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
| license: other | |
| library_name: numpy | |
| tags: | |
| - robotics | |
| - embodied-ai | |
| - multimodal | |
| - ropedia | |
| - xperience-10m | |
| - baseline | |
| - linear-model | |
| - retrieval | |
| metrics: | |
| - accuracy | |
| - f1 | |
| - mean-reciprocal-rank | |
| - mean-squared-error | |
| model-index: | |
| - name: Ropedia Minimal Task Baselines | |
| results: | |
| - task: | |
| type: robotics | |
| name: Cross-modal retrieval | |
| dataset: | |
| type: ropedia-ai/xperience-10m-sample | |
| name: Xperience-10M public sample episode | |
| metrics: | |
| - type: top_5_accuracy | |
| value: 0.3764 | |
| name: top-5 retrieval accuracy | |
| - type: mrr | |
| value: 0.2634 | |
| name: mean reciprocal rank | |
| - task: | |
| type: robotics | |
| name: Transition detection | |
| dataset: | |
| type: ropedia-ai/xperience-10m-sample | |
| name: Xperience-10M public sample episode | |
| metrics: | |
| - type: f1 | |
| value: 0.6552 | |
| name: macro-F1 | |
| # Ropedia Minimal Task Baselines | |
| This repo stores the minimal baseline weights and metrics for the 12-task Ropedia episode suite. | |
| These are intentionally small, transparent baselines: | |
| - z-score + linear softmax classifiers, | |
| - dual ridge regression/projection heads, | |
| - sigmoid multi-label logistic regression, | |
| - cosine ranking for retrieval tasks. | |
| They are not deep robot policies or foundation models. Their purpose is to make every input/output contract auditable before scaling to many episodes. | |
| ## Included | |
| - `artifacts/**/model.npz`: minimal baseline weights, scalers, and labels | |
| - `artifacts/**/metrics.json`: committed metrics | |
| - `artifacts/**/feature_manifest.json`: feature block boundaries where relevant | |
| - `scripts/*.py`: training and visualization scripts | |
| - `notes/*.md`: interpretation and reproducibility notes | |
| The companion artifact dataset repo stores CSV/JSON predictions and dashboard assets: | |
| https://huggingface.co/datasets/cy0307/ropedia-episode-task-suite-artifacts | |
| The public visual dashboard is here: | |
| https://huggingface.co/spaces/cy0307/ropedia-episode-task-suite | |
| Direct static app: | |
| https://cy0307-ropedia-episode-task-suite.static.hf.space/ | |
| The full Hugging Face collection is here: | |
| https://huggingface.co/collections/cy0307/ropedia-episode-task-suite | |
| ## Minimal Architecture | |
|  | |
| ## Metrics Snapshot | |
| | Task | Minimal head | Main metric | | |
| | --- | --- | ---: | | |
| | `timeline_action` | linear softmax | 0.0500 macro-F1 | | |
| | `timeline_subtask` | linear softmax | 0.0495 macro-F1 | | |
| | `transition_detection` | linear softmax | 0.6552 macro-F1 | | |
| | `next_action` | linear softmax | 0.0593 macro-F1 | | |
| | `hand_trajectory_forecast` | ridge regression | 0.8223 MPJPE | | |
| | `contact_prediction` | linear softmax | 1.0000 macro-F1 | | |
| | `object_relevance` | multi-label logistic | 0.1839 micro-F1 | | |
| | `caption_grounding` | ridge + cosine rank | 0.0172 MRR | | |
| | `cross_modal_retrieval` | ridge + cosine rank | 0.3764 top-5 | | |
| | `modality_reconstruction` | ridge regression | -0.0160 R2 | | |
| | `temporal_order` | binary softmax | 0.5487 F1 | | |
| | `misalignment_detection` | binary softmax | 0.4866 F1 | | |
| ## Data Notice | |
| This repo does not redistribute raw Ropedia videos or raw `annotation.hdf5`. Download the original sample from Ropedia / Hugging Face and follow the dataset terms: | |
| - https://huggingface.co/datasets/ropedia-ai/xperience-10m-sample | |
| - https://ropedia.com/dataset | |
| ## Source | |
| GitHub: | |
| https://github.com/ChaoYue0307/ropedia-episode-task-suite | |
| GitHub Pages: | |
| https://chaoyue0307.github.io/ropedia-episode-task-suite/ | |