--- license: other pretty_name: Ropedia Xperience-10M Task Suite Artifacts tags: - robotics - embodied-ai - multimodal - ropedia - xperience-10m - evaluation - baseline - neural-network - pytorch - retrieval task_categories: - robotics - time-series-forecasting - text-retrieval language: - en size_categories: - n<1K --- # Ropedia Xperience-10M Task Suite Artifacts This dataset repo contains the derived evidence layer for the public Xperience-10M sample episode released by Ropedia: metrics, predictions, manifests, charts, diagrams, notes, reproduction scripts, and the small neural MLP task-head artifacts. The dashboard assets follow a Ropedia-inspired visual system: dark 4D-world canvas, lime-green accents, point-cloud texture, thin green cards, and research-grade typography, while all labels and metrics are script-generated from committed result files. It does **not** contain raw Xperience-10M videos or raw `annotation.hdf5`. Download raw data only from the official Ropedia / Hugging Face sources and follow their terms. Current scale-up status: the full `ropedia-ai/xperience-10m` Hugging Face dataset is still gated for this account. The A100 relay has been configured to poll access, download a 32-episode stratified pilot subset after approval, validate it, transfer it to H20, and run the readiness gate. Until that completes, the committed Qwen3-Omni artifacts remain smoke/debug evidence, not real 32-episode held-out metrics. ## Why This Repo Exists This is the reviewable half of the project. You can inspect the task outputs, compare the committed metrics, and understand the single-episode limitations without downloading the raw videos first. ## Evidence Contract | Claim layer | Evidence | Boundary | | --- | --- | --- | | Data windows | `results/episode_task_suite/windows.csv`, `shared_windows.npz`, `summary_report.json` | one public sample episode | | Feature contract | `results/episode_task_suite/feature_manifest.json`, `available_modalities.json` | 8,378 current features; audio documented but not featurized | | 12-task suite | per-task `metrics.json`, predictions, confusion matrices | chronological single-episode split | | Neural heads | `results/episode_task_suite/neural_mlp/` | compact MLP heads, not a foundation model | | Research directions | `research_direction_taxonomy.json`, extension probe results | direct/proxy/diagnostic evidence, not full solutions | | Qwen3-Omni | `DATA_BLOCKER_REPORT.md`, `A100_HF_RELAY_STATUS.md` | smoke-only until 32 valid episodes are available | | Publication hygiene | `docs/data/publication_audit.json`, `scripts/validate_publication_package.py` | public files and HF bundles only | | Citation metadata | `PROJECT_README.md`, `docs/data/project_manifest.json`, GitHub `CITATION.cff` | code/data license boundary remains explicit | ## What Is Included - `results/**/*.json`: verified metrics and metadata for minimal and neural MLP runs - `results/**/*.csv`: predictions, confusion matrices, per-class metrics, windows, boundaries - `results/**/history.json`: neural MLP training traces - `docs/assets/*.svg` and `docs/assets/*.png`: generated diagrams, charts, and ChatGPT-image-backed overview figures - `docs/assets/task_suite_infographic.png`: ChatGPT-image-backed infographic with larger public-sample modality atlas thumbnails, including audio waveform context, and verified metric overlays - `docs/data/summary_metrics.json`: dashboard-readable summary bundle - `docs/data/evidence_contract.json`: machine-readable proof boundary - `docs/data/publication_audit.json`: machine-readable publication hygiene check - `docs/data/project_manifest.json`: machine-readable public URL and citation metadata - `docs/data/research_directions.json`: generated four-track taxonomy for the website - `docs/data/research_direction_extensions.json`: four extra data-backed probes, one per research direction - `docs/data/task_walkthroughs.json`: beginner-oriented input/process/output guide for all 12 tasks - `results/episode_task_suite/research_directions/`: JSON, CSV, and Markdown task-to-research-track mapping - `results/episode_task_suite/research_direction_extensions/`: metrics, prediction CSVs, rank CSVs, and Markdown summary for the four extension probes - `results/episode_task_suite/task_walkthroughs/`: case-study walkthroughs for every task contract - `scripts/*.py`: reproduction scripts - `scripts/validate_publication_package.py`: public bundle validator - `notes/*.md`: interpretation and reproducibility notes The companion model repo stores the lightweight model checkpoints and mirrors the binary arrays (`model.npz`, `model.pt`, and compact neural prediction arrays). This artifact dataset stays focused on reviewable CSV/JSON/Markdown, scripts, notes, and visual assets: https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines ## Links | Resource | URL | | --- | --- | | Hugging Face Space | https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite | | Live Hugging Face app | https://cy0307-ropedia-xperience-10m-task-suite.static.hf.space/ | | Hugging Face collection | https://huggingface.co/collections/cy0307/ropedia-xperience-10m-task-suite | | Minimal and neural task baseline repo | https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines | | GitHub repo | https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite | | GitHub Pages dashboard | https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/ | | Xperience-10M website | https://ropedia.com/dataset | | Xperience-10M release page | https://ropedia.com/blog/20260316_xperience_10m | | Ropedia GitHub organization | https://github.com/Ropedia | | HOMIE Toolkit | https://github.com/Ropedia/HOMIE-toolkit | | Xperience-10M dataset | https://huggingface.co/datasets/ropedia-ai/xperience-10m | | Xperience-10M sample | https://huggingface.co/datasets/ropedia-ai/xperience-10m-sample | ## Scope The artifacts validate one public sample episode: - 5,821 aligned frames - 1,161 sliding windows - 8,378 current feature dimensions, with audio documented but not featurized - 12 supervised/self-supervised task definitions - minimal linear/ridge baselines and neural MLP heads for all 12 tasks - four direction-extension probes with minimal and neural MLP baselines - chronological 70/30 split For research claims, rerun the same scripts over many episodes and evaluate on held-out episodes. ## Neural MLP Result Snapshot These are single-episode chronological-split metrics. They are useful for debugging task definitions and input contracts, not for claiming cross-episode generalization. | Task | Neural metric | Minimal metric | | --- | ---: | ---: | | `timeline_action` macro-F1 | 0.0263 | 0.0500 | | `timeline_subtask` macro-F1 | 0.0175 | 0.0495 | | `transition_detection` macro-F1 | 0.6485 | 0.6552 | | `next_action` macro-F1 | 0.0235 | 0.0593 | | `hand_trajectory_forecast` MPJPE, lower is better | 0.1116 | 0.8223 | | `contact_prediction` macro-F1 | 1.0000 | 1.0000 | | `object_relevance` micro-F1 | 0.1798 | 0.1839 | | `caption_grounding` MRR | 0.0178 | 0.0172 | | `cross_modal_retrieval` MRR | 0.1530 | 0.2634 | | `modality_reconstruction` R2 | -0.0102 | -0.0160 | | `temporal_order` F1 | 0.8718 | 0.5487 | | `misalignment_detection` F1 | 0.7335 | 0.4866 | Primary NN artifact path: `results/episode_task_suite/neural_mlp//` ## Four Research Directions The current 12 tasks are organized into the four Ropedia research directions with two baselines per task: minimal interpretable heads and neural MLP heads. | Direction | Current status | Evidence | | --- | --- | --- | | A. Human Modeling & Motion Understanding | partially implemented | hand trajectory and contact are direct; action/object tasks are proxies | | B. 3D/4D Reconstruction & Neural Rendering | proxy tasks only | retrieval, reconstruction, and misalignment diagnose prerequisites | | C. Egocentric Vision & Interaction | strongest implemented track | 6 direct tasks plus order/alignment diagnostics | | D. Scene Reconstruction & World Modeling | early proxy tasks | state, object, retrieval, reconstruction, and temporal probes | Primary taxonomy artifact: `results/episode_task_suite/research_directions/research_direction_taxonomy.json` ## Four Direction-Extension Probes The artifact bundle also includes one extra coded probe for each Ropedia research direction. These are still single-episode diagnostics, but they make the four-direction roadmap concrete. | Direction | Extension task | Minimal | Neural MLP | | --- | --- | ---: | ---: | | A. Human Modeling & Motion Understanding | `body_motion_intensity` | 0.7827 macro-F1 | 0.7986 macro-F1 | | B. 3D/4D Reconstruction & Neural Rendering | `multi_view_consistency_retrieval` | 0.5534 MRR | 0.3469 MRR | | C. Egocentric Vision & Interaction | `action_phase_progress` | 0.3416 MAE | 0.3038 MAE | | D. Scene Reconstruction & World Modeling | `ego_motion_forecast` | 0.1989 MAE | 0.0989 MAE | Primary extension artifact: `results/episode_task_suite/research_direction_extensions/research_direction_extension_results.json` ## Junior Task Walkthroughs Each task has a case study, input contract, middle process modules, output contract, metric, and current limitation. Start here when onboarding a junior researcher or engineer: `results/episode_task_suite/task_walkthroughs/TASK_WALKTHROUGHS.md` ## Pending 32-Episode Pilot | Item | Value | | --- | --- | | Selection strategy | stratified round-robin across top-level session UUIDs | | Candidate scan | first 64 top-level session UUIDs | | Valid complete candidates | 680 | | Selected pilot episodes | 32 from 32 session UUIDs | | Estimated raw subset | about 72.0 GB | | Excluded file type | `visualization.rrd` | | Blocker | HF gated dataset approval pending | ![12-task infographic](assets/task_suite_infographic.png) ![Verified episode pipeline](assets/pipeline_diagram.png) ![Minimal task architectures](assets/task_architectures.png)