; strict-JSON validity meets target, while weak action/subtask metrics guide the next error-analysis pass" | |
| } | |
| ], | |
| "reading_order": [ | |
| "Start with the website or PROJECT_BRIEF.md 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 docs/data/omni_finetune_verified_result.json for the current multi-episode Qwen3-Omni pilot result." | |
| ], | |
| "scope_boundary": "The public sample is enough to build and verify task definitions, feature contracts, metrics, visualization, and baseline code. The final multi-episode Qwen3-Omni diagnostic result verifies the training loop and strict-JSON output reliability, but does not yet show strong action/subtask model quality.", | |
| "next_stage": "Improve action/subtask quality through error analysis before larger robustness or alternative-backbone claims.", | |
| "entry_points": { | |
| "visual_dashboard": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/", | |
| "hf_space": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite", | |
| "artifact_dataset": "https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts", | |
| "baseline_model_bundle": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines", | |
| "official_xperience10m_dataset": "https://huggingface.co/datasets/ropedia-ai/xperience-10m" | |
| } | |
| } | |