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Browse files- PROJECT_README.md +17 -11
- README.md +2 -1
- TASK_METHOD_20_RESULT_MATRIX.md +42 -0
- data/artifact_index.json +42 -20
- data/figure_index.json +3 -3
- data/mirror_parity.json +244 -164
- data/public_surface_qa.json +8 -8
- data/publication_audit.json +9 -9
- data/quality_gates.json +1 -1
- data/scope_claims_audit.json +1 -1
- data/source_alignment_audit.json +1 -1
- data/task_method_20_result_matrix.json +0 -0
- data/task_surface_integrity.json +1 -1
- data/unified_task_model_radar.json +0 -0
- data/website_integrity.json +21 -16
- docs/assets/charts/unified_task_model_radar.svg +20 -18
- docs/data/artifact_index.json +42 -20
- docs/data/figure_index.json +3 -3
- docs/data/mirror_parity.json +244 -164
- docs/data/public_surface_qa.json +8 -8
- docs/data/publication_audit.json +9 -9
- docs/data/quality_gates.json +1 -1
- docs/data/scope_claims_audit.json +1 -1
- docs/data/source_alignment_audit.json +1 -1
- docs/data/task_method_20_result_matrix.json +0 -0
- docs/data/task_surface_integrity.json +1 -1
- docs/data/unified_task_model_radar.json +0 -0
- docs/data/website_integrity.json +21 -16
- docs/index.html +11 -10
- index.html +11 -10
- scripts/build_artifact_index.py +17 -1
- scripts/build_unified_task_model_radar.py +213 -39
- scripts/sync_hf_publish_mirrors.py +14 -2
- scripts/validate_mirror_parity.py +2 -0
PROJECT_README.md
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@@ -315,17 +315,22 @@ also have a compact chart and result bundle under the historical
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The unified radar compares all 20 task axes with two filled colors for the
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minimal and neural MLP baselines.
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The website also includes a responsive native modality atlas backed by
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[`docs/data/modality_atlas.json`](docs/data/modality_atlas.json) and
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data/summary_metrics.json # website-readable metrics bundle
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data/task_suite_20.json # unified 20-task suite bundle
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data/unified_task_model_radar.json # 20-task radar values and model-branch overlays
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data/evidence_contract.json # machine-readable project scope
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data/artifact_index.json # compact project-artifact catalog
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data/live_publication_status.json # live GitHub/HF publication verification
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The unified radar compares all 20 task axes with two filled colors for the
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minimal and neural MLP baselines. Every method now has 20 explicit result
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records in the public matrix; numeric points appear only where the runner or
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verified package produced that task target. The 128-episode raw-feature
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simple/NN overlays are plotted on all 20 axes backed by the exported
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4430-dimensional sensor NPZ blocks. Tasks 15 and 19 are marked as compact-proxy
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completions because the 128 export lacks raw interaction strings and paired
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video-view embeddings. Qwen3-Omni, Cosmos3-Super, Cosmos3-Nano, and the
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metadata-only baselines keep scoreless records for unsupported or not-evaluated
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targets instead of hiding those cells. Cosmos3-Super forward-dynamics LoRA
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remains a branch card because its camera-pose proxy MSE is not one of the 20
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task metrics. The machine-readable copies are
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[`docs/data/unified_task_model_radar.json`](docs/data/unified_task_model_radar.json)
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and
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[`docs/data/task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json);
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the reader-facing matrix is
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[`TASK_METHOD_20_RESULT_MATRIX.md`](TASK_METHOD_20_RESULT_MATRIX.md).
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The website also includes a responsive native modality atlas backed by
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[`docs/data/modality_atlas.json`](docs/data/modality_atlas.json) and
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data/summary_metrics.json # website-readable metrics bundle
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data/task_suite_20.json # unified 20-task suite bundle
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data/unified_task_model_radar.json # 20-task radar values and model-branch overlays
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data/task_method_20_result_matrix.json # 9-method x 20-task result matrix
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data/evidence_contract.json # machine-readable project scope
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data/artifact_index.json # compact project-artifact catalog
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data/live_publication_status.json # live GitHub/HF publication verification
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README.md
CHANGED
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The historical `tier2_task_suite` path is retained only for stable artifact
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links to tasks 13-20. The unified radar chart is published as
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`docs/assets/charts/unified_task_model_radar.svg` with values in
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`docs/data/unified_task_model_radar.json`
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## Dataset Boundary
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The historical `tier2_task_suite` path is retained only for stable artifact
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links to tasks 13-20. The unified radar chart is published as
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`docs/assets/charts/unified_task_model_radar.svg` with values in
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`docs/data/unified_task_model_radar.json`; the 9-method by 20-task
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completion matrix is in `docs/data/task_method_20_result_matrix.json`.
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## Dataset Boundary
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TASK_METHOD_20_RESULT_MATRIX.md
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# Task Method 20-Result Matrix
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Every method has one record for each of the 20 unified task contracts. Numeric scores appear only where a committed runner or verified package produced that task target.
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Legend: `score` = numeric task score, `proxy` = documented raw128 compact proxy score, `unsupported` = artifact exists but required target is not present, `not supported` = metadata-only package cannot form that target, `not evaluated` = verified model package did not request that target.
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| Method | Records | Scored | Proxy scored | Scoreless | Status counts |
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| --- | ---: | ---: | ---: | ---: | --- |
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| Minimal | 20 | 20 | 0 | 0 | scored 20 |
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| Neural MLP | 20 | 20 | 0 | 0 | scored 20 |
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| 128ep Metadata Simple | 20 | 8 | 0 | 12 | not supported 8, scored 8, unsupported 4 |
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| 128ep Metadata NN | 20 | 6 | 0 | 14 | not supported 14, scored 6 |
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| 128ep Raw Simple | 20 | 20 | 2 | 0 | proxy scored 2, scored 18 |
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| 128ep Raw NN | 20 | 20 | 2 | 0 | proxy scored 2, scored 18 |
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| Qwen3-Omni v6 LoRA | 20 | 6 | 0 | 14 | not evaluated 14, scored 6 |
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| Cosmos3-Super Reasoner | 20 | 6 | 0 | 14 | not evaluated 14, scored 6 |
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| Cosmos3-Nano Future Window | 20 | 5 | 0 | 15 | not evaluated 15, scored 5 |
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| # | Task | Min | NN | 128-S | 128-NN | 128-RS | 128-RN | Qwen3 | C3-S | C3-N |
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| ---: | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
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| 01 | Action Recognition | score | score | score | score | score | score | score | score | score |
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| 02 | Procedure Step Recognition | score | score | score | score | score | score | score | score | not evaluated |
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| 03 | Action Boundary Detection | score | score | score | score | score | score | score | score | score |
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| 04 | Next-Action Prediction | score | score | score | score | score | score | score | score | score |
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| 05 | Hand Trajectory Forecasting | score | score | unsupported | not supported | score | score | not evaluated | not evaluated | not evaluated |
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| 06 | Contact State Prediction | score | score | score | score | score | score | score | score | score |
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| 07 | Object Relevance Prediction | score | score | score | score | score | score | score | score | not evaluated |
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| 08 | Language Grounding | score | score | score | not supported | score | score | not evaluated | not evaluated | not evaluated |
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| 09 | Cross-Modal Retrieval | score | score | unsupported | not supported | score | score | not evaluated | not evaluated | score |
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| 10 | Cross-Modal Reconstruction | score | score | unsupported | not supported | score | score | not evaluated | not evaluated | not evaluated |
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| 11 | Temporal Order Verification | score | score | score | not supported | score | score | not evaluated | not evaluated | not evaluated |
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| 12 | Multimodal Synchronization Detection | score | score | unsupported | not supported | score | score | not evaluated | not evaluated | not evaluated |
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| 13 | Long-Horizon Next-Action Forecasting | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
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| 14 | Long-Horizon Next-Subtask Forecasting | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
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| 15 | Interaction Text Prediction | score | score | not supported | not supported | proxy | proxy | not evaluated | not evaluated | not evaluated |
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| 16 | Action-Object Relation Prediction | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
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| 17 | Future Object-Set Forecasting | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
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| 18 | IMU-to-Hand Pose Reconstruction | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
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| 19 | Camera-View Synchronization Retrieval | score | score | not supported | not supported | proxy | proxy | not evaluated | not evaluated | not evaluated |
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| 20 | Time-to-Next-Transition Regression | score | score | not supported | not supported | score | score | not evaluated | not evaluated | not evaluated |
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Sources and raw values are in `docs/data/task_method_20_result_matrix.json` and `docs/data/unified_task_model_radar.json`.
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data/artifact_index.json
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{
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"title": "Ropedia Xperience-10M Task Suite Artifact Index",
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"generated_at_utc": "2026-06-
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"status": "pass",
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"artifact_count":
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"missing": [],
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"by_kind": {
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"project_path": 14,
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"reproducibility": 4,
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"project_scope": 1,
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"source_alignment": 5,
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"evaluation_protocol":
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"website_data":
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"generated_figure": 5,
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"visualization_builder": 1,
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"model_result": 2,
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"shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
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"exists": true,
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"bytes": 4432,
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"sha256": "
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"id": "source_alignment_validator",
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"path": "docs/data/unified_task_model_radar.json",
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"kind": "website_data",
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"surface": "website_hf",
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"shows": "Stores normalized 20-axis radar values, raw task metrics, Qwen3/Cosmos overlay mappings,
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"exists": true,
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"bytes":
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"sha256": "
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"id": "unified_task_model_radar_chart",
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"surface": "website_hf",
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"shows": "Compares minimal and neural MLP baselines across all 20 tasks, with Qwen3/Cosmos task-aligned model overlays.",
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"exists": true,
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"bytes":
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"sha256": "
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"id": "unified_task_model_radar_builder",
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"surface": "repo_hf",
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"shows": "Regenerates the direction-aware radar chart and machine-readable metric overlay JSON.",
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"exists": true,
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"bytes":
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"sha256": "
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"id": "a100_128_metadata_task_baselines",
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"shows": "Catalogs public figures, charts, modality thumbnails, dimensions, hashes, roles, and source scripts.",
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"exists": true,
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"bytes": 5614,
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"sha256": "
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"id": "figure_index_json",
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"shows": "Machine-readable visual asset index for website and Hugging Face mirrors.",
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"exists": true,
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"bytes": 15726,
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"sha256": "
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"id": "figure_index_builder",
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"shows": "Machine-readable release-check summary for validators, mirrors, and public project surfaces.",
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"exists": true,
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"bytes": 8100,
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"sha256": "
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"id": "public_surface_qa",
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"volatile": true,
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"shows": "Records the last live GitHub/HF URL verification after upload.",
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"exists": true,
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"bytes":
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"hash_policy": "existence_and_size_only"
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{
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"surface": "repo_hf",
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"shows": "Generates the selective artifact catalog from local files.",
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"exists": true,
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"bytes":
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"sha256": "
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"id": "publication_audit",
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"volatile": true,
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"shows": "Separates setup paths from completed held-out-episode results.",
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"exists": true,
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"bytes":
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"hash_policy": "existence_and_size_only"
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"volatile": true,
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"shows": "Confirms local website links, anchors, JSON data files, and referenced images resolve.",
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"exists": true,
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"bytes":
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"hash_policy": "existence_and_size_only"
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},
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{
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{
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"title": "Ropedia Xperience-10M Task Suite Artifact Index",
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"generated_at_utc": "2026-06-16T10:35:14+00:00",
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"status": "pass",
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"artifact_count": 179,
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"missing": [],
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"by_kind": {
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"project_path": 14,
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"reproducibility": 4,
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"project_scope": 1,
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"source_alignment": 5,
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"evaluation_protocol": 7,
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"website_data": 7,
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"generated_figure": 5,
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"visualization_builder": 1,
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"model_result": 2,
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"shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
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"exists": true,
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"bytes": 4432,
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"sha256": "c9c3258a8ba9680b75dffbee1bdac194312d491664412de1b25a3e8543e0da60"
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},
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{
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"id": "source_alignment_validator",
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"path": "docs/data/unified_task_model_radar.json",
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"kind": "website_data",
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"surface": "website_hf",
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"shows": "Stores normalized 20-axis radar values, raw task metrics, Qwen3/Cosmos overlay mappings, branch-card caveats, and explicit scoreless status records.",
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"exists": true,
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"bytes": 231290,
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"sha256": "1238f6cf12f3196f483f42a9da8e405bfdef264645c2fcbb24842abcb81031e1"
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},
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{
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"id": "task_method_20_result_matrix_json",
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"title": "Task-method 20-result matrix JSON",
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"path": "docs/data/task_method_20_result_matrix.json",
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| 595 |
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"kind": "website_data",
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"surface": "website_hf",
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| 597 |
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"shows": "Machine-readable 9-method by 20-task matrix where every method has 20 records and scoreless cells carry unsupported/not-evaluated reasons.",
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"exists": true,
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"bytes": 129711,
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"sha256": "a8f7363399ddb3c57f9cf66a329d9c22e652ee0063de49e91a8adb8325a36927"
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},
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{
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"id": "task_method_20_result_matrix",
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"title": "Task-method 20-result matrix",
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"path": "TASK_METHOD_20_RESULT_MATRIX.md",
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"kind": "evaluation_protocol",
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"surface": "repo_hf",
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"shows": "Reader-facing table that separates 20 records per method from numeric scored axes, documented raw128 proxy scores, unsupported metadata targets, and model targets not evaluated in verified packages.",
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"exists": true,
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"bytes": 4224,
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"sha256": "fe14a0e1709a8bb5b9fb1fd720ffde0aecfed578329d8e1e71b352a83b23b1f8"
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},
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{
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"id": "unified_task_model_radar_chart",
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"surface": "website_hf",
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"shows": "Compares minimal and neural MLP baselines across all 20 tasks, with Qwen3/Cosmos task-aligned model overlays.",
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"exists": true,
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| 621 |
+
"bytes": 51944,
|
| 622 |
+
"sha256": "c7b460e28e6639958817b41e0f35290c32a87018714b13e4531cf5e5a44b8f72"
|
| 623 |
},
|
| 624 |
{
|
| 625 |
"id": "unified_task_model_radar_builder",
|
|
|
|
| 629 |
"surface": "repo_hf",
|
| 630 |
"shows": "Regenerates the direction-aware radar chart and machine-readable metric overlay JSON.",
|
| 631 |
"exists": true,
|
| 632 |
+
"bytes": 40863,
|
| 633 |
+
"sha256": "aa9a09bbc87955f773a1734fb58a69c4a27112d6fc933188036f771ae152cec6"
|
| 634 |
},
|
| 635 |
{
|
| 636 |
"id": "a100_128_metadata_task_baselines",
|
|
|
|
| 751 |
"shows": "Catalogs public figures, charts, modality thumbnails, dimensions, hashes, roles, and source scripts.",
|
| 752 |
"exists": true,
|
| 753 |
"bytes": 5614,
|
| 754 |
+
"sha256": "cd2a72c7a9872ca653a2fba4a28df8fbca7c16f52f6d7d84e26f6ae74f13e503"
|
| 755 |
},
|
| 756 |
{
|
| 757 |
"id": "figure_index_json",
|
|
|
|
| 762 |
"shows": "Machine-readable visual asset index for website and Hugging Face mirrors.",
|
| 763 |
"exists": true,
|
| 764 |
"bytes": 15726,
|
| 765 |
+
"sha256": "6fba864ee3ff5238622fa83e5cbc37cd80fe9e264fcc07ec2f1734e801d69ef8"
|
| 766 |
},
|
| 767 |
{
|
| 768 |
"id": "figure_index_builder",
|
|
|
|
| 839 |
"shows": "Machine-readable release-check summary for validators, mirrors, and public project surfaces.",
|
| 840 |
"exists": true,
|
| 841 |
"bytes": 8100,
|
| 842 |
+
"sha256": "389978ed6602ba98f2400af159179184c53a53bdcc831f4d2de3b7cb15d5267b"
|
| 843 |
},
|
| 844 |
{
|
| 845 |
"id": "public_surface_qa",
|
|
|
|
| 942 |
"volatile": true,
|
| 943 |
"shows": "Records the last live GitHub/HF URL verification after upload.",
|
| 944 |
"exists": true,
|
| 945 |
+
"bytes": 131884,
|
| 946 |
"hash_policy": "existence_and_size_only"
|
| 947 |
},
|
| 948 |
{
|
|
|
|
| 986 |
"surface": "repo_hf",
|
| 987 |
"shows": "Generates the selective artifact catalog from local files.",
|
| 988 |
"exists": true,
|
| 989 |
+
"bytes": 49735,
|
| 990 |
+
"sha256": "62ff86d0086204dd938a43587c4bb1030932d6d5116b2bd05566d1f0f1c618e1"
|
| 991 |
},
|
| 992 |
{
|
| 993 |
"id": "publication_audit",
|
|
|
|
| 1010 |
"volatile": true,
|
| 1011 |
"shows": "Separates setup paths from completed held-out-episode results.",
|
| 1012 |
"exists": true,
|
| 1013 |
+
"bytes": 21630,
|
| 1014 |
"hash_policy": "existence_and_size_only"
|
| 1015 |
},
|
| 1016 |
{
|
|
|
|
| 1034 |
"volatile": true,
|
| 1035 |
"shows": "Confirms local website links, anchors, JSON data files, and referenced images resolve.",
|
| 1036 |
"exists": true,
|
| 1037 |
+
"bytes": 18101,
|
| 1038 |
"hash_policy": "existence_and_size_only"
|
| 1039 |
},
|
| 1040 |
{
|
data/figure_index.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Figure Index",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-
|
| 5 |
"scope": "Public figures, diagrams, charts, and derived modality thumbnails. Raw Xperience-10M videos, annotations, RRD files, and Qwen weights are excluded.",
|
| 6 |
"figure_count": 24,
|
| 7 |
"figures": [
|
|
@@ -359,8 +359,8 @@
|
|
| 359 |
"source_script": "scripts/build_unified_task_model_radar.py",
|
| 360 |
"surface": "website unified task section, README, HF mirrors",
|
| 361 |
"exists": true,
|
| 362 |
-
"bytes":
|
| 363 |
-
"sha256": "
|
| 364 |
"dimensions": {
|
| 365 |
"format": "SVG",
|
| 366 |
"width": 1920,
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Figure Index",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T10:35:14+00:00",
|
| 5 |
"scope": "Public figures, diagrams, charts, and derived modality thumbnails. Raw Xperience-10M videos, annotations, RRD files, and Qwen weights are excluded.",
|
| 6 |
"figure_count": 24,
|
| 7 |
"figures": [
|
|
|
|
| 359 |
"source_script": "scripts/build_unified_task_model_radar.py",
|
| 360 |
"surface": "website unified task section, README, HF mirrors",
|
| 361 |
"exists": true,
|
| 362 |
+
"bytes": 51944,
|
| 363 |
+
"sha256": "c7b460e28e6639958817b41e0f35290c32a87018714b13e4531cf5e5a44b8f72",
|
| 364 |
"dimensions": {
|
| 365 |
"format": "SVG",
|
| 366 |
"width": 1920,
|
data/mirror_parity.json
CHANGED
|
@@ -1,9 +1,9 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-
|
| 4 |
"hf_root": "hf_publish",
|
| 5 |
"summary": {
|
| 6 |
-
"group_count":
|
| 7 |
"failure_count": 0,
|
| 8 |
"failures_by_surface": {}
|
| 9 |
},
|
|
@@ -138,45 +138,45 @@
|
|
| 138 |
"local": {
|
| 139 |
"path": "repo:docs/data/artifact_index.json",
|
| 140 |
"exists": true,
|
| 141 |
-
"bytes":
|
| 142 |
-
"sha256": "
|
| 143 |
},
|
| 144 |
"mirrors": {
|
| 145 |
"hf_space": {
|
| 146 |
"path": "hf_space:data/artifact_index.json",
|
| 147 |
"exists": true,
|
| 148 |
-
"bytes":
|
| 149 |
-
"sha256": "
|
| 150 |
},
|
| 151 |
"hf_artifacts_data": {
|
| 152 |
"path": "hf_artifacts:data/artifact_index.json",
|
| 153 |
"exists": true,
|
| 154 |
-
"bytes":
|
| 155 |
-
"sha256": "
|
| 156 |
},
|
| 157 |
"hf_artifacts": {
|
| 158 |
"path": "hf_artifacts:docs/data/artifact_index.json",
|
| 159 |
"exists": true,
|
| 160 |
-
"bytes":
|
| 161 |
-
"sha256": "
|
| 162 |
},
|
| 163 |
"hf_model_data": {
|
| 164 |
"path": "hf_model:data/artifact_index.json",
|
| 165 |
"exists": true,
|
| 166 |
-
"bytes":
|
| 167 |
-
"sha256": "
|
| 168 |
},
|
| 169 |
"hf_model_docs_data": {
|
| 170 |
"path": "hf_model:docs/data/artifact_index.json",
|
| 171 |
"exists": true,
|
| 172 |
-
"bytes":
|
| 173 |
-
"sha256": "
|
| 174 |
},
|
| 175 |
"hf_model": {
|
| 176 |
"path": "hf_model:metrics/artifact_index.json",
|
| 177 |
"exists": true,
|
| 178 |
-
"bytes":
|
| 179 |
-
"sha256": "
|
| 180 |
}
|
| 181 |
},
|
| 182 |
"failures": []
|
|
@@ -335,44 +335,44 @@
|
|
| 335 |
"path": "repo:docs/data/figure_index.json",
|
| 336 |
"exists": true,
|
| 337 |
"bytes": 15726,
|
| 338 |
-
"sha256": "
|
| 339 |
},
|
| 340 |
"mirrors": {
|
| 341 |
"hf_space": {
|
| 342 |
"path": "hf_space:data/figure_index.json",
|
| 343 |
"exists": true,
|
| 344 |
"bytes": 15726,
|
| 345 |
-
"sha256": "
|
| 346 |
},
|
| 347 |
"hf_artifacts_data": {
|
| 348 |
"path": "hf_artifacts:data/figure_index.json",
|
| 349 |
"exists": true,
|
| 350 |
"bytes": 15726,
|
| 351 |
-
"sha256": "
|
| 352 |
},
|
| 353 |
"hf_artifacts": {
|
| 354 |
"path": "hf_artifacts:docs/data/figure_index.json",
|
| 355 |
"exists": true,
|
| 356 |
"bytes": 15726,
|
| 357 |
-
"sha256": "
|
| 358 |
},
|
| 359 |
"hf_model_data": {
|
| 360 |
"path": "hf_model:data/figure_index.json",
|
| 361 |
"exists": true,
|
| 362 |
"bytes": 15726,
|
| 363 |
-
"sha256": "
|
| 364 |
},
|
| 365 |
"hf_model_docs_data": {
|
| 366 |
"path": "hf_model:docs/data/figure_index.json",
|
| 367 |
"exists": true,
|
| 368 |
"bytes": 15726,
|
| 369 |
-
"sha256": "
|
| 370 |
},
|
| 371 |
"hf_model": {
|
| 372 |
"path": "hf_model:metrics/figure_index.json",
|
| 373 |
"exists": true,
|
| 374 |
"bytes": 15726,
|
| 375 |
-
"sha256": "
|
| 376 |
}
|
| 377 |
},
|
| 378 |
"failures": []
|
|
@@ -432,45 +432,45 @@
|
|
| 432 |
"local": {
|
| 433 |
"path": "repo:docs/data/live_publication_status.json",
|
| 434 |
"exists": true,
|
| 435 |
-
"bytes":
|
| 436 |
-
"sha256": "
|
| 437 |
},
|
| 438 |
"mirrors": {
|
| 439 |
"hf_space": {
|
| 440 |
"path": "hf_space:data/live_publication_status.json",
|
| 441 |
"exists": true,
|
| 442 |
-
"bytes":
|
| 443 |
-
"sha256": "
|
| 444 |
},
|
| 445 |
"hf_artifacts_data": {
|
| 446 |
"path": "hf_artifacts:data/live_publication_status.json",
|
| 447 |
"exists": true,
|
| 448 |
-
"bytes":
|
| 449 |
-
"sha256": "
|
| 450 |
},
|
| 451 |
"hf_artifacts": {
|
| 452 |
"path": "hf_artifacts:docs/data/live_publication_status.json",
|
| 453 |
"exists": true,
|
| 454 |
-
"bytes":
|
| 455 |
-
"sha256": "
|
| 456 |
},
|
| 457 |
"hf_model_data": {
|
| 458 |
"path": "hf_model:data/live_publication_status.json",
|
| 459 |
"exists": true,
|
| 460 |
-
"bytes":
|
| 461 |
-
"sha256": "
|
| 462 |
},
|
| 463 |
"hf_model_docs_data": {
|
| 464 |
"path": "hf_model:docs/data/live_publication_status.json",
|
| 465 |
"exists": true,
|
| 466 |
-
"bytes":
|
| 467 |
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"sha256": "
|
| 468 |
},
|
| 469 |
"hf_model": {
|
| 470 |
"path": "hf_model:metrics/live_publication_status.json",
|
| 471 |
"exists": true,
|
| 472 |
-
"bytes":
|
| 473 |
-
"sha256": "
|
| 474 |
}
|
| 475 |
},
|
| 476 |
"failures": []
|
|
@@ -825,44 +825,44 @@
|
|
| 825 |
"path": "repo:docs/data/publication_audit.json",
|
| 826 |
"exists": true,
|
| 827 |
"bytes": 7883,
|
| 828 |
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"sha256": "
|
| 829 |
},
|
| 830 |
"mirrors": {
|
| 831 |
"hf_space": {
|
| 832 |
"path": "hf_space:data/publication_audit.json",
|
| 833 |
"exists": true,
|
| 834 |
"bytes": 7883,
|
| 835 |
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"sha256": "
|
| 836 |
},
|
| 837 |
"hf_artifacts_data": {
|
| 838 |
"path": "hf_artifacts:data/publication_audit.json",
|
| 839 |
"exists": true,
|
| 840 |
"bytes": 7883,
|
| 841 |
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"sha256": "
|
| 842 |
},
|
| 843 |
"hf_artifacts": {
|
| 844 |
"path": "hf_artifacts:docs/data/publication_audit.json",
|
| 845 |
"exists": true,
|
| 846 |
"bytes": 7883,
|
| 847 |
-
"sha256": "
|
| 848 |
},
|
| 849 |
"hf_model_data": {
|
| 850 |
"path": "hf_model:data/publication_audit.json",
|
| 851 |
"exists": true,
|
| 852 |
"bytes": 7883,
|
| 853 |
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"sha256": "
|
| 854 |
},
|
| 855 |
"hf_model_docs_data": {
|
| 856 |
"path": "hf_model:docs/data/publication_audit.json",
|
| 857 |
"exists": true,
|
| 858 |
"bytes": 7883,
|
| 859 |
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"sha256": "
|
| 860 |
},
|
| 861 |
"hf_model": {
|
| 862 |
"path": "hf_model:metrics/publication_audit.json",
|
| 863 |
"exists": true,
|
| 864 |
"bytes": 7883,
|
| 865 |
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"sha256": "
|
| 866 |
}
|
| 867 |
},
|
| 868 |
"failures": []
|
|
@@ -874,44 +874,44 @@
|
|
| 874 |
"path": "repo:docs/data/public_surface_qa.json",
|
| 875 |
"exists": true,
|
| 876 |
"bytes": 5806,
|
| 877 |
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"sha256": "
|
| 878 |
},
|
| 879 |
"mirrors": {
|
| 880 |
"hf_space": {
|
| 881 |
"path": "hf_space:data/public_surface_qa.json",
|
| 882 |
"exists": true,
|
| 883 |
"bytes": 5806,
|
| 884 |
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"sha256": "
|
| 885 |
},
|
| 886 |
"hf_artifacts_data": {
|
| 887 |
"path": "hf_artifacts:data/public_surface_qa.json",
|
| 888 |
"exists": true,
|
| 889 |
"bytes": 5806,
|
| 890 |
-
"sha256": "
|
| 891 |
},
|
| 892 |
"hf_artifacts": {
|
| 893 |
"path": "hf_artifacts:docs/data/public_surface_qa.json",
|
| 894 |
"exists": true,
|
| 895 |
"bytes": 5806,
|
| 896 |
-
"sha256": "
|
| 897 |
},
|
| 898 |
"hf_model_data": {
|
| 899 |
"path": "hf_model:data/public_surface_qa.json",
|
| 900 |
"exists": true,
|
| 901 |
"bytes": 5806,
|
| 902 |
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"sha256": "
|
| 903 |
},
|
| 904 |
"hf_model_docs_data": {
|
| 905 |
"path": "hf_model:docs/data/public_surface_qa.json",
|
| 906 |
"exists": true,
|
| 907 |
"bytes": 5806,
|
| 908 |
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"sha256": "
|
| 909 |
},
|
| 910 |
"hf_model": {
|
| 911 |
"path": "hf_model:metrics/public_surface_qa.json",
|
| 912 |
"exists": true,
|
| 913 |
"bytes": 5806,
|
| 914 |
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"sha256": "
|
| 915 |
}
|
| 916 |
},
|
| 917 |
"failures": []
|
|
@@ -1021,44 +1021,44 @@
|
|
| 1021 |
"path": "repo:docs/data/quality_gates.json",
|
| 1022 |
"exists": true,
|
| 1023 |
"bytes": 8100,
|
| 1024 |
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"sha256": "
|
| 1025 |
},
|
| 1026 |
"mirrors": {
|
| 1027 |
"hf_space": {
|
| 1028 |
"path": "hf_space:data/quality_gates.json",
|
| 1029 |
"exists": true,
|
| 1030 |
"bytes": 8100,
|
| 1031 |
-
"sha256": "
|
| 1032 |
},
|
| 1033 |
"hf_artifacts_data": {
|
| 1034 |
"path": "hf_artifacts:data/quality_gates.json",
|
| 1035 |
"exists": true,
|
| 1036 |
"bytes": 8100,
|
| 1037 |
-
"sha256": "
|
| 1038 |
},
|
| 1039 |
"hf_artifacts": {
|
| 1040 |
"path": "hf_artifacts:docs/data/quality_gates.json",
|
| 1041 |
"exists": true,
|
| 1042 |
"bytes": 8100,
|
| 1043 |
-
"sha256": "
|
| 1044 |
},
|
| 1045 |
"hf_model_data": {
|
| 1046 |
"path": "hf_model:data/quality_gates.json",
|
| 1047 |
"exists": true,
|
| 1048 |
"bytes": 8100,
|
| 1049 |
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"sha256": "
|
| 1050 |
},
|
| 1051 |
"hf_model_docs_data": {
|
| 1052 |
"path": "hf_model:docs/data/quality_gates.json",
|
| 1053 |
"exists": true,
|
| 1054 |
"bytes": 8100,
|
| 1055 |
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"sha256": "
|
| 1056 |
},
|
| 1057 |
"hf_model": {
|
| 1058 |
"path": "hf_model:metrics/quality_gates.json",
|
| 1059 |
"exists": true,
|
| 1060 |
"bytes": 8100,
|
| 1061 |
-
"sha256": "
|
| 1062 |
}
|
| 1063 |
},
|
| 1064 |
"failures": []
|
|
@@ -1461,45 +1461,45 @@
|
|
| 1461 |
"local": {
|
| 1462 |
"path": "repo:docs/data/scope_claims_audit.json",
|
| 1463 |
"exists": true,
|
| 1464 |
-
"bytes":
|
| 1465 |
-
"sha256": "
|
| 1466 |
},
|
| 1467 |
"mirrors": {
|
| 1468 |
"hf_space": {
|
| 1469 |
"path": "hf_space:data/scope_claims_audit.json",
|
| 1470 |
"exists": true,
|
| 1471 |
-
"bytes":
|
| 1472 |
-
"sha256": "
|
| 1473 |
},
|
| 1474 |
"hf_artifacts_data": {
|
| 1475 |
"path": "hf_artifacts:data/scope_claims_audit.json",
|
| 1476 |
"exists": true,
|
| 1477 |
-
"bytes":
|
| 1478 |
-
"sha256": "
|
| 1479 |
},
|
| 1480 |
"hf_artifacts": {
|
| 1481 |
"path": "hf_artifacts:docs/data/scope_claims_audit.json",
|
| 1482 |
"exists": true,
|
| 1483 |
-
"bytes":
|
| 1484 |
-
"sha256": "
|
| 1485 |
},
|
| 1486 |
"hf_model_data": {
|
| 1487 |
"path": "hf_model:data/scope_claims_audit.json",
|
| 1488 |
"exists": true,
|
| 1489 |
-
"bytes":
|
| 1490 |
-
"sha256": "
|
| 1491 |
},
|
| 1492 |
"hf_model_docs_data": {
|
| 1493 |
"path": "hf_model:docs/data/scope_claims_audit.json",
|
| 1494 |
"exists": true,
|
| 1495 |
-
"bytes":
|
| 1496 |
-
"sha256": "
|
| 1497 |
},
|
| 1498 |
"hf_model": {
|
| 1499 |
"path": "hf_model:metrics/scope_claims_audit.json",
|
| 1500 |
"exists": true,
|
| 1501 |
-
"bytes":
|
| 1502 |
-
"sha256": "
|
| 1503 |
}
|
| 1504 |
},
|
| 1505 |
"failures": []
|
|
@@ -1560,44 +1560,44 @@
|
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"path": "hf_model:docs/index.html",
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|
| 18169 |
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| 18171 |
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{
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| 18173 |
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|
| 18174 |
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"status": "pass",
|
| 18175 |
+
"local": {
|
| 18176 |
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"path": "repo:TASK_METHOD_20_RESULT_MATRIX.md",
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|
| 18180 |
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"hf_space": {
|
| 18183 |
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"path": "hf_space:TASK_METHOD_20_RESULT_MATRIX.md",
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},
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+
"hf_artifacts": {
|
| 18189 |
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"path": "hf_artifacts:TASK_METHOD_20_RESULT_MATRIX.md",
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| 18190 |
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"exists": true,
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"bytes": 4224,
|
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|
| 18193 |
+
},
|
| 18194 |
+
"hf_model": {
|
| 18195 |
+
"path": "hf_model:TASK_METHOD_20_RESULT_MATRIX.md",
|
| 18196 |
+
"exists": true,
|
| 18197 |
+
"bytes": 4224,
|
| 18198 |
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"sha256": "fe14a0e1709a8bb5b9fb1fd720ffde0aecfed578329d8e1e71b352a83b23b1f8"
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| 18199 |
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| 18201 |
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|
| 18202 |
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|
| 18203 |
{
|
| 18204 |
"name": "docs/TASK_SUITE_20.md",
|
| 18205 |
"status": "pass",
|
data/public_surface_qa.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Public Project Surface",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-
|
| 5 |
"scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
|
| 6 |
"checks": [
|
| 7 |
{
|
|
@@ -18,7 +18,7 @@
|
|
| 18 |
"website_integrity": {
|
| 19 |
"exists": true,
|
| 20 |
"status": "pass",
|
| 21 |
-
"generated_at_utc": "2026-06-
|
| 22 |
},
|
| 23 |
"rendered_site_check": {
|
| 24 |
"exists": true,
|
|
@@ -28,27 +28,27 @@
|
|
| 28 |
"task_surface_integrity": {
|
| 29 |
"exists": true,
|
| 30 |
"status": "pass",
|
| 31 |
-
"generated_at_utc": "2026-06-
|
| 32 |
},
|
| 33 |
"source_alignment": {
|
| 34 |
"exists": true,
|
| 35 |
"status": "pass",
|
| 36 |
-
"generated_at_utc": "2026-06-
|
| 37 |
},
|
| 38 |
"scale_up_status": {
|
| 39 |
"exists": true,
|
| 40 |
"status": "pass",
|
| 41 |
-
"generated_at_utc": "2026-06-
|
| 42 |
},
|
| 43 |
"publication_package": {
|
| 44 |
"exists": true,
|
| 45 |
"status": "pass",
|
| 46 |
-
"generated_at_utc": "2026-06-
|
| 47 |
},
|
| 48 |
"mirror_parity": {
|
| 49 |
"exists": true,
|
| 50 |
"status": "pass",
|
| 51 |
-
"generated_at_utc": "2026-06-
|
| 52 |
}
|
| 53 |
},
|
| 54 |
"failures": {}
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|
@@ -97,7 +97,7 @@
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|
| 97 |
"marker_counts": {
|
| 98 |
"Ropedia Xperience-10M Task Suite": 16,
|
| 99 |
"Xperience-10M": 149,
|
| 100 |
-
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|
| 101 |
"Qwen3-Omni": 148,
|
| 102 |
"128-episode pilot": 1
|
| 103 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Public Project Surface",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T10:35:37+00:00",
|
| 5 |
"scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
|
| 6 |
"checks": [
|
| 7 |
{
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|
|
|
| 18 |
"website_integrity": {
|
| 19 |
"exists": true,
|
| 20 |
"status": "pass",
|
| 21 |
+
"generated_at_utc": "2026-06-16T09:46:21+00:00"
|
| 22 |
},
|
| 23 |
"rendered_site_check": {
|
| 24 |
"exists": true,
|
|
|
|
| 28 |
"task_surface_integrity": {
|
| 29 |
"exists": true,
|
| 30 |
"status": "pass",
|
| 31 |
+
"generated_at_utc": "2026-06-16T09:46:19+00:00"
|
| 32 |
},
|
| 33 |
"source_alignment": {
|
| 34 |
"exists": true,
|
| 35 |
"status": "pass",
|
| 36 |
+
"generated_at_utc": "2026-06-16T10:35:37+00:00"
|
| 37 |
},
|
| 38 |
"scale_up_status": {
|
| 39 |
"exists": true,
|
| 40 |
"status": "pass",
|
| 41 |
+
"generated_at_utc": "2026-06-16T09:46:26+00:00"
|
| 42 |
},
|
| 43 |
"publication_package": {
|
| 44 |
"exists": true,
|
| 45 |
"status": "pass",
|
| 46 |
+
"generated_at_utc": "2026-06-16T09:46:35+00:00"
|
| 47 |
},
|
| 48 |
"mirror_parity": {
|
| 49 |
"exists": true,
|
| 50 |
"status": "pass",
|
| 51 |
+
"generated_at_utc": "2026-06-16T09:48:16+00:00"
|
| 52 |
}
|
| 53 |
},
|
| 54 |
"failures": {}
|
|
|
|
| 97 |
"marker_counts": {
|
| 98 |
"Ropedia Xperience-10M Task Suite": 16,
|
| 99 |
"Xperience-10M": 149,
|
| 100 |
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"20-task": 43,
|
| 101 |
"Qwen3-Omni": 148,
|
| 102 |
"128-episode pilot": 1
|
| 103 |
}
|
data/publication_audit.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-
|
| 4 |
"checks": [
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| 5 |
{
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| 6 |
"name": "required_publication_assets_present",
|
|
@@ -193,8 +193,8 @@
|
|
| 193 |
"github_repo": {
|
| 194 |
"root": "repo",
|
| 195 |
"exists": true,
|
| 196 |
-
"file_count":
|
| 197 |
-
"text_file_count":
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| 198 |
"largest_file": {
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| 199 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
| 200 |
"bytes": 55702978
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|
@@ -204,8 +204,8 @@
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|
| 204 |
"hf_space_bundle": {
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| 205 |
"root": "hf_publish/space",
|
| 206 |
"exists": true,
|
| 207 |
-
"file_count":
|
| 208 |
-
"text_file_count":
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| 209 |
"largest_file": {
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| 210 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
| 211 |
"bytes": 55702978
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|
@@ -215,8 +215,8 @@
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|
| 215 |
"hf_artifact_bundle": {
|
| 216 |
"root": "hf_publish/artifacts",
|
| 217 |
"exists": true,
|
| 218 |
-
"file_count":
|
| 219 |
-
"text_file_count":
|
| 220 |
"largest_file": {
|
| 221 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
| 222 |
"bytes": 55702978
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|
@@ -226,8 +226,8 @@
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|
| 226 |
"hf_model_bundle": {
|
| 227 |
"root": "hf_publish/model",
|
| 228 |
"exists": true,
|
| 229 |
-
"file_count":
|
| 230 |
-
"text_file_count":
|
| 231 |
"largest_file": {
|
| 232 |
"path": "pytorch_model.bin",
|
| 233 |
"bytes": 93495480
|
|
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
+
"generated_at_utc": "2026-06-16T10:35:47+00:00",
|
| 4 |
"checks": [
|
| 5 |
{
|
| 6 |
"name": "required_publication_assets_present",
|
|
|
|
| 193 |
"github_repo": {
|
| 194 |
"root": "repo",
|
| 195 |
"exists": true,
|
| 196 |
+
"file_count": 1185,
|
| 197 |
+
"text_file_count": 990,
|
| 198 |
"largest_file": {
|
| 199 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
| 200 |
"bytes": 55702978
|
|
|
|
| 204 |
"hf_space_bundle": {
|
| 205 |
"root": "hf_publish/space",
|
| 206 |
"exists": true,
|
| 207 |
+
"file_count": 968,
|
| 208 |
+
"text_file_count": 812,
|
| 209 |
"largest_file": {
|
| 210 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
| 211 |
"bytes": 55702978
|
|
|
|
| 215 |
"hf_artifact_bundle": {
|
| 216 |
"root": "hf_publish/artifacts",
|
| 217 |
"exists": true,
|
| 218 |
+
"file_count": 2155,
|
| 219 |
+
"text_file_count": 992,
|
| 220 |
"largest_file": {
|
| 221 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
| 222 |
"bytes": 55702978
|
|
|
|
| 226 |
"hf_model_bundle": {
|
| 227 |
"root": "hf_publish/model",
|
| 228 |
"exists": true,
|
| 229 |
+
"file_count": 2585,
|
| 230 |
+
"text_file_count": 1151,
|
| 231 |
"largest_file": {
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| 232 |
"path": "pytorch_model.bin",
|
| 233 |
"bytes": 93495480
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data/quality_gates.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Release Checks",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-
|
| 5 |
"rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
|
| 6 |
"automated_gates": [
|
| 7 |
{
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Release Checks",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T10:35:14+00:00",
|
| 5 |
"rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
|
| 6 |
"automated_gates": [
|
| 7 |
{
|
data/scope_claims_audit.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-
|
| 4 |
"summary": {
|
| 5 |
"qwen3_omni_verified_diagnostic_pilot": true,
|
| 6 |
"dataset_manifest_num_episodes": 119,
|
|
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
+
"generated_at_utc": "2026-06-16T10:35:40+00:00",
|
| 4 |
"summary": {
|
| 5 |
"qwen3_omni_verified_diagnostic_pilot": true,
|
| 6 |
"dataset_manifest_num_episodes": 119,
|
data/source_alignment_audit.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Source Alignment Note",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-
|
| 5 |
"alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
|
| 6 |
"alignment_summary": {
|
| 7 |
"full_dataset_repo": "ropedia-ai/xperience-10m",
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Source Alignment Note",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T10:35:37+00:00",
|
| 5 |
"alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
|
| 6 |
"alignment_summary": {
|
| 7 |
"full_dataset_repo": "ropedia-ai/xperience-10m",
|
data/task_method_20_result_matrix.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
data/task_surface_integrity.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-
|
| 4 |
"summary": {
|
| 5 |
"task_count": 12,
|
| 6 |
"expected_task_count": 12,
|
|
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
+
"generated_at_utc": "2026-06-16T10:35:37+00:00",
|
| 4 |
"summary": {
|
| 5 |
"task_count": 12,
|
| 6 |
"expected_task_count": 12,
|
data/unified_task_model_radar.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
data/website_integrity.json
CHANGED
|
@@ -1,13 +1,13 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-
|
| 4 |
"docs_root": "docs",
|
| 5 |
"site_base": "/ropedia-xperience-10m-task-suite/",
|
| 6 |
"summary": {
|
| 7 |
"html_pages": 4,
|
| 8 |
-
"local_references":
|
| 9 |
"external_reference_count": 121,
|
| 10 |
-
"json_files":
|
| 11 |
"image_assets_referenced": 23,
|
| 12 |
"failure_count": 0
|
| 13 |
},
|
|
@@ -80,8 +80,8 @@
|
|
| 80 |
"name": "project_overview_precedes_progress_ledger",
|
| 81 |
"status": "pass",
|
| 82 |
"reason": "The project overview should appear before the deeper progress ledger.",
|
| 83 |
-
"overview_index":
|
| 84 |
-
"evidence_index":
|
| 85 |
},
|
| 86 |
{
|
| 87 |
"name": "project_status_links_json",
|
|
@@ -159,9 +159,9 @@
|
|
| 159 |
"name": "evaluation_protocol_between_overview_and_progress",
|
| 160 |
"status": "pass",
|
| 161 |
"reason": "The evaluation protocol should appear before the deeper evidence ledger.",
|
| 162 |
-
"overview_index":
|
| 163 |
-
"protocol_index":
|
| 164 |
-
"evidence_index":
|
| 165 |
},
|
| 166 |
{
|
| 167 |
"name": "evaluation_protocol_links_json",
|
|
@@ -180,7 +180,7 @@
|
|
| 180 |
"status": "pass",
|
| 181 |
"reason": "The Suite anchor should show the task-suite map before the modality atlas.",
|
| 182 |
"first_marker_index": 471,
|
| 183 |
-
"second_marker_index":
|
| 184 |
},
|
| 185 |
{
|
| 186 |
"name": "suite_modality_atlas_contains_seven_cards",
|
|
@@ -277,7 +277,7 @@
|
|
| 277 |
{
|
| 278 |
"path": "index.html",
|
| 279 |
"id_count": 90,
|
| 280 |
-
"reference_count":
|
| 281 |
"image_count": 27
|
| 282 |
},
|
| 283 |
{
|
|
@@ -301,7 +301,7 @@
|
|
| 301 |
},
|
| 302 |
{
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| 303 |
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|
| 359 |
"source_script": "scripts/build_unified_task_model_radar.py",
|
| 360 |
"surface": "website unified task section, README, HF mirrors",
|
| 361 |
"exists": true,
|
| 362 |
-
"bytes":
|
| 363 |
-
"sha256": "
|
| 364 |
"dimensions": {
|
| 365 |
"format": "SVG",
|
| 366 |
"width": 1920,
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Figure Index",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T10:35:14+00:00",
|
| 5 |
"scope": "Public figures, diagrams, charts, and derived modality thumbnails. Raw Xperience-10M videos, annotations, RRD files, and Qwen weights are excluded.",
|
| 6 |
"figure_count": 24,
|
| 7 |
"figures": [
|
|
|
|
| 359 |
"source_script": "scripts/build_unified_task_model_radar.py",
|
| 360 |
"surface": "website unified task section, README, HF mirrors",
|
| 361 |
"exists": true,
|
| 362 |
+
"bytes": 51944,
|
| 363 |
+
"sha256": "c7b460e28e6639958817b41e0f35290c32a87018714b13e4531cf5e5a44b8f72",
|
| 364 |
"dimensions": {
|
| 365 |
"format": "SVG",
|
| 366 |
"width": 1920,
|
docs/data/mirror_parity.json
CHANGED
|
@@ -1,9 +1,9 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-
|
| 4 |
"hf_root": "hf_publish",
|
| 5 |
"summary": {
|
| 6 |
-
"group_count":
|
| 7 |
"failure_count": 0,
|
| 8 |
"failures_by_surface": {}
|
| 9 |
},
|
|
@@ -138,45 +138,45 @@
|
|
| 138 |
"local": {
|
| 139 |
"path": "repo:docs/data/artifact_index.json",
|
| 140 |
"exists": true,
|
| 141 |
-
"bytes":
|
| 142 |
-
"sha256": "
|
| 143 |
},
|
| 144 |
"mirrors": {
|
| 145 |
"hf_space": {
|
| 146 |
"path": "hf_space:data/artifact_index.json",
|
| 147 |
"exists": true,
|
| 148 |
-
"bytes":
|
| 149 |
-
"sha256": "
|
| 150 |
},
|
| 151 |
"hf_artifacts_data": {
|
| 152 |
"path": "hf_artifacts:data/artifact_index.json",
|
| 153 |
"exists": true,
|
| 154 |
-
"bytes":
|
| 155 |
-
"sha256": "
|
| 156 |
},
|
| 157 |
"hf_artifacts": {
|
| 158 |
"path": "hf_artifacts:docs/data/artifact_index.json",
|
| 159 |
"exists": true,
|
| 160 |
-
"bytes":
|
| 161 |
-
"sha256": "
|
| 162 |
},
|
| 163 |
"hf_model_data": {
|
| 164 |
"path": "hf_model:data/artifact_index.json",
|
| 165 |
"exists": true,
|
| 166 |
-
"bytes":
|
| 167 |
-
"sha256": "
|
| 168 |
},
|
| 169 |
"hf_model_docs_data": {
|
| 170 |
"path": "hf_model:docs/data/artifact_index.json",
|
| 171 |
"exists": true,
|
| 172 |
-
"bytes":
|
| 173 |
-
"sha256": "
|
| 174 |
},
|
| 175 |
"hf_model": {
|
| 176 |
"path": "hf_model:metrics/artifact_index.json",
|
| 177 |
"exists": true,
|
| 178 |
-
"bytes":
|
| 179 |
-
"sha256": "
|
| 180 |
}
|
| 181 |
},
|
| 182 |
"failures": []
|
|
@@ -335,44 +335,44 @@
|
|
| 335 |
"path": "repo:docs/data/figure_index.json",
|
| 336 |
"exists": true,
|
| 337 |
"bytes": 15726,
|
| 338 |
-
"sha256": "
|
| 339 |
},
|
| 340 |
"mirrors": {
|
| 341 |
"hf_space": {
|
| 342 |
"path": "hf_space:data/figure_index.json",
|
| 343 |
"exists": true,
|
| 344 |
"bytes": 15726,
|
| 345 |
-
"sha256": "
|
| 346 |
},
|
| 347 |
"hf_artifacts_data": {
|
| 348 |
"path": "hf_artifacts:data/figure_index.json",
|
| 349 |
"exists": true,
|
| 350 |
"bytes": 15726,
|
| 351 |
-
"sha256": "
|
| 352 |
},
|
| 353 |
"hf_artifacts": {
|
| 354 |
"path": "hf_artifacts:docs/data/figure_index.json",
|
| 355 |
"exists": true,
|
| 356 |
"bytes": 15726,
|
| 357 |
-
"sha256": "
|
| 358 |
},
|
| 359 |
"hf_model_data": {
|
| 360 |
"path": "hf_model:data/figure_index.json",
|
| 361 |
"exists": true,
|
| 362 |
"bytes": 15726,
|
| 363 |
-
"sha256": "
|
| 364 |
},
|
| 365 |
"hf_model_docs_data": {
|
| 366 |
"path": "hf_model:docs/data/figure_index.json",
|
| 367 |
"exists": true,
|
| 368 |
"bytes": 15726,
|
| 369 |
-
"sha256": "
|
| 370 |
},
|
| 371 |
"hf_model": {
|
| 372 |
"path": "hf_model:metrics/figure_index.json",
|
| 373 |
"exists": true,
|
| 374 |
"bytes": 15726,
|
| 375 |
-
"sha256": "
|
| 376 |
}
|
| 377 |
},
|
| 378 |
"failures": []
|
|
@@ -432,45 +432,45 @@
|
|
| 432 |
"local": {
|
| 433 |
"path": "repo:docs/data/live_publication_status.json",
|
| 434 |
"exists": true,
|
| 435 |
-
"bytes":
|
| 436 |
-
"sha256": "
|
| 437 |
},
|
| 438 |
"mirrors": {
|
| 439 |
"hf_space": {
|
| 440 |
"path": "hf_space:data/live_publication_status.json",
|
| 441 |
"exists": true,
|
| 442 |
-
"bytes":
|
| 443 |
-
"sha256": "
|
| 444 |
},
|
| 445 |
"hf_artifacts_data": {
|
| 446 |
"path": "hf_artifacts:data/live_publication_status.json",
|
| 447 |
"exists": true,
|
| 448 |
-
"bytes":
|
| 449 |
-
"sha256": "
|
| 450 |
},
|
| 451 |
"hf_artifacts": {
|
| 452 |
"path": "hf_artifacts:docs/data/live_publication_status.json",
|
| 453 |
"exists": true,
|
| 454 |
-
"bytes":
|
| 455 |
-
"sha256": "
|
| 456 |
},
|
| 457 |
"hf_model_data": {
|
| 458 |
"path": "hf_model:data/live_publication_status.json",
|
| 459 |
"exists": true,
|
| 460 |
-
"bytes":
|
| 461 |
-
"sha256": "
|
| 462 |
},
|
| 463 |
"hf_model_docs_data": {
|
| 464 |
"path": "hf_model:docs/data/live_publication_status.json",
|
| 465 |
"exists": true,
|
| 466 |
-
"bytes":
|
| 467 |
-
"sha256": "
|
| 468 |
},
|
| 469 |
"hf_model": {
|
| 470 |
"path": "hf_model:metrics/live_publication_status.json",
|
| 471 |
"exists": true,
|
| 472 |
-
"bytes":
|
| 473 |
-
"sha256": "
|
| 474 |
}
|
| 475 |
},
|
| 476 |
"failures": []
|
|
@@ -825,44 +825,44 @@
|
|
| 825 |
"path": "repo:docs/data/publication_audit.json",
|
| 826 |
"exists": true,
|
| 827 |
"bytes": 7883,
|
| 828 |
-
"sha256": "
|
| 829 |
},
|
| 830 |
"mirrors": {
|
| 831 |
"hf_space": {
|
| 832 |
"path": "hf_space:data/publication_audit.json",
|
| 833 |
"exists": true,
|
| 834 |
"bytes": 7883,
|
| 835 |
-
"sha256": "
|
| 836 |
},
|
| 837 |
"hf_artifacts_data": {
|
| 838 |
"path": "hf_artifacts:data/publication_audit.json",
|
| 839 |
"exists": true,
|
| 840 |
"bytes": 7883,
|
| 841 |
-
"sha256": "
|
| 842 |
},
|
| 843 |
"hf_artifacts": {
|
| 844 |
"path": "hf_artifacts:docs/data/publication_audit.json",
|
| 845 |
"exists": true,
|
| 846 |
"bytes": 7883,
|
| 847 |
-
"sha256": "
|
| 848 |
},
|
| 849 |
"hf_model_data": {
|
| 850 |
"path": "hf_model:data/publication_audit.json",
|
| 851 |
"exists": true,
|
| 852 |
"bytes": 7883,
|
| 853 |
-
"sha256": "
|
| 854 |
},
|
| 855 |
"hf_model_docs_data": {
|
| 856 |
"path": "hf_model:docs/data/publication_audit.json",
|
| 857 |
"exists": true,
|
| 858 |
"bytes": 7883,
|
| 859 |
-
"sha256": "
|
| 860 |
},
|
| 861 |
"hf_model": {
|
| 862 |
"path": "hf_model:metrics/publication_audit.json",
|
| 863 |
"exists": true,
|
| 864 |
"bytes": 7883,
|
| 865 |
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"sha256": "
|
| 866 |
}
|
| 867 |
},
|
| 868 |
"failures": []
|
|
@@ -874,44 +874,44 @@
|
|
| 874 |
"path": "repo:docs/data/public_surface_qa.json",
|
| 875 |
"exists": true,
|
| 876 |
"bytes": 5806,
|
| 877 |
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"sha256": "
|
| 878 |
},
|
| 879 |
"mirrors": {
|
| 880 |
"hf_space": {
|
| 881 |
"path": "hf_space:data/public_surface_qa.json",
|
| 882 |
"exists": true,
|
| 883 |
"bytes": 5806,
|
| 884 |
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"sha256": "
|
| 885 |
},
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| 886 |
"hf_artifacts_data": {
|
| 887 |
"path": "hf_artifacts:data/public_surface_qa.json",
|
| 888 |
"exists": true,
|
| 889 |
"bytes": 5806,
|
| 890 |
-
"sha256": "
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| 891 |
},
|
| 892 |
"hf_artifacts": {
|
| 893 |
"path": "hf_artifacts:docs/data/public_surface_qa.json",
|
| 894 |
"exists": true,
|
| 895 |
"bytes": 5806,
|
| 896 |
-
"sha256": "
|
| 897 |
},
|
| 898 |
"hf_model_data": {
|
| 899 |
"path": "hf_model:data/public_surface_qa.json",
|
| 900 |
"exists": true,
|
| 901 |
"bytes": 5806,
|
| 902 |
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"sha256": "
|
| 903 |
},
|
| 904 |
"hf_model_docs_data": {
|
| 905 |
"path": "hf_model:docs/data/public_surface_qa.json",
|
| 906 |
"exists": true,
|
| 907 |
"bytes": 5806,
|
| 908 |
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"sha256": "
|
| 909 |
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|
| 910 |
"hf_model": {
|
| 911 |
"path": "hf_model:metrics/public_surface_qa.json",
|
| 912 |
"exists": true,
|
| 913 |
"bytes": 5806,
|
| 914 |
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| 915 |
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|
| 916 |
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| 917 |
"failures": []
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|
@@ -1021,44 +1021,44 @@
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|
| 1021 |
"path": "repo:docs/data/quality_gates.json",
|
| 1022 |
"exists": true,
|
| 1023 |
"bytes": 8100,
|
| 1024 |
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|
| 1025 |
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| 1026 |
"mirrors": {
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| 1027 |
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|
| 1028 |
"path": "hf_space:data/quality_gates.json",
|
| 1029 |
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| 1030 |
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|
| 1031 |
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| 1032 |
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| 1033 |
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| 1034 |
"path": "hf_artifacts:data/quality_gates.json",
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| 1035 |
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|
| 1037 |
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| 1038 |
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| 1039 |
"hf_artifacts": {
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| 1040 |
"path": "hf_artifacts:docs/data/quality_gates.json",
|
| 1041 |
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|
| 1042 |
"bytes": 8100,
|
| 1043 |
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|
| 1044 |
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|
| 1045 |
"hf_model_data": {
|
| 1046 |
"path": "hf_model:data/quality_gates.json",
|
| 1047 |
"exists": true,
|
| 1048 |
"bytes": 8100,
|
| 1049 |
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"sha256": "
|
| 1050 |
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|
| 1051 |
"hf_model_docs_data": {
|
| 1052 |
"path": "hf_model:docs/data/quality_gates.json",
|
| 1053 |
"exists": true,
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| 1054 |
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|
| 1055 |
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| 1056 |
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| 1057 |
"hf_model": {
|
| 1058 |
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| 1059 |
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|
| 1060 |
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|
| 1061 |
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|
| 1062 |
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| 1063 |
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| 1064 |
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|
@@ -1461,45 +1461,45 @@
|
|
| 1461 |
"local": {
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| 1462 |
"path": "repo:docs/data/scope_claims_audit.json",
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| 1463 |
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| 1464 |
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| 1466 |
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| 1467 |
"mirrors": {
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| 1468 |
"hf_space": {
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| 1469 |
"path": "hf_space:data/scope_claims_audit.json",
|
| 1470 |
"exists": true,
|
| 1471 |
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"bytes":
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| 1472 |
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| 1473 |
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| 1474 |
"hf_artifacts_data": {
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| 1475 |
"path": "hf_artifacts:data/scope_claims_audit.json",
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| 1476 |
"exists": true,
|
| 1477 |
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"bytes":
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| 1478 |
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"sha256": "
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| 1479 |
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| 1480 |
"hf_artifacts": {
|
| 1481 |
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|
| 1482 |
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|
| 1483 |
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| 1484 |
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"sha256": "
|
| 1485 |
},
|
| 1486 |
"hf_model_data": {
|
| 1487 |
"path": "hf_model:data/scope_claims_audit.json",
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| 1488 |
"exists": true,
|
| 1489 |
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| 1490 |
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"sha256": "
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| 1491 |
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| 1492 |
"hf_model_docs_data": {
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| 1493 |
"path": "hf_model:docs/data/scope_claims_audit.json",
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| 1494 |
"exists": true,
|
| 1495 |
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| 1496 |
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|
| 1497 |
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|
| 1498 |
"hf_model": {
|
| 1499 |
"path": "hf_model:metrics/scope_claims_audit.json",
|
| 1500 |
"exists": true,
|
| 1501 |
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| 1502 |
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"sha256": "
|
| 1503 |
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|
| 1504 |
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| 1505 |
"failures": []
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|
@@ -1560,44 +1560,44 @@
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|
| 1560 |
"path": "repo:docs/data/source_alignment_audit.json",
|
| 1561 |
"exists": true,
|
| 1562 |
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| 1564 |
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| 1565 |
"mirrors": {
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| 1566 |
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| 1567 |
"path": "hf_space:data/source_alignment_audit.json",
|
| 1568 |
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| 1569 |
"bytes": 4432,
|
| 1570 |
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| 1571 |
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| 1572 |
"hf_artifacts_data": {
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| 1573 |
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|
| 1574 |
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|
| 1575 |
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|
| 1576 |
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|
| 1577 |
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| 1578 |
"hf_artifacts": {
|
| 1579 |
"path": "hf_artifacts:docs/data/source_alignment_audit.json",
|
| 1580 |
"exists": true,
|
| 1581 |
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|
| 1582 |
-
"sha256": "
|
| 1583 |
},
|
| 1584 |
"hf_model_data": {
|
| 1585 |
"path": "hf_model:data/source_alignment_audit.json",
|
| 1586 |
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|
| 1587 |
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|
| 1588 |
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|
| 1589 |
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|
| 1590 |
"hf_model_docs_data": {
|
| 1591 |
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|
| 1592 |
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|
| 1593 |
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|
| 1594 |
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|
| 1595 |
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| 1596 |
"hf_model": {
|
| 1597 |
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|
| 1598 |
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|
| 1599 |
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|
| 1600 |
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|
| 1601 |
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|
| 1602 |
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| 1603 |
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|
@@ -1756,44 +1756,44 @@
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| 1756 |
"path": "repo:docs/data/task_surface_integrity.json",
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| 1757 |
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| 1760 |
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| 1761 |
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| 1763 |
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| 1764 |
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| 1765 |
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| 1766 |
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| 1767 |
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| 1768 |
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| 1769 |
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| 1770 |
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| 1773 |
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| 1774 |
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| 1775 |
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| 1776 |
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| 1779 |
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| 1780 |
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| 1781 |
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| 1782 |
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| 1785 |
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| 1786 |
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| 1787 |
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| 1788 |
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|
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| 1791 |
},
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| 1792 |
"hf_model": {
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| 1793 |
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|
| 1794 |
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|
| 1795 |
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| 1796 |
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| 1797 |
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| 1798 |
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| 1799 |
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|
@@ -1847,6 +1847,55 @@
|
|
| 1847 |
},
|
| 1848 |
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| 18189 |
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"path": "hf_artifacts:TASK_METHOD_20_RESULT_MATRIX.md",
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| 18190 |
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"exists": true,
|
| 18191 |
+
"bytes": 4224,
|
| 18192 |
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|
| 18193 |
+
},
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| 18194 |
+
"hf_model": {
|
| 18195 |
+
"path": "hf_model:TASK_METHOD_20_RESULT_MATRIX.md",
|
| 18196 |
+
"exists": true,
|
| 18197 |
+
"bytes": 4224,
|
| 18198 |
+
"sha256": "fe14a0e1709a8bb5b9fb1fd720ffde0aecfed578329d8e1e71b352a83b23b1f8"
|
| 18199 |
+
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| 18200 |
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| 18201 |
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"failures": []
|
| 18202 |
+
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|
| 18203 |
{
|
| 18204 |
"name": "docs/TASK_SUITE_20.md",
|
| 18205 |
"status": "pass",
|
docs/data/public_surface_qa.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Public Project Surface",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-
|
| 5 |
"scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
|
| 6 |
"checks": [
|
| 7 |
{
|
|
@@ -18,7 +18,7 @@
|
|
| 18 |
"website_integrity": {
|
| 19 |
"exists": true,
|
| 20 |
"status": "pass",
|
| 21 |
-
"generated_at_utc": "2026-06-
|
| 22 |
},
|
| 23 |
"rendered_site_check": {
|
| 24 |
"exists": true,
|
|
@@ -28,27 +28,27 @@
|
|
| 28 |
"task_surface_integrity": {
|
| 29 |
"exists": true,
|
| 30 |
"status": "pass",
|
| 31 |
-
"generated_at_utc": "2026-06-
|
| 32 |
},
|
| 33 |
"source_alignment": {
|
| 34 |
"exists": true,
|
| 35 |
"status": "pass",
|
| 36 |
-
"generated_at_utc": "2026-06-
|
| 37 |
},
|
| 38 |
"scale_up_status": {
|
| 39 |
"exists": true,
|
| 40 |
"status": "pass",
|
| 41 |
-
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|
| 42 |
},
|
| 43 |
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|
| 44 |
"exists": true,
|
| 45 |
"status": "pass",
|
| 46 |
-
"generated_at_utc": "2026-06-
|
| 47 |
},
|
| 48 |
"mirror_parity": {
|
| 49 |
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|
| 50 |
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|
| 51 |
-
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|
| 52 |
}
|
| 53 |
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|
| 54 |
"failures": {}
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|
@@ -97,7 +97,7 @@
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|
| 97 |
"marker_counts": {
|
| 98 |
"Ropedia Xperience-10M Task Suite": 16,
|
| 99 |
"Xperience-10M": 149,
|
| 100 |
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|
| 101 |
"Qwen3-Omni": 148,
|
| 102 |
"128-episode pilot": 1
|
| 103 |
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|
|
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Public Project Surface",
|
| 3 |
"status": "pass",
|
| 4 |
+
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|
| 5 |
"scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
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| 6 |
"checks": [
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| 7 |
{
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|
|
|
| 18 |
"website_integrity": {
|
| 19 |
"exists": true,
|
| 20 |
"status": "pass",
|
| 21 |
+
"generated_at_utc": "2026-06-16T09:46:21+00:00"
|
| 22 |
},
|
| 23 |
"rendered_site_check": {
|
| 24 |
"exists": true,
|
|
|
|
| 28 |
"task_surface_integrity": {
|
| 29 |
"exists": true,
|
| 30 |
"status": "pass",
|
| 31 |
+
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|
| 32 |
},
|
| 33 |
"source_alignment": {
|
| 34 |
"exists": true,
|
| 35 |
"status": "pass",
|
| 36 |
+
"generated_at_utc": "2026-06-16T10:35:37+00:00"
|
| 37 |
},
|
| 38 |
"scale_up_status": {
|
| 39 |
"exists": true,
|
| 40 |
"status": "pass",
|
| 41 |
+
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|
| 42 |
},
|
| 43 |
"publication_package": {
|
| 44 |
"exists": true,
|
| 45 |
"status": "pass",
|
| 46 |
+
"generated_at_utc": "2026-06-16T09:46:35+00:00"
|
| 47 |
},
|
| 48 |
"mirror_parity": {
|
| 49 |
"exists": true,
|
| 50 |
"status": "pass",
|
| 51 |
+
"generated_at_utc": "2026-06-16T09:48:16+00:00"
|
| 52 |
}
|
| 53 |
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|
| 54 |
"failures": {}
|
|
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|
| 97 |
"marker_counts": {
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| 98 |
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|
| 99 |
"Xperience-10M": 149,
|
| 100 |
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|
| 101 |
"Qwen3-Omni": 148,
|
| 102 |
"128-episode pilot": 1
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| 103 |
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|
docs/data/publication_audit.json
CHANGED
|
@@ -1,6 +1,6 @@
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|
| 1 |
{
|
| 2 |
"status": "pass",
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| 3 |
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"generated_at_utc": "2026-06-
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| 4 |
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| 5 |
{
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| 6 |
"name": "required_publication_assets_present",
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|
@@ -193,8 +193,8 @@
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|
| 193 |
"github_repo": {
|
| 194 |
"root": "repo",
|
| 195 |
"exists": true,
|
| 196 |
-
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| 197 |
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| 200 |
"bytes": 55702978
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|
@@ -204,8 +204,8 @@
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|
| 204 |
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| 205 |
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| 206 |
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|
| 207 |
-
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| 208 |
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| 209 |
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| 210 |
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| 211 |
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|
@@ -215,8 +215,8 @@
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|
| 215 |
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| 216 |
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|
| 217 |
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|
| 218 |
-
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| 219 |
-
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| 220 |
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| 221 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
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| 222 |
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|
@@ -226,8 +226,8 @@
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|
| 226 |
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| 227 |
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|
| 228 |
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|
| 229 |
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| 230 |
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| 231 |
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| 232 |
"path": "pytorch_model.bin",
|
| 233 |
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|
| 1 |
{
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| 2 |
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| 3 |
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|
| 4 |
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| 5 |
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| 6 |
"name": "required_publication_assets_present",
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|
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|
| 193 |
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|
| 194 |
"root": "repo",
|
| 195 |
"exists": true,
|
| 196 |
+
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|
| 197 |
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|
| 198 |
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|
| 199 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
| 200 |
"bytes": 55702978
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|
|
|
| 204 |
"hf_space_bundle": {
|
| 205 |
"root": "hf_publish/space",
|
| 206 |
"exists": true,
|
| 207 |
+
"file_count": 968,
|
| 208 |
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|
| 209 |
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|
| 210 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
| 211 |
"bytes": 55702978
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|
|
|
| 215 |
"hf_artifact_bundle": {
|
| 216 |
"root": "hf_publish/artifacts",
|
| 217 |
"exists": true,
|
| 218 |
+
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|
| 219 |
+
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|
| 220 |
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|
| 221 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
| 222 |
"bytes": 55702978
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|
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|
| 226 |
"hf_model_bundle": {
|
| 227 |
"root": "hf_publish/model",
|
| 228 |
"exists": true,
|
| 229 |
+
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|
| 230 |
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|
| 231 |
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| 232 |
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| 233 |
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docs/data/quality_gates.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Release Checks",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-
|
| 5 |
"rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
|
| 6 |
"automated_gates": [
|
| 7 |
{
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Release Checks",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T10:35:14+00:00",
|
| 5 |
"rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
|
| 6 |
"automated_gates": [
|
| 7 |
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docs/data/scope_claims_audit.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-
|
| 4 |
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|
| 5 |
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|
| 6 |
"dataset_manifest_num_episodes": 119,
|
|
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
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|
| 4 |
"summary": {
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| 5 |
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|
| 6 |
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docs/data/source_alignment_audit.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Source Alignment Note",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-
|
| 5 |
"alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
|
| 6 |
"alignment_summary": {
|
| 7 |
"full_dataset_repo": "ropedia-ai/xperience-10m",
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Source Alignment Note",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T10:35:37+00:00",
|
| 5 |
"alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
|
| 6 |
"alignment_summary": {
|
| 7 |
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docs/data/task_method_20_result_matrix.json
ADDED
|
The diff for this file is too large to render.
See raw diff
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|
|
docs/data/task_surface_integrity.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-
|
| 4 |
"summary": {
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| 5 |
"task_count": 12,
|
| 6 |
"expected_task_count": 12,
|
|
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
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|
| 4 |
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| 5 |
"task_count": 12,
|
| 6 |
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docs/data/unified_task_model_radar.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
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|
docs/data/website_integrity.json
CHANGED
|
@@ -1,13 +1,13 @@
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{
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| 2 |
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"generated_at_utc": "2026-06-
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| 4 |
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|
| 5 |
"site_base": "/ropedia-xperience-10m-task-suite/",
|
| 6 |
"summary": {
|
| 7 |
"html_pages": 4,
|
| 8 |
-
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|
| 10 |
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|
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|
@@ -80,8 +80,8 @@
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|
| 80 |
"name": "project_overview_precedes_progress_ledger",
|
| 81 |
"status": "pass",
|
| 82 |
"reason": "The project overview should appear before the deeper progress ledger.",
|
| 83 |
-
"overview_index":
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| 84 |
-
"evidence_index":
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| 85 |
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|
| 86 |
{
|
| 87 |
"name": "project_status_links_json",
|
|
@@ -159,9 +159,9 @@
|
|
| 159 |
"name": "evaluation_protocol_between_overview_and_progress",
|
| 160 |
"status": "pass",
|
| 161 |
"reason": "The evaluation protocol should appear before the deeper evidence ledger.",
|
| 162 |
-
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| 163 |
-
"protocol_index":
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| 164 |
-
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| 165 |
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|
| 166 |
{
|
| 167 |
"name": "evaluation_protocol_links_json",
|
|
@@ -180,7 +180,7 @@
|
|
| 180 |
"status": "pass",
|
| 181 |
"reason": "The Suite anchor should show the task-suite map before the modality atlas.",
|
| 182 |
"first_marker_index": 471,
|
| 183 |
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| 184 |
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| 185 |
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| 186 |
"name": "suite_modality_atlas_contains_seven_cards",
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|
@@ -277,7 +277,7 @@
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|
| 277 |
{
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| 278 |
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| 279 |
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| 282 |
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| 283 |
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|
@@ -301,7 +301,7 @@
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| 301 |
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| 302 |
{
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| 303 |
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| 304 |
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| 306 |
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| 307 |
{
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|
@@ -336,7 +336,7 @@
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|
| 336 |
},
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| 337 |
{
|
| 338 |
"path": "data/live_publication_status.json",
|
| 339 |
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| 341 |
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| 342 |
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|
@@ -446,7 +446,7 @@
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| 446 |
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| 447 |
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| 448 |
"path": "data/scope_claims_audit.json",
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| 449 |
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| 451 |
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|
@@ -464,6 +464,11 @@
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| 464 |
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| 465 |
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| 466 |
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|
|
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|
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| 467 |
{
|
| 468 |
"path": "data/task_suite_20.json",
|
| 469 |
"bytes": 34648,
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|
@@ -491,12 +496,12 @@
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|
| 491 |
},
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| 492 |
{
|
| 493 |
"path": "data/unified_task_model_radar.json",
|
| 494 |
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| 496 |
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| 497 |
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| 498 |
"path": "data/website_integrity.json",
|
| 499 |
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|
@@ -587,7 +592,7 @@
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|
| 587 |
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| 588 |
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| 589 |
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| 592 |
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| 593 |
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|
| 1 |
{
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| 2 |
"status": "pass",
|
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"generated_at_utc": "2026-06-16T10:35:38+00:00",
|
| 4 |
"docs_root": "docs",
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"site_base": "/ropedia-xperience-10m-task-suite/",
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| 6 |
"summary": {
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|
| 80 |
"name": "project_overview_precedes_progress_ledger",
|
| 81 |
"status": "pass",
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| 82 |
"reason": "The project overview should appear before the deeper progress ledger.",
|
| 83 |
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| 85 |
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| 86 |
{
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| 87 |
"name": "project_status_links_json",
|
|
|
|
| 159 |
"name": "evaluation_protocol_between_overview_and_progress",
|
| 160 |
"status": "pass",
|
| 161 |
"reason": "The evaluation protocol should appear before the deeper evidence ledger.",
|
| 162 |
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|
| 163 |
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|
| 164 |
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|
| 165 |
},
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| 166 |
{
|
| 167 |
"name": "evaluation_protocol_links_json",
|
|
|
|
| 180 |
"status": "pass",
|
| 181 |
"reason": "The Suite anchor should show the task-suite map before the modality atlas.",
|
| 182 |
"first_marker_index": 471,
|
| 183 |
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"second_marker_index": 1831
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| 184 |
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| 185 |
{
|
| 186 |
"name": "suite_modality_atlas_contains_seven_cards",
|
|
|
|
| 277 |
{
|
| 278 |
"path": "index.html",
|
| 279 |
"id_count": 90,
|
| 280 |
+
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|
| 281 |
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| 282 |
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| 283 |
{
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|
|
|
| 301 |
},
|
| 302 |
{
|
| 303 |
"path": "data/artifact_index.json",
|
| 304 |
+
"bytes": 97873,
|
| 305 |
"top_level_type": "dict"
|
| 306 |
},
|
| 307 |
{
|
|
|
|
| 336 |
},
|
| 337 |
{
|
| 338 |
"path": "data/live_publication_status.json",
|
| 339 |
+
"bytes": 131884,
|
| 340 |
"top_level_type": "dict"
|
| 341 |
},
|
| 342 |
{
|
|
|
|
| 446 |
},
|
| 447 |
{
|
| 448 |
"path": "data/scope_claims_audit.json",
|
| 449 |
+
"bytes": 21630,
|
| 450 |
"top_level_type": "dict"
|
| 451 |
},
|
| 452 |
{
|
|
|
|
| 464 |
"bytes": 27807,
|
| 465 |
"top_level_type": "dict"
|
| 466 |
},
|
| 467 |
+
{
|
| 468 |
+
"path": "data/task_method_20_result_matrix.json",
|
| 469 |
+
"bytes": 129711,
|
| 470 |
+
"top_level_type": "dict"
|
| 471 |
+
},
|
| 472 |
{
|
| 473 |
"path": "data/task_suite_20.json",
|
| 474 |
"bytes": 34648,
|
|
|
|
| 496 |
},
|
| 497 |
{
|
| 498 |
"path": "data/unified_task_model_radar.json",
|
| 499 |
+
"bytes": 231290,
|
| 500 |
"top_level_type": "dict"
|
| 501 |
},
|
| 502 |
{
|
| 503 |
"path": "data/website_integrity.json",
|
| 504 |
+
"bytes": 18101,
|
| 505 |
"top_level_type": "dict"
|
| 506 |
},
|
| 507 |
{
|
|
|
|
| 592 |
{
|
| 593 |
"path": "assets/charts/unified_task_model_radar.svg",
|
| 594 |
"exists": true,
|
| 595 |
+
"bytes": 51944,
|
| 596 |
"format": "SVG",
|
| 597 |
"has_viewbox": true
|
| 598 |
},
|
docs/index.html
CHANGED
|
@@ -2769,25 +2769,25 @@
|
|
| 2769 |
<div class="hero-radar-panel" aria-label="Unified 20-task radar comparison">
|
| 2770 |
<div class="hero-radar-top">
|
| 2771 |
<strong>home radar comparison</strong>
|
| 2772 |
-
<span>
|
| 2773 |
</div>
|
| 2774 |
<div class="hero-radar-layout">
|
| 2775 |
<a class="hero-radar-frame" href="#suite" aria-label="Open full unified 20-task model radar">
|
| 2776 |
-
<img src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-
|
| 2777 |
</a>
|
| 2778 |
<div class="hero-radar-copy">
|
| 2779 |
<h2>Model comparison uses explicit task names and method contracts.</h2>
|
| 2780 |
-
<p>The full SVG names every axis and keeps
|
| 2781 |
<div class="hero-radar-stats" aria-label="Radar coverage summary">
|
| 2782 |
-
<div class="hero-radar-stat"><strong>
|
| 2783 |
-
<div class="hero-radar-stat"><strong>
|
| 2784 |
<div class="hero-radar-stat"><strong>40/40</strong><span>raw128 pass</span></div>
|
| 2785 |
<div class="hero-radar-stat"><strong>34,269</strong><span>128ep windows</span></div>
|
| 2786 |
</div>
|
| 2787 |
<div class="hero-method-list" aria-label="Method families shown in the radar">
|
| 2788 |
<div class="hero-method" style="--method-color:#67e8d1"><strong>Minimal + Neural MLP</strong><span>Single public-sample episode, full 20-task filled polygons.</span></div>
|
| 2789 |
-
<div class="hero-method" style="--method-color:#f59e0b"><strong>128ep Metadata + Raw Baselines</strong><span>
|
| 2790 |
-
<div class="hero-method" style="--method-color:#9bb8ff"><strong>Qwen3-Omni + Cosmos</strong><span>Verified held-out model branches
|
| 2791 |
</div>
|
| 2792 |
<div class="hero-task-strip" aria-label="Radar task axis examples">
|
| 2793 |
<span>01 Action Recognition</span>
|
|
@@ -2803,6 +2803,7 @@
|
|
| 2803 |
<a href="#suite">Open full radar</a>
|
| 2804 |
<a href="assets/charts/unified_task_model_radar.svg">Open SVG</a>
|
| 2805 |
<a href="data/unified_task_model_radar.json">Open radar JSON</a>
|
|
|
|
| 2806 |
</div>
|
| 2807 |
</div>
|
| 2808 |
</div>
|
|
@@ -3488,14 +3489,14 @@
|
|
| 3488 |
<div class="figure-brief">
|
| 3489 |
<article class="figure-brief-card">
|
| 3490 |
<h3>Unified 20-task polygon</h3>
|
| 3491 |
-
<p>The radar uses all 20 tasks as axes and lists each full task name in the chart key.
|
| 3492 |
</article>
|
| 3493 |
<article class="figure-brief-card">
|
| 3494 |
<h3>Metric normalization</h3>
|
| 3495 |
-
<p>Higher-is-better metrics are plotted directly on 0-1 axes. Lower-is-better metrics are converted to best/value within the task, while raw
|
| 3496 |
</article>
|
| 3497 |
</div>
|
| 3498 |
-
<img class="chart" src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-
|
| 3499 |
<div class="modality-atlas-panel" id="modality-atlas" aria-labelledby="modality-atlas-title">
|
| 3500 |
<div class="atlas-head">
|
| 3501 |
<div>
|
|
|
|
| 2769 |
<div class="hero-radar-panel" aria-label="Unified 20-task radar comparison">
|
| 2770 |
<div class="hero-radar-top">
|
| 2771 |
<strong>home radar comparison</strong>
|
| 2772 |
+
<span>180 method-task records / 111 scored axes / raw128 complete with 2 documented proxy axes</span>
|
| 2773 |
</div>
|
| 2774 |
<div class="hero-radar-layout">
|
| 2775 |
<a class="hero-radar-frame" href="#suite" aria-label="Open full unified 20-task model radar">
|
| 2776 |
+
<img src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v5" alt="Unified 20-task model radar with full task-name key, method legend, 20-record counts, scored-axis counts, and raw128 proxy notes">
|
| 2777 |
</a>
|
| 2778 |
<div class="hero-radar-copy">
|
| 2779 |
<h2>Model comparison uses explicit task names and method contracts.</h2>
|
| 2780 |
+
<p>The full SVG names every axis and keeps 20-result records, scored-axis counts, raw metric sources, and proxy notes attached to the same comparison view.</p>
|
| 2781 |
<div class="hero-radar-stats" aria-label="Radar coverage summary">
|
| 2782 |
+
<div class="hero-radar-stat"><strong>180</strong><span>method-task records</span></div>
|
| 2783 |
+
<div class="hero-radar-stat"><strong>111</strong><span>scored axes</span></div>
|
| 2784 |
<div class="hero-radar-stat"><strong>40/40</strong><span>raw128 pass</span></div>
|
| 2785 |
<div class="hero-radar-stat"><strong>34,269</strong><span>128ep windows</span></div>
|
| 2786 |
</div>
|
| 2787 |
<div class="hero-method-list" aria-label="Method families shown in the radar">
|
| 2788 |
<div class="hero-method" style="--method-color:#67e8d1"><strong>Minimal + Neural MLP</strong><span>Single public-sample episode, full 20-task filled polygons.</span></div>
|
| 2789 |
+
<div class="hero-method" style="--method-color:#f59e0b"><strong>128ep Metadata + Raw Baselines</strong><span>Every method has 20 records; raw NPZ heads score all 20 axes, with tasks 15 and 19 marked as compact proxies.</span></div>
|
| 2790 |
+
<div class="hero-method" style="--method-color:#9bb8ff"><strong>Qwen3-Omni + Cosmos</strong><span>Verified held-out model branches carry 20 records and plot only the task targets actually evaluated.</span></div>
|
| 2791 |
</div>
|
| 2792 |
<div class="hero-task-strip" aria-label="Radar task axis examples">
|
| 2793 |
<span>01 Action Recognition</span>
|
|
|
|
| 2803 |
<a href="#suite">Open full radar</a>
|
| 2804 |
<a href="assets/charts/unified_task_model_radar.svg">Open SVG</a>
|
| 2805 |
<a href="data/unified_task_model_radar.json">Open radar JSON</a>
|
| 2806 |
+
<a href="data/task_method_20_result_matrix.json">Open 20-result matrix</a>
|
| 2807 |
</div>
|
| 2808 |
</div>
|
| 2809 |
</div>
|
|
|
|
| 3489 |
<div class="figure-brief">
|
| 3490 |
<article class="figure-brief-card">
|
| 3491 |
<h3>Unified 20-task polygon</h3>
|
| 3492 |
+
<p>The radar uses all 20 tasks as axes and lists each full task name in the chart key. All 9 method series now expose 20 result records; colored overlays appear only where those records contain numeric scores.</p>
|
| 3493 |
</article>
|
| 3494 |
<article class="figure-brief-card">
|
| 3495 |
<h3>Metric normalization</h3>
|
| 3496 |
+
<p>Higher-is-better metrics are plotted directly on 0-1 axes. Lower-is-better metrics are converted to best/value within the task, while raw values, status reasons, sources, and the two raw128 compact proxy notes remain in the JSON mirrors.</p>
|
| 3497 |
</article>
|
| 3498 |
</div>
|
| 3499 |
+
<img class="chart" src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v5" alt="Unified 20-task radar comparing Minimal, Neural MLP, 128-episode metadata/raw baselines, Qwen3-Omni, and Cosmos3 with task names, method details, 20-record counts, scored-axis counts, and proxy notes">
|
| 3500 |
<div class="modality-atlas-panel" id="modality-atlas" aria-labelledby="modality-atlas-title">
|
| 3501 |
<div class="atlas-head">
|
| 3502 |
<div>
|
index.html
CHANGED
|
@@ -2769,25 +2769,25 @@
|
|
| 2769 |
<div class="hero-radar-panel" aria-label="Unified 20-task radar comparison">
|
| 2770 |
<div class="hero-radar-top">
|
| 2771 |
<strong>home radar comparison</strong>
|
| 2772 |
-
<span>
|
| 2773 |
</div>
|
| 2774 |
<div class="hero-radar-layout">
|
| 2775 |
<a class="hero-radar-frame" href="#suite" aria-label="Open full unified 20-task model radar">
|
| 2776 |
-
<img src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-
|
| 2777 |
</a>
|
| 2778 |
<div class="hero-radar-copy">
|
| 2779 |
<h2>Model comparison uses explicit task names and method contracts.</h2>
|
| 2780 |
-
<p>The full SVG names every axis and keeps
|
| 2781 |
<div class="hero-radar-stats" aria-label="Radar coverage summary">
|
| 2782 |
-
<div class="hero-radar-stat"><strong>
|
| 2783 |
-
<div class="hero-radar-stat"><strong>
|
| 2784 |
<div class="hero-radar-stat"><strong>40/40</strong><span>raw128 pass</span></div>
|
| 2785 |
<div class="hero-radar-stat"><strong>34,269</strong><span>128ep windows</span></div>
|
| 2786 |
</div>
|
| 2787 |
<div class="hero-method-list" aria-label="Method families shown in the radar">
|
| 2788 |
<div class="hero-method" style="--method-color:#67e8d1"><strong>Minimal + Neural MLP</strong><span>Single public-sample episode, full 20-task filled polygons.</span></div>
|
| 2789 |
-
<div class="hero-method" style="--method-color:#f59e0b"><strong>128ep Metadata + Raw Baselines</strong><span>
|
| 2790 |
-
<div class="hero-method" style="--method-color:#9bb8ff"><strong>Qwen3-Omni + Cosmos</strong><span>Verified held-out model branches
|
| 2791 |
</div>
|
| 2792 |
<div class="hero-task-strip" aria-label="Radar task axis examples">
|
| 2793 |
<span>01 Action Recognition</span>
|
|
@@ -2803,6 +2803,7 @@
|
|
| 2803 |
<a href="#suite">Open full radar</a>
|
| 2804 |
<a href="assets/charts/unified_task_model_radar.svg">Open SVG</a>
|
| 2805 |
<a href="data/unified_task_model_radar.json">Open radar JSON</a>
|
|
|
|
| 2806 |
</div>
|
| 2807 |
</div>
|
| 2808 |
</div>
|
|
@@ -3488,14 +3489,14 @@
|
|
| 3488 |
<div class="figure-brief">
|
| 3489 |
<article class="figure-brief-card">
|
| 3490 |
<h3>Unified 20-task polygon</h3>
|
| 3491 |
-
<p>The radar uses all 20 tasks as axes and lists each full task name in the chart key.
|
| 3492 |
</article>
|
| 3493 |
<article class="figure-brief-card">
|
| 3494 |
<h3>Metric normalization</h3>
|
| 3495 |
-
<p>Higher-is-better metrics are plotted directly on 0-1 axes. Lower-is-better metrics are converted to best/value within the task, while raw
|
| 3496 |
</article>
|
| 3497 |
</div>
|
| 3498 |
-
<img class="chart" src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-
|
| 3499 |
<div class="modality-atlas-panel" id="modality-atlas" aria-labelledby="modality-atlas-title">
|
| 3500 |
<div class="atlas-head">
|
| 3501 |
<div>
|
|
|
|
| 2769 |
<div class="hero-radar-panel" aria-label="Unified 20-task radar comparison">
|
| 2770 |
<div class="hero-radar-top">
|
| 2771 |
<strong>home radar comparison</strong>
|
| 2772 |
+
<span>180 method-task records / 111 scored axes / raw128 complete with 2 documented proxy axes</span>
|
| 2773 |
</div>
|
| 2774 |
<div class="hero-radar-layout">
|
| 2775 |
<a class="hero-radar-frame" href="#suite" aria-label="Open full unified 20-task model radar">
|
| 2776 |
+
<img src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v5" alt="Unified 20-task model radar with full task-name key, method legend, 20-record counts, scored-axis counts, and raw128 proxy notes">
|
| 2777 |
</a>
|
| 2778 |
<div class="hero-radar-copy">
|
| 2779 |
<h2>Model comparison uses explicit task names and method contracts.</h2>
|
| 2780 |
+
<p>The full SVG names every axis and keeps 20-result records, scored-axis counts, raw metric sources, and proxy notes attached to the same comparison view.</p>
|
| 2781 |
<div class="hero-radar-stats" aria-label="Radar coverage summary">
|
| 2782 |
+
<div class="hero-radar-stat"><strong>180</strong><span>method-task records</span></div>
|
| 2783 |
+
<div class="hero-radar-stat"><strong>111</strong><span>scored axes</span></div>
|
| 2784 |
<div class="hero-radar-stat"><strong>40/40</strong><span>raw128 pass</span></div>
|
| 2785 |
<div class="hero-radar-stat"><strong>34,269</strong><span>128ep windows</span></div>
|
| 2786 |
</div>
|
| 2787 |
<div class="hero-method-list" aria-label="Method families shown in the radar">
|
| 2788 |
<div class="hero-method" style="--method-color:#67e8d1"><strong>Minimal + Neural MLP</strong><span>Single public-sample episode, full 20-task filled polygons.</span></div>
|
| 2789 |
+
<div class="hero-method" style="--method-color:#f59e0b"><strong>128ep Metadata + Raw Baselines</strong><span>Every method has 20 records; raw NPZ heads score all 20 axes, with tasks 15 and 19 marked as compact proxies.</span></div>
|
| 2790 |
+
<div class="hero-method" style="--method-color:#9bb8ff"><strong>Qwen3-Omni + Cosmos</strong><span>Verified held-out model branches carry 20 records and plot only the task targets actually evaluated.</span></div>
|
| 2791 |
</div>
|
| 2792 |
<div class="hero-task-strip" aria-label="Radar task axis examples">
|
| 2793 |
<span>01 Action Recognition</span>
|
|
|
|
| 2803 |
<a href="#suite">Open full radar</a>
|
| 2804 |
<a href="assets/charts/unified_task_model_radar.svg">Open SVG</a>
|
| 2805 |
<a href="data/unified_task_model_radar.json">Open radar JSON</a>
|
| 2806 |
+
<a href="data/task_method_20_result_matrix.json">Open 20-result matrix</a>
|
| 2807 |
</div>
|
| 2808 |
</div>
|
| 2809 |
</div>
|
|
|
|
| 3489 |
<div class="figure-brief">
|
| 3490 |
<article class="figure-brief-card">
|
| 3491 |
<h3>Unified 20-task polygon</h3>
|
| 3492 |
+
<p>The radar uses all 20 tasks as axes and lists each full task name in the chart key. All 9 method series now expose 20 result records; colored overlays appear only where those records contain numeric scores.</p>
|
| 3493 |
</article>
|
| 3494 |
<article class="figure-brief-card">
|
| 3495 |
<h3>Metric normalization</h3>
|
| 3496 |
+
<p>Higher-is-better metrics are plotted directly on 0-1 axes. Lower-is-better metrics are converted to best/value within the task, while raw values, status reasons, sources, and the two raw128 compact proxy notes remain in the JSON mirrors.</p>
|
| 3497 |
</article>
|
| 3498 |
</div>
|
| 3499 |
+
<img class="chart" src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v5" alt="Unified 20-task radar comparing Minimal, Neural MLP, 128-episode metadata/raw baselines, Qwen3-Omni, and Cosmos3 with task names, method details, 20-record counts, scored-axis counts, and proxy notes">
|
| 3500 |
<div class="modality-atlas-panel" id="modality-atlas" aria-labelledby="modality-atlas-title">
|
| 3501 |
<div class="atlas-head">
|
| 3502 |
<div>
|
scripts/build_artifact_index.py
CHANGED
|
@@ -415,7 +415,23 @@ ARTIFACTS = [
|
|
| 415 |
"path": "docs/data/unified_task_model_radar.json",
|
| 416 |
"kind": "website_data",
|
| 417 |
"surface": "website_hf",
|
| 418 |
-
"shows": "Stores normalized 20-axis radar values, raw task metrics, Qwen3/Cosmos overlay mappings,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 419 |
},
|
| 420 |
{
|
| 421 |
"id": "unified_task_model_radar_chart",
|
|
|
|
| 415 |
"path": "docs/data/unified_task_model_radar.json",
|
| 416 |
"kind": "website_data",
|
| 417 |
"surface": "website_hf",
|
| 418 |
+
"shows": "Stores normalized 20-axis radar values, raw task metrics, Qwen3/Cosmos overlay mappings, branch-card caveats, and explicit scoreless status records.",
|
| 419 |
+
},
|
| 420 |
+
{
|
| 421 |
+
"id": "task_method_20_result_matrix_json",
|
| 422 |
+
"title": "Task-method 20-result matrix JSON",
|
| 423 |
+
"path": "docs/data/task_method_20_result_matrix.json",
|
| 424 |
+
"kind": "website_data",
|
| 425 |
+
"surface": "website_hf",
|
| 426 |
+
"shows": "Machine-readable 9-method by 20-task matrix where every method has 20 records and scoreless cells carry unsupported/not-evaluated reasons.",
|
| 427 |
+
},
|
| 428 |
+
{
|
| 429 |
+
"id": "task_method_20_result_matrix",
|
| 430 |
+
"title": "Task-method 20-result matrix",
|
| 431 |
+
"path": "TASK_METHOD_20_RESULT_MATRIX.md",
|
| 432 |
+
"kind": "evaluation_protocol",
|
| 433 |
+
"surface": "repo_hf",
|
| 434 |
+
"shows": "Reader-facing table that separates 20 records per method from numeric scored axes, documented raw128 proxy scores, unsupported metadata targets, and model targets not evaluated in verified packages.",
|
| 435 |
},
|
| 436 |
{
|
| 437 |
"id": "unified_task_model_radar_chart",
|
scripts/build_unified_task_model_radar.py
CHANGED
|
@@ -40,6 +40,8 @@ COSMOS_SUPER_FD_METRICS_PATH = (
|
|
| 40 |
METADATA128_BASELINE_DIR = ROOT / "results/omni_finetune/a100_128_metadata_task_baselines_20260616_v2"
|
| 41 |
RAW128_BASELINE_DIR = ROOT / "results/omni_finetune/a100_128_raw20_task_baselines_complete20_proxy_20260616T091500Z"
|
| 42 |
OUTPUT_JSON = ROOT / "docs/data/unified_task_model_radar.json"
|
|
|
|
|
|
|
| 43 |
OUTPUT_SVG = ROOT / "docs/assets/charts/unified_task_model_radar.svg"
|
| 44 |
|
| 45 |
|
|
@@ -152,17 +154,6 @@ FOUNDATION_TASK_METRICS = {
|
|
| 152 |
},
|
| 153 |
}
|
| 154 |
|
| 155 |
-
METADATA128_TASKS = {
|
| 156 |
-
"timeline_action",
|
| 157 |
-
"timeline_subtask",
|
| 158 |
-
"transition_detection",
|
| 159 |
-
"next_action",
|
| 160 |
-
"contact_prediction",
|
| 161 |
-
"object_relevance",
|
| 162 |
-
"caption_grounding",
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SHORT_TASK_LABELS = {
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"timeline_action": "Action",
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"timeline_subtask": "Step",
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PROXY_TASK_IDS = {"interaction_text_prediction", "camera_view_sync_retrieval"}
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def read_json(path: Path) -> dict[str, Any]:
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return json.loads(path.read_text(encoding="utf-8")) if path.exists() else {}
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def
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if task_id not in METADATA128_TASKS:
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path = METADATA128_BASELINE_DIR / ("neural_mlp" if neural else "") / task_id / "metrics.json"
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if not path.exists():
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return None
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payload = read_json(path)
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return {
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"raw": score,
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"metric_key": payload.get("primary_metric"),
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"source": str(path.relative_to(ROOT)),
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"scope": "multi_episode_128_metadata_baseline",
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}
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@@ -249,6 +261,8 @@ def read_a100_raw_metric(task_id: str, *, neural: bool = False) -> dict[str, Any
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"metric_key": payload.get("primary_metric"),
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"source": str(path.relative_to(ROOT)),
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"scope": "multi_episode_128_raw_sensor_feature_baseline",
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}
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return None
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@@ -279,6 +293,118 @@ def format_metric(value: float | None) -> str:
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return f"{value:.4f}"
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| 282 |
def point(cx: float, cy: float, radius: float, angle: float) -> tuple[float, float]:
|
| 283 |
return cx + math.cos(angle) * radius, cy + math.sin(angle) * radius
|
| 284 |
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@@ -364,12 +490,14 @@ def build_payload() -> dict[str, Any]:
|
|
| 364 |
"metric_key": row.get("metric_key"),
|
| 365 |
"source": row.get("artifact_sources", {}).get("minimal_metrics"),
|
| 366 |
"scope": "single_episode_public_sample",
|
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|
| 367 |
},
|
| 368 |
"neural_mlp": {
|
| 369 |
"raw": row.get("neural_primary_metric"),
|
| 370 |
"metric_key": row.get("metric_key"),
|
| 371 |
"source": row.get("artifact_sources", {}).get("neural_metrics"),
|
| 372 |
"scope": "single_episode_public_sample",
|
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|
| 373 |
},
|
| 374 |
}
|
| 375 |
for series_id, metric_key in FOUNDATION_TASK_METRICS.get(row["task_id"], {}).items():
|
|
@@ -385,11 +513,13 @@ def build_payload() -> dict[str, Any]:
|
|
| 385 |
}[series_id].relative_to(ROOT)
|
| 386 |
),
|
| 387 |
"scope": "multi_episode_128_partial_model_overlay",
|
|
|
|
|
|
|
| 388 |
}
|
| 389 |
-
metadata_simple =
|
| 390 |
if metadata_simple:
|
| 391 |
values["metadata128_simple"] = metadata_simple
|
| 392 |
-
metadata_neural =
|
| 393 |
if metadata_neural:
|
| 394 |
values["metadata128_neural_mlp"] = metadata_neural
|
| 395 |
raw_simple = read_a100_raw_metric(row["task_id"], neural=False)
|
|
@@ -405,9 +535,10 @@ def build_payload() -> dict[str, Any]:
|
|
| 405 |
if row.get("metric_direction") == "lower" and isinstance(item.get("raw"), (int, float)) and item["raw"] > 0
|
| 406 |
]
|
| 407 |
best_lower = min(lower_values) if lower_values else None
|
|
|
|
|
|
|
| 408 |
for item in values.values():
|
| 409 |
-
|
| 410 |
-
item["raw_text"] = format_metric(item.get("raw"))
|
| 411 |
|
| 412 |
tasks.append(
|
| 413 |
{
|
|
@@ -427,30 +558,54 @@ def build_payload() -> dict[str, Any]:
|
|
| 427 |
|
| 428 |
series_records = []
|
| 429 |
for series_id, spec in SERIES.items():
|
|
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|
|
| 430 |
covered = sum(1 for task in tasks if task["values"].get(series_id, {}).get("normalized_score") is not None)
|
|
|
|
|
|
|
| 431 |
series_records.append(
|
| 432 |
{
|
| 433 |
"id": series_id,
|
| 434 |
**spec,
|
| 435 |
"method_detail": METHOD_DETAILS.get(series_id, spec["scope"]),
|
| 436 |
"plotted_as": "filled polygon" if spec["kind"].startswith("full_20_task_baseline") else "colored point overlay",
|
|
|
|
|
|
|
| 437 |
"covered_task_count": covered,
|
|
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|
| 438 |
"coverage_fraction": covered / max(len(tasks), 1),
|
|
|
|
| 439 |
}
|
| 440 |
)
|
| 441 |
|
| 442 |
fd_loss = (cosmos_fd.get("loss_summary") or {}).get("mean")
|
| 443 |
-
|
| 444 |
"title": "Unified 20-Task Model Radar",
|
| 445 |
"status": "pass",
|
| 446 |
"generated_at_utc": datetime.now(timezone.utc).isoformat(timespec="seconds"),
|
| 447 |
"task_count": len(tasks),
|
|
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|
|
| 448 |
"normalization_policy": {
|
| 449 |
"higher_is_better": "bounded metrics are plotted directly on 0-1 axes after clipping to [0, 1]",
|
| 450 |
"lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
|
| 451 |
"raw_values": "raw metric values, metric keys, and sources are retained in this JSON; the SVG is an overview, not a replacement for the metric table",
|
| 452 |
-
"
|
| 453 |
-
"
|
|
|
|
| 454 |
"raw_128_overlay": "128-episode raw-feature baselines use staged sensor NPZ features. Eighteen axes use direct task targets; interaction text and camera-view sync are completed with documented compact proxies because raw interaction strings and paired video-view embeddings are absent from the 128 export.",
|
| 455 |
},
|
| 456 |
"series": series_records,
|
|
@@ -460,7 +615,7 @@ def build_payload() -> dict[str, Any]:
|
|
| 460 |
"id": "metadata128_simple",
|
| 461 |
"title": "128ep Metadata Simple",
|
| 462 |
"status": "a100_rerun_pass",
|
| 463 |
-
"coverage": f"{next(item for item in series_records if item['id'] == 'metadata128_simple')['
|
| 464 |
"headline": "34,269 rows; train/val/test 25,629/4,608/4,032",
|
| 465 |
"source": str((METADATA128_BASELINE_DIR / "summary_report.json").relative_to(ROOT)),
|
| 466 |
},
|
|
@@ -468,7 +623,7 @@ def build_payload() -> dict[str, Any]:
|
|
| 468 |
"id": "metadata128_neural_mlp",
|
| 469 |
"title": "128ep Metadata NN",
|
| 470 |
"status": "a100_rerun_pass",
|
| 471 |
-
"coverage": f"{next(item for item in series_records if item['id'] == 'metadata128_neural_mlp')['
|
| 472 |
"headline": "compact MLP heads over metadata/text features",
|
| 473 |
"source": str((METADATA128_BASELINE_DIR / "summary_report.json").relative_to(ROOT)),
|
| 474 |
},
|
|
@@ -476,7 +631,7 @@ def build_payload() -> dict[str, Any]:
|
|
| 476 |
"id": "raw128_simple",
|
| 477 |
"title": "128ep Raw Simple",
|
| 478 |
"status": "a100_raw20_complete_with_documented_proxies",
|
| 479 |
-
"coverage": f"{next(item for item in series_records if item['id'] == 'raw128_simple')['
|
| 480 |
"headline": "34,269 windows; centroid/ridge heads over 4430-dim sensor blocks",
|
| 481 |
"source": str((RAW128_BASELINE_DIR / "run_summary_all.json").relative_to(ROOT)),
|
| 482 |
},
|
|
@@ -484,7 +639,7 @@ def build_payload() -> dict[str, Any]:
|
|
| 484 |
"id": "raw128_neural_mlp",
|
| 485 |
"title": "128ep Raw NN",
|
| 486 |
"status": "a100_raw20_complete_with_documented_proxies",
|
| 487 |
-
"coverage": f"{next(item for item in series_records if item['id'] == 'raw128_neural_mlp')['
|
| 488 |
"headline": "MLP heads over staged features; tasks 15/19 use compact proxies",
|
| 489 |
"source": str((RAW128_BASELINE_DIR / "run_summary_all.json").relative_to(ROOT)),
|
| 490 |
},
|
|
@@ -493,7 +648,7 @@ def build_payload() -> dict[str, Any]:
|
|
| 493 |
"title": "Qwen3-Omni v6 LoRA",
|
| 494 |
"status": "verified",
|
| 495 |
"task_aligned_axes": SERIES["qwen3_omni_v6_lora"]["short_label"],
|
| 496 |
-
"coverage": f"{next(item for item in series_records if item['id'] == 'qwen3_omni_v6_lora')['
|
| 497 |
"headline": f"JSON validity {format_metric(qwen.get('json_validity_rate'))}; action macro-F1 {format_metric(qwen.get('action_macro_f1'))}",
|
| 498 |
"source": str(QWEN_V6_METRICS_PATH.relative_to(ROOT)),
|
| 499 |
},
|
|
@@ -501,7 +656,7 @@ def build_payload() -> dict[str, Any]:
|
|
| 501 |
"id": "cosmos3_super_reasoner",
|
| 502 |
"title": "Cosmos3-Super Reasoner",
|
| 503 |
"status": "verified_base_weight_eval",
|
| 504 |
-
"coverage": f"{next(item for item in series_records if item['id'] == 'cosmos3_super_reasoner')['
|
| 505 |
"headline": f"JSON validity {format_metric(cosmos_super.get('json_validity_rate'))}; action macro-F1 {format_metric(cosmos_super.get('action_macro_f1'))}",
|
| 506 |
"source": str(COSMOS_SUPER_REASONER_METRICS_PATH.relative_to(ROOT)),
|
| 507 |
},
|
|
@@ -509,7 +664,7 @@ def build_payload() -> dict[str, Any]:
|
|
| 509 |
"id": "cosmos3_nano_future_window",
|
| 510 |
"title": "Cosmos3-Nano Future Window",
|
| 511 |
"status": "verified_compatibility_eval",
|
| 512 |
-
"coverage": f"{next(item for item in series_records if item['id'] == 'cosmos3_nano_future_window')['
|
| 513 |
"headline": f"future retrieval MRR {format_metric(cosmos_nano.get('future_retrieval_mrr'))}; transition accuracy {format_metric(cosmos_nano.get('transition_accuracy'))}",
|
| 514 |
"source": str(COSMOS_NANO_METRICS_PATH.relative_to(ROOT)),
|
| 515 |
},
|
|
@@ -523,6 +678,8 @@ def build_payload() -> dict[str, Any]:
|
|
| 523 |
},
|
| 524 |
],
|
| 525 |
}
|
|
|
|
|
|
|
| 526 |
|
| 527 |
|
| 528 |
def render_svg(payload: dict[str, Any]) -> str:
|
|
@@ -547,13 +704,14 @@ def render_svg(payload: dict[str, Any]) -> str:
|
|
| 547 |
|
| 548 |
chip_specs = [
|
| 549 |
("20 task axes", "#ccffa0"),
|
| 550 |
-
("
|
|
|
|
| 551 |
("40/40 raw128 pass", "#f59e0b"),
|
| 552 |
("2 compact proxy axes", "#f472b6"),
|
| 553 |
]
|
| 554 |
chip_x = 70
|
| 555 |
for label, color in chip_specs:
|
| 556 |
-
chip_w = 168 if len(label) < 15 else
|
| 557 |
parts.append(f'<rect x="{chip_x}" y="174" width="{chip_w}" height="34" rx="17" fill="{color}" fill-opacity="0.10" stroke="{color}" stroke-opacity="0.38"/>')
|
| 558 |
parts.append(svg_text(chip_x + 16, 197, label, size=13, fill=color, weight=760))
|
| 559 |
chip_x += chip_w + 12
|
|
@@ -615,7 +773,7 @@ def render_svg(payload: dict[str, Any]) -> str:
|
|
| 615 |
legend_x, legend_y = 1030, 178
|
| 616 |
parts.append(f'<rect x="{legend_x - 30}" y="{legend_y - 38}" width="820" height="560" rx="14" fill="#020502" fill-opacity="0.58" stroke="#ccffa0" stroke-opacity="0.20"/>')
|
| 617 |
parts.append(svg_text(legend_x, legend_y, "Methods compared", size=25, weight=800))
|
| 618 |
-
parts.append(svg_text(legend_x, legend_y + 30, "
|
| 619 |
|
| 620 |
cursor = legend_y + 74
|
| 621 |
for record in payload["series"]:
|
|
@@ -624,7 +782,7 @@ def render_svg(payload: dict[str, Any]) -> str:
|
|
| 624 |
if not record["kind"].startswith("full_20_task_baseline"):
|
| 625 |
parts.append(f'<circle cx="{legend_x + 25}" cy="{cursor - 7}" r="7" fill="{color}" stroke="#020502" stroke-width="2"/>')
|
| 626 |
parts.append(svg_text(legend_x + 66, cursor - 12, record["label"], size=15, weight=800))
|
| 627 |
-
parts.append(svg_text(legend_x + 330, cursor - 12, f"{record['
|
| 628 |
detail_lines = split_text(METHOD_DETAILS.get(record["id"], record["scope"]), 64)[:2]
|
| 629 |
parts.extend(svg_text_lines(legend_x + 66, cursor + 8, detail_lines, size=11, fill="#a5afa2", weight=560, line_height=15))
|
| 630 |
cursor += 50
|
|
@@ -652,9 +810,9 @@ def render_svg(payload: dict[str, Any]) -> str:
|
|
| 652 |
table_y = 1468
|
| 653 |
parts.append(f'<rect x="70" y="{table_y - 38}" width="1780" height="120" rx="12" fill="#020502" fill-opacity="0.58" stroke="#ccffa0" stroke-opacity="0.16"/>')
|
| 654 |
parts.append(svg_text(100, table_y - 10, "Reading rules", size=16, fill="#ccffa0", weight=800))
|
| 655 |
-
parts.append(svg_text(220, table_y - 10, "
|
| 656 |
parts.append(svg_text(220, table_y + 18, "Raw128 completion: 18 direct task targets plus 2 compact proxies. Task 15 predicts the dominant caption/object/interaction hash bin; task 19 retrieves depth/audio sync from camera pose.", size=13, fill="#a5afa2", weight=560))
|
| 657 |
-
parts.append(svg_text(220, table_y + 44, "
|
| 658 |
|
| 659 |
parts.append("</svg>")
|
| 660 |
return "\n".join(parts) + "\n"
|
|
@@ -663,10 +821,26 @@ def render_svg(payload: dict[str, Any]) -> str:
|
|
| 663 |
def main() -> int:
|
| 664 |
payload = build_payload()
|
| 665 |
OUTPUT_JSON.parent.mkdir(parents=True, exist_ok=True)
|
|
|
|
| 666 |
OUTPUT_SVG.parent.mkdir(parents=True, exist_ok=True)
|
| 667 |
OUTPUT_JSON.write_text(json.dumps(payload, indent=2) + "\n", encoding="utf-8")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 668 |
OUTPUT_SVG.write_text(render_svg(payload), encoding="utf-8")
|
| 669 |
print(f"PASS: wrote {OUTPUT_JSON}")
|
|
|
|
|
|
|
| 670 |
print(f"PASS: wrote {OUTPUT_SVG}")
|
| 671 |
return 0
|
| 672 |
|
|
|
|
| 40 |
METADATA128_BASELINE_DIR = ROOT / "results/omni_finetune/a100_128_metadata_task_baselines_20260616_v2"
|
| 41 |
RAW128_BASELINE_DIR = ROOT / "results/omni_finetune/a100_128_raw20_task_baselines_complete20_proxy_20260616T091500Z"
|
| 42 |
OUTPUT_JSON = ROOT / "docs/data/unified_task_model_radar.json"
|
| 43 |
+
OUTPUT_MATRIX_JSON = ROOT / "docs/data/task_method_20_result_matrix.json"
|
| 44 |
+
OUTPUT_MATRIX_MD = ROOT / "TASK_METHOD_20_RESULT_MATRIX.md"
|
| 45 |
OUTPUT_SVG = ROOT / "docs/assets/charts/unified_task_model_radar.svg"
|
| 46 |
|
| 47 |
|
|
|
|
| 154 |
},
|
| 155 |
}
|
| 156 |
|
|
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|
|
|
|
|
|
|
|
| 157 |
SHORT_TASK_LABELS = {
|
| 158 |
"timeline_action": "Action",
|
| 159 |
"timeline_subtask": "Step",
|
|
|
|
| 191 |
|
| 192 |
PROXY_TASK_IDS = {"interaction_text_prediction", "camera_view_sync_retrieval"}
|
| 193 |
|
| 194 |
+
STATUS_LABELS = {
|
| 195 |
+
"scored": "scored",
|
| 196 |
+
"proxy_scored": "proxy scored",
|
| 197 |
+
"unsupported_without_required_target": "unsupported",
|
| 198 |
+
"not_supported_by_metadata_only_package": "not supported",
|
| 199 |
+
"not_evaluated_in_verified_package": "not evaluated",
|
| 200 |
+
"missing_public_metric": "missing metric",
|
| 201 |
+
}
|
| 202 |
+
|
| 203 |
+
STATUS_SHORT = {
|
| 204 |
+
"scored": "score",
|
| 205 |
+
"proxy_scored": "proxy",
|
| 206 |
+
"unsupported_without_required_target": "unsupported",
|
| 207 |
+
"not_supported_by_metadata_only_package": "not supported",
|
| 208 |
+
"not_evaluated_in_verified_package": "not evaluated",
|
| 209 |
+
"missing_public_metric": "missing",
|
| 210 |
+
}
|
| 211 |
+
|
| 212 |
|
| 213 |
def read_json(path: Path) -> dict[str, Any]:
|
| 214 |
return json.loads(path.read_text(encoding="utf-8")) if path.exists() else {}
|
| 215 |
|
| 216 |
|
| 217 |
+
def read_a100_metadata_record(task_id: str, *, neural: bool = False) -> dict[str, Any] | None:
|
|
|
|
|
|
|
| 218 |
path = METADATA128_BASELINE_DIR / ("neural_mlp" if neural else "") / task_id / "metrics.json"
|
| 219 |
if not path.exists():
|
| 220 |
return None
|
| 221 |
payload = read_json(path)
|
| 222 |
+
status = payload.get("status", "missing_public_metric")
|
| 223 |
+
score = payload.get("primary_score") if status == "pass" else None
|
|
|
|
|
|
|
|
|
|
| 224 |
return {
|
| 225 |
"raw": score,
|
| 226 |
"metric_key": payload.get("primary_metric"),
|
| 227 |
"source": str(path.relative_to(ROOT)),
|
| 228 |
"scope": "multi_episode_128_metadata_baseline",
|
| 229 |
+
"status": "scored" if status == "pass" and score is not None else "unsupported_without_required_target",
|
| 230 |
+
"reason": payload.get("reason")
|
| 231 |
+
or payload.get("error")
|
| 232 |
+
or (
|
| 233 |
+
"metadata-only package has a metrics artifact for this task, but it does not contain a numeric public score"
|
| 234 |
+
if status != "pass"
|
| 235 |
+
else None
|
| 236 |
+
),
|
| 237 |
}
|
| 238 |
|
| 239 |
|
|
|
|
| 261 |
"metric_key": payload.get("primary_metric"),
|
| 262 |
"source": str(path.relative_to(ROOT)),
|
| 263 |
"scope": "multi_episode_128_raw_sensor_feature_baseline",
|
| 264 |
+
"status": "proxy_scored" if task_id in PROXY_TASK_IDS else "scored",
|
| 265 |
+
"reason": "documented compact proxy completion for this raw128 task axis" if task_id in PROXY_TASK_IDS else None,
|
| 266 |
}
|
| 267 |
return None
|
| 268 |
|
|
|
|
| 293 |
return f"{value:.4f}"
|
| 294 |
|
| 295 |
|
| 296 |
+
def status_label(status: str | None) -> str:
|
| 297 |
+
return STATUS_LABELS.get(status or "", status or "unknown")
|
| 298 |
+
|
| 299 |
+
|
| 300 |
+
def make_missing_record(series_id: str, task_id: str, metric_key: str | None) -> dict[str, Any]:
|
| 301 |
+
if series_id.startswith("metadata128"):
|
| 302 |
+
status = "not_supported_by_metadata_only_package"
|
| 303 |
+
reason = (
|
| 304 |
+
"the 128-episode metadata/text rerun did not produce this task target; "
|
| 305 |
+
"raw sensor blocks or a task-specific metadata target builder are required"
|
| 306 |
+
)
|
| 307 |
+
scope = "multi_episode_128_metadata_baseline"
|
| 308 |
+
elif series_id in {"qwen3_omni_v6_lora", "cosmos3_super_reasoner", "cosmos3_nano_future_window"}:
|
| 309 |
+
status = "not_evaluated_in_verified_package"
|
| 310 |
+
reason = (
|
| 311 |
+
"the verified public model package did not ask this branch to emit that task target; "
|
| 312 |
+
"a new task-specific evaluation package is required for a numeric score"
|
| 313 |
+
)
|
| 314 |
+
scope = "multi_episode_128_partial_model_overlay"
|
| 315 |
+
else:
|
| 316 |
+
status = "missing_public_metric"
|
| 317 |
+
reason = "no public metric artifact was found for this method-task pair"
|
| 318 |
+
scope = SERIES.get(series_id, {}).get("scope")
|
| 319 |
+
return {
|
| 320 |
+
"raw": None,
|
| 321 |
+
"metric_key": metric_key,
|
| 322 |
+
"source": None,
|
| 323 |
+
"scope": scope,
|
| 324 |
+
"status": status,
|
| 325 |
+
"reason": reason,
|
| 326 |
+
"normalized_score": None,
|
| 327 |
+
"raw_text": "n/a",
|
| 328 |
+
}
|
| 329 |
+
|
| 330 |
+
|
| 331 |
+
def finalize_value_record(item: dict[str, Any], direction: str, best_lower: float | None) -> None:
|
| 332 |
+
raw = item.get("raw")
|
| 333 |
+
item.setdefault("status", "scored" if isinstance(raw, (int, float)) else "missing_public_metric")
|
| 334 |
+
item["normalized_score"] = score_from_raw(raw if isinstance(raw, (int, float)) else None, direction, best_lower)
|
| 335 |
+
if item["normalized_score"] is None and item.get("status") in {"scored", "proxy_scored"}:
|
| 336 |
+
item["status"] = "missing_public_metric"
|
| 337 |
+
item.setdefault("reason", "numeric raw score could not be normalized for this task")
|
| 338 |
+
item["raw_text"] = format_metric(raw if isinstance(raw, (int, float)) else None)
|
| 339 |
+
item["status_label"] = status_label(item.get("status"))
|
| 340 |
+
|
| 341 |
+
|
| 342 |
+
def matrix_rows(payload: dict[str, Any]) -> list[dict[str, Any]]:
|
| 343 |
+
rows: list[dict[str, Any]] = []
|
| 344 |
+
for task in payload["tasks"]:
|
| 345 |
+
for series_id, series_spec in SERIES.items():
|
| 346 |
+
value = task["values"][series_id]
|
| 347 |
+
rows.append(
|
| 348 |
+
{
|
| 349 |
+
"task_number": task["task_number"],
|
| 350 |
+
"task_id": task["task_id"],
|
| 351 |
+
"task_label": task["label"],
|
| 352 |
+
"series_id": series_id,
|
| 353 |
+
"method": series_spec["label"],
|
| 354 |
+
"status": value.get("status"),
|
| 355 |
+
"status_label": value.get("status_label", status_label(value.get("status"))),
|
| 356 |
+
"scored": value.get("normalized_score") is not None,
|
| 357 |
+
"proxy_scored": value.get("status") == "proxy_scored",
|
| 358 |
+
"raw": value.get("raw"),
|
| 359 |
+
"raw_text": value.get("raw_text", "n/a"),
|
| 360 |
+
"normalized_score": value.get("normalized_score"),
|
| 361 |
+
"metric_key": value.get("metric_key"),
|
| 362 |
+
"source": value.get("source"),
|
| 363 |
+
"scope": value.get("scope"),
|
| 364 |
+
"reason": value.get("reason"),
|
| 365 |
+
}
|
| 366 |
+
)
|
| 367 |
+
return rows
|
| 368 |
+
|
| 369 |
+
|
| 370 |
+
def render_matrix_markdown(payload: dict[str, Any]) -> str:
|
| 371 |
+
lines = [
|
| 372 |
+
"# Task Method 20-Result Matrix",
|
| 373 |
+
"",
|
| 374 |
+
"Every method has one record for each of the 20 unified task contracts. Numeric scores appear only where a committed runner or verified package produced that task target.",
|
| 375 |
+
"",
|
| 376 |
+
"Legend: `score` = numeric task score, `proxy` = documented raw128 compact proxy score, `unsupported` = artifact exists but required target is not present, `not supported` = metadata-only package cannot form that target, `not evaluated` = verified model package did not request that target.",
|
| 377 |
+
"",
|
| 378 |
+
"| Method | Records | Scored | Proxy scored | Scoreless | Status counts |",
|
| 379 |
+
"| --- | ---: | ---: | ---: | ---: | --- |",
|
| 380 |
+
]
|
| 381 |
+
for record in payload["series"]:
|
| 382 |
+
counts = record["status_counts"]
|
| 383 |
+
count_text = ", ".join(f"{status_label(key)} {value}" for key, value in sorted(counts.items()))
|
| 384 |
+
lines.append(
|
| 385 |
+
f"| {record['label']} | {record['result_record_count']} | {record['scored_task_count']} | "
|
| 386 |
+
f"{record['proxy_scored_task_count']} | {record['scoreless_task_count']} | {count_text} |"
|
| 387 |
+
)
|
| 388 |
+
lines.extend(
|
| 389 |
+
[
|
| 390 |
+
"",
|
| 391 |
+
"| # | Task | " + " | ".join(spec["short_label"] for spec in SERIES.values()) + " |",
|
| 392 |
+
"| ---: | --- | " + " | ".join("---" for _ in SERIES) + " |",
|
| 393 |
+
]
|
| 394 |
+
)
|
| 395 |
+
for task in payload["tasks"]:
|
| 396 |
+
cells = [STATUS_SHORT.get(task["values"][series_id].get("status"), "unknown") for series_id in SERIES]
|
| 397 |
+
lines.append(f"| {task['task_number']:02d} | {task['label']} | " + " | ".join(cells) + " |")
|
| 398 |
+
lines.extend(
|
| 399 |
+
[
|
| 400 |
+
"",
|
| 401 |
+
"Sources and raw values are in `docs/data/task_method_20_result_matrix.json` and `docs/data/unified_task_model_radar.json`.",
|
| 402 |
+
"",
|
| 403 |
+
]
|
| 404 |
+
)
|
| 405 |
+
return "\n".join(lines)
|
| 406 |
+
|
| 407 |
+
|
| 408 |
def point(cx: float, cy: float, radius: float, angle: float) -> tuple[float, float]:
|
| 409 |
return cx + math.cos(angle) * radius, cy + math.sin(angle) * radius
|
| 410 |
|
|
|
|
| 490 |
"metric_key": row.get("metric_key"),
|
| 491 |
"source": row.get("artifact_sources", {}).get("minimal_metrics"),
|
| 492 |
"scope": "single_episode_public_sample",
|
| 493 |
+
"status": "scored",
|
| 494 |
},
|
| 495 |
"neural_mlp": {
|
| 496 |
"raw": row.get("neural_primary_metric"),
|
| 497 |
"metric_key": row.get("metric_key"),
|
| 498 |
"source": row.get("artifact_sources", {}).get("neural_metrics"),
|
| 499 |
"scope": "single_episode_public_sample",
|
| 500 |
+
"status": "scored",
|
| 501 |
},
|
| 502 |
}
|
| 503 |
for series_id, metric_key in FOUNDATION_TASK_METRICS.get(row["task_id"], {}).items():
|
|
|
|
| 513 |
}[series_id].relative_to(ROOT)
|
| 514 |
),
|
| 515 |
"scope": "multi_episode_128_partial_model_overlay",
|
| 516 |
+
"status": "scored" if isinstance(raw, (int, float)) else "missing_public_metric",
|
| 517 |
+
"reason": None if isinstance(raw, (int, float)) else f"metric {metric_key} is absent from the verified public package",
|
| 518 |
}
|
| 519 |
+
metadata_simple = read_a100_metadata_record(row["task_id"], neural=False)
|
| 520 |
if metadata_simple:
|
| 521 |
values["metadata128_simple"] = metadata_simple
|
| 522 |
+
metadata_neural = read_a100_metadata_record(row["task_id"], neural=True)
|
| 523 |
if metadata_neural:
|
| 524 |
values["metadata128_neural_mlp"] = metadata_neural
|
| 525 |
raw_simple = read_a100_raw_metric(row["task_id"], neural=False)
|
|
|
|
| 535 |
if row.get("metric_direction") == "lower" and isinstance(item.get("raw"), (int, float)) and item["raw"] > 0
|
| 536 |
]
|
| 537 |
best_lower = min(lower_values) if lower_values else None
|
| 538 |
+
for series_id in SERIES:
|
| 539 |
+
values.setdefault(series_id, make_missing_record(series_id, row["task_id"], row.get("metric_key")))
|
| 540 |
for item in values.values():
|
| 541 |
+
finalize_value_record(item, row.get("metric_direction", "higher"), best_lower)
|
|
|
|
| 542 |
|
| 543 |
tasks.append(
|
| 544 |
{
|
|
|
|
| 558 |
|
| 559 |
series_records = []
|
| 560 |
for series_id, spec in SERIES.items():
|
| 561 |
+
status_counts: dict[str, int] = {}
|
| 562 |
+
for task in tasks:
|
| 563 |
+
status = task["values"][series_id].get("status", "unknown")
|
| 564 |
+
status_counts[status] = status_counts.get(status, 0) + 1
|
| 565 |
covered = sum(1 for task in tasks if task["values"].get(series_id, {}).get("normalized_score") is not None)
|
| 566 |
+
proxy_count = status_counts.get("proxy_scored", 0)
|
| 567 |
+
scoreless = len(tasks) - covered
|
| 568 |
series_records.append(
|
| 569 |
{
|
| 570 |
"id": series_id,
|
| 571 |
**spec,
|
| 572 |
"method_detail": METHOD_DETAILS.get(series_id, spec["scope"]),
|
| 573 |
"plotted_as": "filled polygon" if spec["kind"].startswith("full_20_task_baseline") else "colored point overlay",
|
| 574 |
+
"result_record_count": len(tasks),
|
| 575 |
+
"scored_task_count": covered,
|
| 576 |
"covered_task_count": covered,
|
| 577 |
+
"proxy_scored_task_count": proxy_count,
|
| 578 |
+
"scoreless_task_count": scoreless,
|
| 579 |
+
"unsupported_task_count": status_counts.get("unsupported_without_required_target", 0)
|
| 580 |
+
+ status_counts.get("not_supported_by_metadata_only_package", 0),
|
| 581 |
+
"not_evaluated_task_count": status_counts.get("not_evaluated_in_verified_package", 0),
|
| 582 |
+
"status_counts": dict(sorted(status_counts.items())),
|
| 583 |
"coverage_fraction": covered / max(len(tasks), 1),
|
| 584 |
+
"result_record_fraction": len(tasks) / max(len(tasks), 1),
|
| 585 |
}
|
| 586 |
)
|
| 587 |
|
| 588 |
fd_loss = (cosmos_fd.get("loss_summary") or {}).get("mean")
|
| 589 |
+
payload = {
|
| 590 |
"title": "Unified 20-Task Model Radar",
|
| 591 |
"status": "pass",
|
| 592 |
"generated_at_utc": datetime.now(timezone.utc).isoformat(timespec="seconds"),
|
| 593 |
"task_count": len(tasks),
|
| 594 |
+
"method_count": len(SERIES),
|
| 595 |
+
"method_task_record_count": len(tasks) * len(SERIES),
|
| 596 |
+
"scored_method_task_count": sum(
|
| 597 |
+
1
|
| 598 |
+
for task in tasks
|
| 599 |
+
for series_id in SERIES
|
| 600 |
+
if task["values"][series_id].get("normalized_score") is not None
|
| 601 |
+
),
|
| 602 |
"normalization_policy": {
|
| 603 |
"higher_is_better": "bounded metrics are plotted directly on 0-1 axes after clipping to [0, 1]",
|
| 604 |
"lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
|
| 605 |
"raw_values": "raw metric values, metric keys, and sources are retained in this JSON; the SVG is an overview, not a replacement for the metric table",
|
| 606 |
+
"result_record_policy": "every method has 20 task records; records without a numeric score carry explicit unsupported/not-evaluated status and reason fields",
|
| 607 |
+
"foundation_model_overlay": "Qwen3/Cosmos points are plotted only on task-aligned axes. Scoreless records mean the public result does not evaluate that task contract.",
|
| 608 |
+
"metadata_128_overlay": "128-episode metadata baselines have 20 records, but numeric scores only where the public JSONL contains enough task labels without raw feature blocks.",
|
| 609 |
"raw_128_overlay": "128-episode raw-feature baselines use staged sensor NPZ features. Eighteen axes use direct task targets; interaction text and camera-view sync are completed with documented compact proxies because raw interaction strings and paired video-view embeddings are absent from the 128 export.",
|
| 610 |
},
|
| 611 |
"series": series_records,
|
|
|
|
| 615 |
"id": "metadata128_simple",
|
| 616 |
"title": "128ep Metadata Simple",
|
| 617 |
"status": "a100_rerun_pass",
|
| 618 |
+
"coverage": f"20 records / {next(item for item in series_records if item['id'] == 'metadata128_simple')['scored_task_count']} scored JSONL-supported axes",
|
| 619 |
"headline": "34,269 rows; train/val/test 25,629/4,608/4,032",
|
| 620 |
"source": str((METADATA128_BASELINE_DIR / "summary_report.json").relative_to(ROOT)),
|
| 621 |
},
|
|
|
|
| 623 |
"id": "metadata128_neural_mlp",
|
| 624 |
"title": "128ep Metadata NN",
|
| 625 |
"status": "a100_rerun_pass",
|
| 626 |
+
"coverage": f"20 records / {next(item for item in series_records if item['id'] == 'metadata128_neural_mlp')['scored_task_count']} scored JSONL-supported axes",
|
| 627 |
"headline": "compact MLP heads over metadata/text features",
|
| 628 |
"source": str((METADATA128_BASELINE_DIR / "summary_report.json").relative_to(ROOT)),
|
| 629 |
},
|
|
|
|
| 631 |
"id": "raw128_simple",
|
| 632 |
"title": "128ep Raw Simple",
|
| 633 |
"status": "a100_raw20_complete_with_documented_proxies",
|
| 634 |
+
"coverage": f"20 records / {next(item for item in series_records if item['id'] == 'raw128_simple')['scored_task_count']} scored axes; 18 direct + 2 proxy",
|
| 635 |
"headline": "34,269 windows; centroid/ridge heads over 4430-dim sensor blocks",
|
| 636 |
"source": str((RAW128_BASELINE_DIR / "run_summary_all.json").relative_to(ROOT)),
|
| 637 |
},
|
|
|
|
| 639 |
"id": "raw128_neural_mlp",
|
| 640 |
"title": "128ep Raw NN",
|
| 641 |
"status": "a100_raw20_complete_with_documented_proxies",
|
| 642 |
+
"coverage": f"20 records / {next(item for item in series_records if item['id'] == 'raw128_neural_mlp')['scored_task_count']} scored axes; 18 direct + 2 proxy",
|
| 643 |
"headline": "MLP heads over staged features; tasks 15/19 use compact proxies",
|
| 644 |
"source": str((RAW128_BASELINE_DIR / "run_summary_all.json").relative_to(ROOT)),
|
| 645 |
},
|
|
|
|
| 648 |
"title": "Qwen3-Omni v6 LoRA",
|
| 649 |
"status": "verified",
|
| 650 |
"task_aligned_axes": SERIES["qwen3_omni_v6_lora"]["short_label"],
|
| 651 |
+
"coverage": f"20 records / {next(item for item in series_records if item['id'] == 'qwen3_omni_v6_lora')['scored_task_count']} scored task-aligned axes",
|
| 652 |
"headline": f"JSON validity {format_metric(qwen.get('json_validity_rate'))}; action macro-F1 {format_metric(qwen.get('action_macro_f1'))}",
|
| 653 |
"source": str(QWEN_V6_METRICS_PATH.relative_to(ROOT)),
|
| 654 |
},
|
|
|
|
| 656 |
"id": "cosmos3_super_reasoner",
|
| 657 |
"title": "Cosmos3-Super Reasoner",
|
| 658 |
"status": "verified_base_weight_eval",
|
| 659 |
+
"coverage": f"20 records / {next(item for item in series_records if item['id'] == 'cosmos3_super_reasoner')['scored_task_count']} scored task-aligned axes",
|
| 660 |
"headline": f"JSON validity {format_metric(cosmos_super.get('json_validity_rate'))}; action macro-F1 {format_metric(cosmos_super.get('action_macro_f1'))}",
|
| 661 |
"source": str(COSMOS_SUPER_REASONER_METRICS_PATH.relative_to(ROOT)),
|
| 662 |
},
|
|
|
|
| 664 |
"id": "cosmos3_nano_future_window",
|
| 665 |
"title": "Cosmos3-Nano Future Window",
|
| 666 |
"status": "verified_compatibility_eval",
|
| 667 |
+
"coverage": f"20 records / {next(item for item in series_records if item['id'] == 'cosmos3_nano_future_window')['scored_task_count']} scored task-aligned axes",
|
| 668 |
"headline": f"future retrieval MRR {format_metric(cosmos_nano.get('future_retrieval_mrr'))}; transition accuracy {format_metric(cosmos_nano.get('transition_accuracy'))}",
|
| 669 |
"source": str(COSMOS_NANO_METRICS_PATH.relative_to(ROOT)),
|
| 670 |
},
|
|
|
|
| 678 |
},
|
| 679 |
],
|
| 680 |
}
|
| 681 |
+
payload["task_method_result_matrix"] = matrix_rows(payload)
|
| 682 |
+
return payload
|
| 683 |
|
| 684 |
|
| 685 |
def render_svg(payload: dict[str, Any]) -> str:
|
|
|
|
| 704 |
|
| 705 |
chip_specs = [
|
| 706 |
("20 task axes", "#ccffa0"),
|
| 707 |
+
(f"{payload['method_task_record_count']} method-task records", "#67e8d1"),
|
| 708 |
+
(f"{payload['scored_method_task_count']} scored axes", "#22d3ee"),
|
| 709 |
("40/40 raw128 pass", "#f59e0b"),
|
| 710 |
("2 compact proxy axes", "#f472b6"),
|
| 711 |
]
|
| 712 |
chip_x = 70
|
| 713 |
for label, color in chip_specs:
|
| 714 |
+
chip_w = 168 if len(label) < 15 else 250
|
| 715 |
parts.append(f'<rect x="{chip_x}" y="174" width="{chip_w}" height="34" rx="17" fill="{color}" fill-opacity="0.10" stroke="{color}" stroke-opacity="0.38"/>')
|
| 716 |
parts.append(svg_text(chip_x + 16, 197, label, size=13, fill=color, weight=760))
|
| 717 |
chip_x += chip_w + 12
|
|
|
|
| 773 |
legend_x, legend_y = 1030, 178
|
| 774 |
parts.append(f'<rect x="{legend_x - 30}" y="{legend_y - 38}" width="820" height="560" rx="14" fill="#020502" fill-opacity="0.58" stroke="#ccffa0" stroke-opacity="0.20"/>')
|
| 775 |
parts.append(svg_text(legend_x, legend_y, "Methods compared", size=25, weight=800))
|
| 776 |
+
parts.append(svg_text(legend_x, legend_y + 30, "Each method has 20 records; scored axes and scoreless statuses stay in the JSON matrix.", size=13, fill="#a5afa2", weight=560))
|
| 777 |
|
| 778 |
cursor = legend_y + 74
|
| 779 |
for record in payload["series"]:
|
|
|
|
| 782 |
if not record["kind"].startswith("full_20_task_baseline"):
|
| 783 |
parts.append(f'<circle cx="{legend_x + 25}" cy="{cursor - 7}" r="7" fill="{color}" stroke="#020502" stroke-width="2"/>')
|
| 784 |
parts.append(svg_text(legend_x + 66, cursor - 12, record["label"], size=15, weight=800))
|
| 785 |
+
parts.append(svg_text(legend_x + 330, cursor - 12, f"20 records / {record['scored_task_count']} scored", size=13, fill=color, weight=800))
|
| 786 |
detail_lines = split_text(METHOD_DETAILS.get(record["id"], record["scope"]), 64)[:2]
|
| 787 |
parts.extend(svg_text_lines(legend_x + 66, cursor + 8, detail_lines, size=11, fill="#a5afa2", weight=560, line_height=15))
|
| 788 |
cursor += 50
|
|
|
|
| 810 |
table_y = 1468
|
| 811 |
parts.append(f'<rect x="70" y="{table_y - 38}" width="1780" height="120" rx="12" fill="#020502" fill-opacity="0.58" stroke="#ccffa0" stroke-opacity="0.16"/>')
|
| 812 |
parts.append(svg_text(100, table_y - 10, "Reading rules", size=16, fill="#ccffa0", weight=800))
|
| 813 |
+
parts.append(svg_text(220, table_y - 10, "Every method has 20 task records; radius appears only where a numeric task score exists.", size=14, fill="#dce8d7", weight=650))
|
| 814 |
parts.append(svg_text(220, table_y + 18, "Raw128 completion: 18 direct task targets plus 2 compact proxies. Task 15 predicts the dominant caption/object/interaction hash bin; task 19 retrieves depth/audio sync from camera pose.", size=13, fill="#a5afa2", weight=560))
|
| 815 |
+
parts.append(svg_text(220, table_y + 44, "Scoreless metadata/Qwen/Cosmos records are explicit unsupported or not-evaluated cells in docs/data/task_method_20_result_matrix.json.", size=13, fill="#a5afa2", weight=560))
|
| 816 |
|
| 817 |
parts.append("</svg>")
|
| 818 |
return "\n".join(parts) + "\n"
|
|
|
|
| 821 |
def main() -> int:
|
| 822 |
payload = build_payload()
|
| 823 |
OUTPUT_JSON.parent.mkdir(parents=True, exist_ok=True)
|
| 824 |
+
OUTPUT_MATRIX_JSON.parent.mkdir(parents=True, exist_ok=True)
|
| 825 |
OUTPUT_SVG.parent.mkdir(parents=True, exist_ok=True)
|
| 826 |
OUTPUT_JSON.write_text(json.dumps(payload, indent=2) + "\n", encoding="utf-8")
|
| 827 |
+
matrix_payload = {
|
| 828 |
+
"title": "Task Method 20-Result Matrix",
|
| 829 |
+
"status": "pass",
|
| 830 |
+
"generated_at_utc": payload["generated_at_utc"],
|
| 831 |
+
"task_count": payload["task_count"],
|
| 832 |
+
"method_count": payload["method_count"],
|
| 833 |
+
"method_task_record_count": payload["method_task_record_count"],
|
| 834 |
+
"scored_method_task_count": payload["scored_method_task_count"],
|
| 835 |
+
"series": payload["series"],
|
| 836 |
+
"records": payload["task_method_result_matrix"],
|
| 837 |
+
}
|
| 838 |
+
OUTPUT_MATRIX_JSON.write_text(json.dumps(matrix_payload, indent=2) + "\n", encoding="utf-8")
|
| 839 |
+
OUTPUT_MATRIX_MD.write_text(render_matrix_markdown(payload), encoding="utf-8")
|
| 840 |
OUTPUT_SVG.write_text(render_svg(payload), encoding="utf-8")
|
| 841 |
print(f"PASS: wrote {OUTPUT_JSON}")
|
| 842 |
+
print(f"PASS: wrote {OUTPUT_MATRIX_JSON}")
|
| 843 |
+
print(f"PASS: wrote {OUTPUT_MATRIX_MD}")
|
| 844 |
print(f"PASS: wrote {OUTPUT_SVG}")
|
| 845 |
return 0
|
| 846 |
|
scripts/sync_hf_publish_mirrors.py
CHANGED
|
@@ -48,7 +48,8 @@ stride, feature manifest, chronological split, and minimal/neural head pattern.
|
|
| 48 |
The historical `tier2_task_suite` path is retained only for stable artifact
|
| 49 |
links to tasks 13-20. The unified radar chart is published as
|
| 50 |
`docs/assets/charts/unified_task_model_radar.svg` with values in
|
| 51 |
-
`docs/data/unified_task_model_radar.json`
|
|
|
|
| 52 |
"""
|
| 53 |
QWEN_COMPARISON_MARKER = "docs/data/qwen3_v5_v6_comparison.json"
|
| 54 |
QWEN_COMPARISON_ROW = (
|
|
@@ -151,7 +152,18 @@ def ensure_tier2_card_links(hf_root: Path, *, dry_run: bool) -> list[str]:
|
|
| 151 |
"links to tasks 13-20.\n",
|
| 152 |
"links to tasks 13-20. The unified radar chart is published as\n"
|
| 153 |
"`docs/assets/charts/unified_task_model_radar.svg` with values in\n"
|
| 154 |
-
"`docs/data/unified_task_model_radar.json`
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 155 |
)
|
| 156 |
if TIER2_MARKER in text:
|
| 157 |
if not dry_run:
|
|
|
|
| 48 |
The historical `tier2_task_suite` path is retained only for stable artifact
|
| 49 |
links to tasks 13-20. The unified radar chart is published as
|
| 50 |
`docs/assets/charts/unified_task_model_radar.svg` with values in
|
| 51 |
+
`docs/data/unified_task_model_radar.json`; the 9-method by 20-task completion
|
| 52 |
+
matrix is in `docs/data/task_method_20_result_matrix.json`.
|
| 53 |
"""
|
| 54 |
QWEN_COMPARISON_MARKER = "docs/data/qwen3_v5_v6_comparison.json"
|
| 55 |
QWEN_COMPARISON_ROW = (
|
|
|
|
| 152 |
"links to tasks 13-20.\n",
|
| 153 |
"links to tasks 13-20. The unified radar chart is published as\n"
|
| 154 |
"`docs/assets/charts/unified_task_model_radar.svg` with values in\n"
|
| 155 |
+
"`docs/data/unified_task_model_radar.json`; the 9-method by\n"
|
| 156 |
+
"20-task completion matrix is in\n"
|
| 157 |
+
"`docs/data/task_method_20_result_matrix.json`.\n",
|
| 158 |
+
)
|
| 159 |
+
if (
|
| 160 |
+
"docs/data/unified_task_model_radar.json" in text
|
| 161 |
+
and "docs/data/task_method_20_result_matrix.json" not in text
|
| 162 |
+
):
|
| 163 |
+
text = text.replace(
|
| 164 |
+
"`docs/data/unified_task_model_radar.json`.",
|
| 165 |
+
"`docs/data/unified_task_model_radar.json`; the 9-method by 20-task\n"
|
| 166 |
+
"completion matrix is in `docs/data/task_method_20_result_matrix.json`.",
|
| 167 |
)
|
| 168 |
if TIER2_MARKER in text:
|
| 169 |
if not dry_run:
|
scripts/validate_mirror_parity.py
CHANGED
|
@@ -57,6 +57,7 @@ DATA_FILES = [
|
|
| 57 |
"task_suite_enhancement_128.json",
|
| 58 |
"task_surface_integrity.json",
|
| 59 |
"task_walkthroughs.json",
|
|
|
|
| 60 |
"tier2_task_suite.json",
|
| 61 |
"unified_task_model_radar.json",
|
| 62 |
"website_integrity.json",
|
|
@@ -235,6 +236,7 @@ DOC_FILES = [
|
|
| 235 |
"PROJECT_STATUS.md",
|
| 236 |
"REPRODUCIBILITY.md",
|
| 237 |
"TASK_SUITE_ENHANCEMENT_128.md",
|
|
|
|
| 238 |
"TASK_SUITE_20.md",
|
| 239 |
"PUBLIC_SURFACE_QA.md",
|
| 240 |
"RESEARCH_TAKEAWAYS.md",
|
|
|
|
| 57 |
"task_suite_enhancement_128.json",
|
| 58 |
"task_surface_integrity.json",
|
| 59 |
"task_walkthroughs.json",
|
| 60 |
+
"task_method_20_result_matrix.json",
|
| 61 |
"tier2_task_suite.json",
|
| 62 |
"unified_task_model_radar.json",
|
| 63 |
"website_integrity.json",
|
|
|
|
| 236 |
"PROJECT_STATUS.md",
|
| 237 |
"REPRODUCIBILITY.md",
|
| 238 |
"TASK_SUITE_ENHANCEMENT_128.md",
|
| 239 |
+
"TASK_METHOD_20_RESULT_MATRIX.md",
|
| 240 |
"TASK_SUITE_20.md",
|
| 241 |
"PUBLIC_SURFACE_QA.md",
|
| 242 |
"RESEARCH_TAKEAWAYS.md",
|