Add files using upload-large-folder tool
Browse files- FIGURE_INDEX.md +3 -3
- assets/charts/episode128_task_model_radar.svg +270 -280
- assets/charts/single_episode_task_model_radar.svg +214 -221
- assets/charts/unified_task_model_radar.svg +320 -331
- data/artifact_index.json +23 -23
- data/episode128_task_model_radar.json +1 -1
- data/figure_index.json +16 -16
- data/mirror_parity.json +158 -158
- data/public_surface_qa.json +7 -7
- data/publication_audit.json +3 -3
- data/quality_gates.json +1 -1
- data/scope_claims_audit.json +1 -1
- data/single_episode_task_model_radar.json +1 -1
- data/source_alignment_audit.json +1 -1
- data/task_method_20_result_matrix.json +1 -1
- data/task_surface_integrity.json +1 -1
- data/unified_task_model_radar.json +1 -1
- data/website_integrity.json +5 -5
- docs/data/artifact_index.json +23 -23
- docs/data/episode128_task_model_radar.json +1 -1
- docs/data/figure_index.json +16 -16
- docs/data/mirror_parity.json +158 -158
- docs/data/public_surface_qa.json +7 -7
- docs/data/publication_audit.json +3 -3
- docs/data/quality_gates.json +1 -1
- docs/data/single_episode_task_model_radar.json +1 -1
- docs/data/task_method_20_result_matrix.json +1 -1
- docs/data/task_surface_integrity.json +1 -1
- docs/data/unified_task_model_radar.json +1 -1
- docs/data/website_integrity.json +5 -5
- metrics/artifact_index.json +23 -23
- metrics/episode128_task_model_radar.json +1 -1
- metrics/figure_index.json +16 -16
- metrics/mirror_parity.json +158 -158
- metrics/public_surface_qa.json +7 -7
- metrics/publication_audit.json +3 -3
- metrics/quality_gates.json +1 -1
- metrics/scope_claims_audit.json +1 -1
- metrics/single_episode_task_model_radar.json +1 -1
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- metrics/task_method_20_result_matrix.json +1 -1
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- metrics/unified_task_model_radar.json +1 -1
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- scripts/build_unified_task_model_radar.py +18 -23
FIGURE_INDEX.md
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@@ -31,9 +31,9 @@ Public figures, diagrams, charts, and derived modality thumbnails. Raw Xperience
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| 31 |
| Research direction coverage chart | `docs/assets/charts/research_direction_coverage.svg` | 1180 x 700 | `scripts/generate_visualizations.py` | Four-track coverage map for Ropedia research directions. |
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| 32 |
| Research direction extension chart | `docs/assets/charts/research_direction_extension_tasks.svg` | 1420 x 920 | `scripts/generate_visualizations.py` | Four coded extension probes, one per Ropedia research direction. |
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| 33 |
| Tasks 13-20 baseline chart | `docs/assets/charts/tier2_task_suite.svg` | 1440 x 832 | `scripts/tier2_task_suite.py` | Eight additional sample-supported tasks in the unified 20-task suite with aligned minimal and neural baseline metrics. |
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| 34 |
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| Unified 20-task model radar | `docs/assets/charts/unified_task_model_radar.svg` |
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| Single-episode 20-task model radar | `docs/assets/charts/single_episode_task_model_radar.svg` |
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| 128-episode 20-task model radar | `docs/assets/charts/episode128_task_model_radar.svg` |
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| Feature block chart | `docs/assets/charts/feature_blocks.svg` | 1100 x 760 | `scripts/generate_visualizations.py` | Feature allocation by modality block. |
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| 38 |
| Minimal task score chart | `docs/assets/charts/episode_task_scores.svg` | 1100 x 556 | `scripts/generate_visualizations.py` | Minimal baseline metric snapshot across the task suite. |
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| 39 |
| Cross-modal retrieval chart | `docs/assets/charts/cross_modal_retrieval.svg` | 1100 x 284 | `scripts/generate_visualizations.py` | Retrieval behavior chart for the cross-modal task. |
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| 31 |
| Research direction coverage chart | `docs/assets/charts/research_direction_coverage.svg` | 1180 x 700 | `scripts/generate_visualizations.py` | Four-track coverage map for Ropedia research directions. |
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| 32 |
| Research direction extension chart | `docs/assets/charts/research_direction_extension_tasks.svg` | 1420 x 920 | `scripts/generate_visualizations.py` | Four coded extension probes, one per Ropedia research direction. |
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| 33 |
| Tasks 13-20 baseline chart | `docs/assets/charts/tier2_task_suite.svg` | 1440 x 832 | `scripts/tier2_task_suite.py` | Eight additional sample-supported tasks in the unified 20-task suite with aligned minimal and neural baseline metrics. |
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| 34 |
+
| Unified 20-task model radar | `docs/assets/charts/unified_task_model_radar.svg` | 2400 x 1840 | `scripts/build_unified_task_model_radar.py` | Twenty-axis direction-aware comparison of minimal and neural MLP baselines, with 128-episode metadata, Qwen3, and Cosmos task-aligned overlay points and branch notes. |
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| 35 |
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| Single-episode 20-task model radar | `docs/assets/charts/single_episode_task_model_radar.svg` | 2400 x 1840 | `scripts/build_unified_task_model_radar.py` | Twenty-axis split radar for the one public-sample episode, comparing Minimal and Neural MLP as two complete 20/20 scored polygons. |
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| 36 |
+
| 128-episode 20-task model radar | `docs/assets/charts/episode128_task_model_radar.svg` | 2400 x 1840 | `scripts/build_unified_task_model_radar.py` | Twenty-axis split radar for selected 128-episode methods: raw-feature simple/NN as complete scored polygons and metadata/Qwen/Cosmos as task-aligned overlays. |
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| 37 |
| Feature block chart | `docs/assets/charts/feature_blocks.svg` | 1100 x 760 | `scripts/generate_visualizations.py` | Feature allocation by modality block. |
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| 38 |
| Minimal task score chart | `docs/assets/charts/episode_task_scores.svg` | 1100 x 556 | `scripts/generate_visualizations.py` | Minimal baseline metric snapshot across the task suite. |
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| 39 |
| Cross-modal retrieval chart | `docs/assets/charts/cross_modal_retrieval.svg` | 1100 x 284 | `scripts/generate_visualizations.py` | Retrieval behavior chart for the cross-modal task. |
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assets/charts/episode128_task_model_radar.svg
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assets/charts/single_episode_task_model_radar.svg
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assets/charts/unified_task_model_radar.svg
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data/artifact_index.json
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"surface": "website_hf",
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@@ -1,7 +1,7 @@
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{
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{
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| 5 |
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CHANGED
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CHANGED
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| 4 |
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CHANGED
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| 5 |
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| 6 |
"method_count": 9,
|
| 7 |
"method_task_record_count": 180,
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Unified 20-Task Model Radar",
|
| 3 |
"status": "pass",
|
| 4 |
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"generated_at_utc": "2026-06-16T11:26:57+00:00",
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| 5 |
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| 6 |
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|
| 7 |
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data/website_integrity.json
CHANGED
|
@@ -1,6 +1,6 @@
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| 1 |
{
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"docs_root": "docs",
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| 5 |
"site_base": "/ropedia-xperience-10m-task-suite/",
|
| 6 |
"summary": {
|
|
@@ -391,7 +391,7 @@
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|
| 391 |
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| 392 |
{
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| 393 |
"path": "data/publication_audit.json",
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| 394 |
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| 395 |
"top_level_type": "dict"
|
| 396 |
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|
| 397 |
{
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|
@@ -546,7 +546,7 @@
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|
| 546 |
{
|
| 547 |
"path": "assets/charts/episode128_task_model_radar.svg",
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| 548 |
"exists": true,
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| 549 |
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| 550 |
"format": "SVG",
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| 551 |
"has_viewbox": true
|
| 552 |
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|
|
@@ -602,7 +602,7 @@
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|
| 602 |
{
|
| 603 |
"path": "assets/charts/single_episode_task_model_radar.svg",
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| 604 |
"exists": true,
|
| 605 |
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"bytes":
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| 606 |
"format": "SVG",
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| 607 |
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| 608 |
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|
@@ -616,7 +616,7 @@
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|
| 616 |
{
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| 617 |
"path": "assets/charts/unified_task_model_radar.svg",
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| 618 |
"exists": true,
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| 619 |
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| 620 |
"format": "SVG",
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| 621 |
"has_viewbox": true
|
| 622 |
},
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|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
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"generated_at_utc": "2026-06-16T11:33:51+00:00",
|
| 4 |
"docs_root": "docs",
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| 5 |
"site_base": "/ropedia-xperience-10m-task-suite/",
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| 6 |
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|
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|
| 391 |
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| 392 |
{
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| 393 |
"path": "data/publication_audit.json",
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| 394 |
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| 396 |
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|
| 546 |
{
|
| 547 |
"path": "assets/charts/episode128_task_model_radar.svg",
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| 548 |
"exists": true,
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| 549 |
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"bytes": 43020,
|
| 550 |
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| 551 |
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|
| 602 |
{
|
| 603 |
"path": "assets/charts/single_episode_task_model_radar.svg",
|
| 604 |
"exists": true,
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| 605 |
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"bytes": 35229,
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| 606 |
"format": "SVG",
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| 607 |
"has_viewbox": true
|
| 608 |
},
|
|
|
|
| 616 |
{
|
| 617 |
"path": "assets/charts/unified_task_model_radar.svg",
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| 618 |
"exists": true,
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| 619 |
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"bytes": 49046,
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| 620 |
"format": "SVG",
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| 621 |
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| 622 |
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docs/data/artifact_index.json
CHANGED
|
@@ -1,6 +1,6 @@
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|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Task Suite Artifact Index",
|
| 3 |
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"generated_at_utc": "2026-06-
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| 4 |
"status": "pass",
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| 5 |
"artifact_count": 183,
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@@ -465,7 +465,7 @@
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@@ -586,7 +586,7 @@
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"id": "single_episode_task_model_radar_json",
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@@ -597,7 +597,7 @@
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| 597 |
"shows": "Machine-readable split radar for the one-episode Minimal and Neural MLP baselines, both scored on all 20 task contracts.",
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| 598 |
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"id": "episode128_task_model_radar_json",
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|
@@ -608,7 +608,7 @@
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| 608 |
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| 612 |
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{
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"id": "task_method_20_result_matrix_json",
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|
@@ -619,7 +619,7 @@
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@@ -640,8 +640,8 @@
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| 640 |
"surface": "website_hf",
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| 641 |
"shows": "Compares minimal and neural MLP baselines across all 20 tasks, with Qwen3/Cosmos task-aligned model overlays.",
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@@ -651,8 +651,8 @@
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| 651 |
"surface": "website_hf",
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| 652 |
"shows": "Separates the one-episode Minimal and Neural MLP 20/20 scored baselines into a clean two-polygon radar.",
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| 653 |
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"id": "episode128_task_model_radar_chart",
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@@ -662,8 +662,8 @@
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| 662 |
"surface": "website_hf",
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| 663 |
"shows": "Separates the selected 128-episode methods: raw-feature simple/NN as complete 20/20 scored polygons and metadata/Qwen/Cosmos as task-aligned overlays.",
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@@ -673,8 +673,8 @@
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| 673 |
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| 675 |
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| 677 |
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{
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| 794 |
"surface": "repo_hf",
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| 795 |
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| 796 |
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| 800 |
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"id": "figure_index_json",
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"surface": "website_hf",
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"shows": "Machine-readable visual asset index for website and Hugging Face mirrors.",
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@@ -905,7 +905,7 @@
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"volatile": true,
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| 911 |
{
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"volatile": true,
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| 1048 |
{
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@@ -1066,7 +1066,7 @@
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| 1066 |
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| 1078 |
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{
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{
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"title": "Ropedia Xperience-10M Task Suite Artifact Index",
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| 4 |
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"id": "task_method_20_result_matrix",
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| 640 |
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docs/data/episode128_task_model_radar.json
CHANGED
|
@@ -1,7 +1,7 @@
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|
| 1 |
{
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"title": "128-Episode 20-Task Radar",
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| 1 |
{
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| 2 |
"title": "128-Episode 20-Task Radar",
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| 7 |
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docs/data/figure_index.json
CHANGED
|
@@ -1,7 +1,7 @@
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{
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|
@@ -359,13 +359,13 @@
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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 |
-
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|
| 363 |
-
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|
| 364 |
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|
| 365 |
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|
| 366 |
-
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|
| 367 |
-
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|
| 368 |
-
"view_box": "0 0
|
| 369 |
},
|
| 370 |
"source_script_exists": true
|
| 371 |
},
|
|
@@ -377,13 +377,13 @@
|
|
| 377 |
"source_script": "scripts/build_unified_task_model_radar.py",
|
| 378 |
"surface": "website unified task section, README, HF mirrors",
|
| 379 |
"exists": true,
|
| 380 |
-
"bytes":
|
| 381 |
-
"sha256": "
|
| 382 |
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|
| 383 |
"format": "SVG",
|
| 384 |
-
"width":
|
| 385 |
-
"height":
|
| 386 |
-
"view_box": "0 0
|
| 387 |
},
|
| 388 |
"source_script_exists": true
|
| 389 |
},
|
|
@@ -395,13 +395,13 @@
|
|
| 395 |
"source_script": "scripts/build_unified_task_model_radar.py",
|
| 396 |
"surface": "website unified task section, README, HF mirrors",
|
| 397 |
"exists": true,
|
| 398 |
-
"bytes":
|
| 399 |
-
"sha256": "
|
| 400 |
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|
| 401 |
"format": "SVG",
|
| 402 |
-
"width":
|
| 403 |
-
"height":
|
| 404 |
-
"view_box": "0 0
|
| 405 |
},
|
| 406 |
"source_script_exists": true
|
| 407 |
},
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Figure Index",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T11:33:21+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": 26,
|
| 7 |
"figures": [
|
|
|
|
| 359 |
"source_script": "scripts/build_unified_task_model_radar.py",
|
| 360 |
"surface": "website unified task section, README, HF mirrors",
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| 361 |
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|
| 362 |
+
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|
| 363 |
+
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| 364 |
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| 365 |
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| 366 |
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|
| 367 |
+
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|
| 368 |
+
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|
| 369 |
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|
| 370 |
"source_script_exists": true
|
| 371 |
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|
|
|
|
| 377 |
"source_script": "scripts/build_unified_task_model_radar.py",
|
| 378 |
"surface": "website unified task section, README, HF mirrors",
|
| 379 |
"exists": true,
|
| 380 |
+
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|
| 381 |
+
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|
| 382 |
"dimensions": {
|
| 383 |
"format": "SVG",
|
| 384 |
+
"width": 2400,
|
| 385 |
+
"height": 1840,
|
| 386 |
+
"view_box": "0 0 2400 1840"
|
| 387 |
},
|
| 388 |
"source_script_exists": true
|
| 389 |
},
|
|
|
|
| 395 |
"source_script": "scripts/build_unified_task_model_radar.py",
|
| 396 |
"surface": "website unified task section, README, HF mirrors",
|
| 397 |
"exists": true,
|
| 398 |
+
"bytes": 43020,
|
| 399 |
+
"sha256": "fad2d354e09ece917350dbbb66a65a4dcfabc38e000da61b002315c67b6aefa9",
|
| 400 |
"dimensions": {
|
| 401 |
"format": "SVG",
|
| 402 |
+
"width": 2400,
|
| 403 |
+
"height": 1840,
|
| 404 |
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"view_box": "0 0 2400 1840"
|
| 405 |
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|
| 406 |
"source_script_exists": true
|
| 407 |
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docs/data/mirror_parity.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-16T11:
|
| 4 |
"hf_root": "hf_publish",
|
| 5 |
"summary": {
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| 6 |
"group_count": 571,
|
|
@@ -139,44 +139,44 @@
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|
| 139 |
"path": "repo:docs/data/artifact_index.json",
|
| 140 |
"exists": true,
|
| 141 |
"bytes": 99966,
|
| 142 |
-
"sha256": "
|
| 143 |
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|
| 144 |
"mirrors": {
|
| 145 |
"hf_space": {
|
| 146 |
"path": "hf_space:data/artifact_index.json",
|
| 147 |
"exists": true,
|
| 148 |
"bytes": 99966,
|
| 149 |
-
"sha256": "
|
| 150 |
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|
| 151 |
"hf_artifacts_data": {
|
| 152 |
"path": "hf_artifacts:data/artifact_index.json",
|
| 153 |
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|
| 154 |
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|
| 155 |
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|
| 156 |
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|
| 157 |
"hf_artifacts": {
|
| 158 |
"path": "hf_artifacts:docs/data/artifact_index.json",
|
| 159 |
"exists": true,
|
| 160 |
"bytes": 99966,
|
| 161 |
-
"sha256": "
|
| 162 |
},
|
| 163 |
"hf_model_data": {
|
| 164 |
"path": "hf_model:data/artifact_index.json",
|
| 165 |
"exists": true,
|
| 166 |
"bytes": 99966,
|
| 167 |
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|
| 168 |
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|
| 169 |
"hf_model_docs_data": {
|
| 170 |
"path": "hf_model:docs/data/artifact_index.json",
|
| 171 |
"exists": true,
|
| 172 |
"bytes": 99966,
|
| 173 |
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"sha256": "
|
| 174 |
},
|
| 175 |
"hf_model": {
|
| 176 |
"path": "hf_model:metrics/artifact_index.json",
|
| 177 |
"exists": true,
|
| 178 |
"bytes": 99966,
|
| 179 |
-
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|
| 180 |
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|
| 181 |
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| 182 |
"failures": []
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|
@@ -335,44 +335,44 @@
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|
| 335 |
"path": "repo:docs/data/figure_index.json",
|
| 336 |
"exists": true,
|
| 337 |
"bytes": 17287,
|
| 338 |
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|
| 339 |
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|
| 340 |
"mirrors": {
|
| 341 |
"hf_space": {
|
| 342 |
"path": "hf_space:data/figure_index.json",
|
| 343 |
"exists": true,
|
| 344 |
"bytes": 17287,
|
| 345 |
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|
| 346 |
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|
| 347 |
"hf_artifacts_data": {
|
| 348 |
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| 349 |
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|
| 350 |
"bytes": 17287,
|
| 351 |
-
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|
| 352 |
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|
| 353 |
"hf_artifacts": {
|
| 354 |
"path": "hf_artifacts:docs/data/figure_index.json",
|
| 355 |
"exists": true,
|
| 356 |
"bytes": 17287,
|
| 357 |
-
"sha256": "
|
| 358 |
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|
| 359 |
"hf_model_data": {
|
| 360 |
"path": "hf_model:data/figure_index.json",
|
| 361 |
"exists": true,
|
| 362 |
"bytes": 17287,
|
| 363 |
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| 364 |
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| 365 |
"hf_model_docs_data": {
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| 366 |
"path": "hf_model:docs/data/figure_index.json",
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| 367 |
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| 368 |
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|
| 369 |
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|
| 370 |
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|
| 371 |
"hf_model": {
|
| 372 |
"path": "hf_model:metrics/figure_index.json",
|
| 373 |
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| 374 |
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|
| 375 |
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|
| 376 |
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| 377 |
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| 378 |
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|
@@ -824,45 +824,45 @@
|
|
| 824 |
"local": {
|
| 825 |
"path": "repo:docs/data/publication_audit.json",
|
| 826 |
"exists": true,
|
| 827 |
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| 828 |
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|
| 829 |
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| 830 |
"mirrors": {
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| 831 |
"hf_space": {
|
| 832 |
"path": "hf_space:data/publication_audit.json",
|
| 833 |
"exists": true,
|
| 834 |
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| 835 |
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|
| 836 |
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| 837 |
"hf_artifacts_data": {
|
| 838 |
"path": "hf_artifacts:data/publication_audit.json",
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| 839 |
"exists": true,
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| 840 |
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| 841 |
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| 842 |
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|
| 843 |
"hf_artifacts": {
|
| 844 |
"path": "hf_artifacts:docs/data/publication_audit.json",
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| 845 |
"exists": true,
|
| 846 |
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| 847 |
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|
| 848 |
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|
| 849 |
"hf_model_data": {
|
| 850 |
"path": "hf_model:data/publication_audit.json",
|
| 851 |
"exists": true,
|
| 852 |
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| 853 |
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|
| 854 |
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| 855 |
"hf_model_docs_data": {
|
| 856 |
"path": "hf_model:docs/data/publication_audit.json",
|
| 857 |
"exists": true,
|
| 858 |
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| 859 |
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|
| 860 |
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|
| 861 |
"hf_model": {
|
| 862 |
"path": "hf_model:metrics/publication_audit.json",
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| 863 |
"exists": true,
|
| 864 |
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| 865 |
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|
| 866 |
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|
| 867 |
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| 868 |
"failures": []
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|
@@ -873,45 +873,45 @@
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|
| 873 |
"local": {
|
| 874 |
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|
| 875 |
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|
| 876 |
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| 877 |
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|
| 878 |
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| 879 |
"mirrors": {
|
| 880 |
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|
| 881 |
"path": "hf_space:data/public_surface_qa.json",
|
| 882 |
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|
| 883 |
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| 884 |
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|
| 885 |
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| 886 |
"hf_artifacts_data": {
|
| 887 |
"path": "hf_artifacts:data/public_surface_qa.json",
|
| 888 |
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|
| 889 |
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|
| 890 |
-
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|
| 891 |
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|
| 892 |
"hf_artifacts": {
|
| 893 |
"path": "hf_artifacts:docs/data/public_surface_qa.json",
|
| 894 |
"exists": true,
|
| 895 |
-
"bytes":
|
| 896 |
-
"sha256": "
|
| 897 |
},
|
| 898 |
"hf_model_data": {
|
| 899 |
"path": "hf_model:data/public_surface_qa.json",
|
| 900 |
"exists": true,
|
| 901 |
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| 902 |
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|
| 903 |
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|
| 904 |
"hf_model_docs_data": {
|
| 905 |
"path": "hf_model:docs/data/public_surface_qa.json",
|
| 906 |
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|
| 907 |
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| 908 |
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|
| 909 |
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|
| 910 |
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| 911 |
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| 912 |
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| 913 |
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| 914 |
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| 915 |
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| 916 |
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| 917 |
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|
@@ -1021,44 +1021,44 @@
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|
| 1021 |
"path": "repo:docs/data/quality_gates.json",
|
| 1022 |
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|
| 1023 |
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|
| 1024 |
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| 1025 |
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| 1026 |
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| 1027 |
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|
| 1028 |
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| 1029 |
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| 1030 |
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|
| 1031 |
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| 1032 |
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| 1033 |
"hf_artifacts_data": {
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| 1034 |
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| 1035 |
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| 1036 |
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| 1037 |
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| 1038 |
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| 1039 |
"hf_artifacts": {
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| 1040 |
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| 1041 |
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| 1042 |
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| 1043 |
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|
| 1044 |
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| 1045 |
"hf_model_data": {
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| 1046 |
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| 1047 |
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| 1048 |
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|
| 1049 |
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| 1050 |
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| 1051 |
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| 1052 |
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| 1054 |
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| 1056 |
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| 1057 |
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| 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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|
@@ -1462,44 +1462,44 @@
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| 1462 |
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| 1463 |
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| 1464 |
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| 1466 |
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| 1467 |
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| 1468 |
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| 1469 |
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| 1470 |
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|
| 1472 |
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| 1473 |
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| 1474 |
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| 1475 |
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| 1476 |
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| 1477 |
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| 1478 |
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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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|
| 1485 |
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| 1486 |
"hf_model_data": {
|
| 1487 |
"path": "hf_model:data/scope_claims_audit.json",
|
| 1488 |
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|
| 1489 |
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|
| 1490 |
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| 1491 |
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| 1492 |
"hf_model_docs_data": {
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| 1493 |
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| 1494 |
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| 1495 |
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| 1496 |
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| 1497 |
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| 1498 |
"hf_model": {
|
| 1499 |
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|
| 1500 |
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|
| 1501 |
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| 1502 |
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| 1503 |
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| 1504 |
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| 1505 |
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|
@@ -1560,44 +1560,44 @@
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| 1560 |
"path": "repo:docs/data/source_alignment_audit.json",
|
| 1561 |
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| 1564 |
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"mirrors": {
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| 1567 |
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| 1568 |
"exists": true,
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| 1569 |
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|
| 1570 |
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| 1571 |
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| 1572 |
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| 1573 |
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| 1574 |
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| 1577 |
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| 1578 |
"hf_artifacts": {
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| 1579 |
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| 1580 |
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| 1581 |
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|
| 1582 |
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| 1583 |
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| 1584 |
"hf_model_data": {
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| 1585 |
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| 1586 |
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| 1587 |
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| 1588 |
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|
| 1589 |
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| 1590 |
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| 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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|
@@ -1658,44 +1658,44 @@
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|
| 1658 |
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| 1659 |
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| 1660 |
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| 1662 |
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| 1663 |
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| 1664 |
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| 1665 |
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| 1666 |
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| 1667 |
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| 1668 |
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| 1669 |
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| 1670 |
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| 1671 |
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| 1672 |
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| 1673 |
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| 1674 |
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| 1675 |
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| 1676 |
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| 1677 |
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| 1678 |
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| 1679 |
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|
| 1680 |
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| 1681 |
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| 1682 |
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"format": "SVG",
|
| 384 |
+
"width": 2400,
|
| 385 |
+
"height": 1840,
|
| 386 |
+
"view_box": "0 0 2400 1840"
|
| 387 |
},
|
| 388 |
"source_script_exists": true
|
| 389 |
},
|
|
|
|
| 395 |
"source_script": "scripts/build_unified_task_model_radar.py",
|
| 396 |
"surface": "website unified task section, README, HF mirrors",
|
| 397 |
"exists": true,
|
| 398 |
+
"bytes": 43020,
|
| 399 |
+
"sha256": "fad2d354e09ece917350dbbb66a65a4dcfabc38e000da61b002315c67b6aefa9",
|
| 400 |
"dimensions": {
|
| 401 |
"format": "SVG",
|
| 402 |
+
"width": 2400,
|
| 403 |
+
"height": 1840,
|
| 404 |
+
"view_box": "0 0 2400 1840"
|
| 405 |
},
|
| 406 |
"source_script_exists": true
|
| 407 |
},
|
metrics/mirror_parity.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-16T11:
|
| 4 |
"hf_root": "hf_publish",
|
| 5 |
"summary": {
|
| 6 |
"group_count": 571,
|
|
@@ -139,44 +139,44 @@
|
|
| 139 |
"path": "repo:docs/data/artifact_index.json",
|
| 140 |
"exists": true,
|
| 141 |
"bytes": 99966,
|
| 142 |
-
"sha256": "
|
| 143 |
},
|
| 144 |
"mirrors": {
|
| 145 |
"hf_space": {
|
| 146 |
"path": "hf_space:data/artifact_index.json",
|
| 147 |
"exists": true,
|
| 148 |
"bytes": 99966,
|
| 149 |
-
"sha256": "
|
| 150 |
},
|
| 151 |
"hf_artifacts_data": {
|
| 152 |
"path": "hf_artifacts:data/artifact_index.json",
|
| 153 |
"exists": true,
|
| 154 |
"bytes": 99966,
|
| 155 |
-
"sha256": "
|
| 156 |
},
|
| 157 |
"hf_artifacts": {
|
| 158 |
"path": "hf_artifacts:docs/data/artifact_index.json",
|
| 159 |
"exists": true,
|
| 160 |
"bytes": 99966,
|
| 161 |
-
"sha256": "
|
| 162 |
},
|
| 163 |
"hf_model_data": {
|
| 164 |
"path": "hf_model:data/artifact_index.json",
|
| 165 |
"exists": true,
|
| 166 |
"bytes": 99966,
|
| 167 |
-
"sha256": "
|
| 168 |
},
|
| 169 |
"hf_model_docs_data": {
|
| 170 |
"path": "hf_model:docs/data/artifact_index.json",
|
| 171 |
"exists": true,
|
| 172 |
"bytes": 99966,
|
| 173 |
-
"sha256": "
|
| 174 |
},
|
| 175 |
"hf_model": {
|
| 176 |
"path": "hf_model:metrics/artifact_index.json",
|
| 177 |
"exists": true,
|
| 178 |
"bytes": 99966,
|
| 179 |
-
"sha256": "
|
| 180 |
}
|
| 181 |
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|
| 182 |
"failures": []
|
|
@@ -335,44 +335,44 @@
|
|
| 335 |
"path": "repo:docs/data/figure_index.json",
|
| 336 |
"exists": true,
|
| 337 |
"bytes": 17287,
|
| 338 |
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|
| 339 |
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|
| 340 |
"mirrors": {
|
| 341 |
"hf_space": {
|
| 342 |
"path": "hf_space:data/figure_index.json",
|
| 343 |
"exists": true,
|
| 344 |
"bytes": 17287,
|
| 345 |
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|
| 346 |
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|
| 347 |
"hf_artifacts_data": {
|
| 348 |
"path": "hf_artifacts:data/figure_index.json",
|
| 349 |
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|
| 350 |
"bytes": 17287,
|
| 351 |
-
"sha256": "
|
| 352 |
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|
| 353 |
"hf_artifacts": {
|
| 354 |
"path": "hf_artifacts:docs/data/figure_index.json",
|
| 355 |
"exists": true,
|
| 356 |
"bytes": 17287,
|
| 357 |
-
"sha256": "
|
| 358 |
},
|
| 359 |
"hf_model_data": {
|
| 360 |
"path": "hf_model:data/figure_index.json",
|
| 361 |
"exists": true,
|
| 362 |
"bytes": 17287,
|
| 363 |
-
"sha256": "
|
| 364 |
},
|
| 365 |
"hf_model_docs_data": {
|
| 366 |
"path": "hf_model:docs/data/figure_index.json",
|
| 367 |
"exists": true,
|
| 368 |
"bytes": 17287,
|
| 369 |
-
"sha256": "
|
| 370 |
},
|
| 371 |
"hf_model": {
|
| 372 |
"path": "hf_model:metrics/figure_index.json",
|
| 373 |
"exists": true,
|
| 374 |
"bytes": 17287,
|
| 375 |
-
"sha256": "
|
| 376 |
}
|
| 377 |
},
|
| 378 |
"failures": []
|
|
@@ -824,45 +824,45 @@
|
|
| 824 |
"local": {
|
| 825 |
"path": "repo:docs/data/publication_audit.json",
|
| 826 |
"exists": true,
|
| 827 |
-
"bytes":
|
| 828 |
-
"sha256": "
|
| 829 |
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|
| 830 |
"mirrors": {
|
| 831 |
"hf_space": {
|
| 832 |
"path": "hf_space:data/publication_audit.json",
|
| 833 |
"exists": true,
|
| 834 |
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"bytes":
|
| 835 |
-
"sha256": "
|
| 836 |
},
|
| 837 |
"hf_artifacts_data": {
|
| 838 |
"path": "hf_artifacts:data/publication_audit.json",
|
| 839 |
"exists": true,
|
| 840 |
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"bytes":
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| 841 |
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|
| 842 |
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|
| 843 |
"hf_artifacts": {
|
| 844 |
"path": "hf_artifacts:docs/data/publication_audit.json",
|
| 845 |
"exists": true,
|
| 846 |
-
"bytes":
|
| 847 |
-
"sha256": "
|
| 848 |
},
|
| 849 |
"hf_model_data": {
|
| 850 |
"path": "hf_model:data/publication_audit.json",
|
| 851 |
"exists": true,
|
| 852 |
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"bytes":
|
| 853 |
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|
| 854 |
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|
| 855 |
"hf_model_docs_data": {
|
| 856 |
"path": "hf_model:docs/data/publication_audit.json",
|
| 857 |
"exists": true,
|
| 858 |
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"bytes":
|
| 859 |
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"sha256": "
|
| 860 |
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|
| 861 |
"hf_model": {
|
| 862 |
"path": "hf_model:metrics/publication_audit.json",
|
| 863 |
"exists": true,
|
| 864 |
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"bytes":
|
| 865 |
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|
| 866 |
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|
| 867 |
},
|
| 868 |
"failures": []
|
|
@@ -873,45 +873,45 @@
|
|
| 873 |
"local": {
|
| 874 |
"path": "repo:docs/data/public_surface_qa.json",
|
| 875 |
"exists": true,
|
| 876 |
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|
| 877 |
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|
| 878 |
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|
| 879 |
"mirrors": {
|
| 880 |
"hf_space": {
|
| 881 |
"path": "hf_space:data/public_surface_qa.json",
|
| 882 |
"exists": true,
|
| 883 |
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"bytes":
|
| 884 |
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|
| 885 |
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|
| 886 |
"hf_artifacts_data": {
|
| 887 |
"path": "hf_artifacts:data/public_surface_qa.json",
|
| 888 |
"exists": true,
|
| 889 |
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"bytes":
|
| 890 |
-
"sha256": "
|
| 891 |
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|
| 892 |
"hf_artifacts": {
|
| 893 |
"path": "hf_artifacts:docs/data/public_surface_qa.json",
|
| 894 |
"exists": true,
|
| 895 |
-
"bytes":
|
| 896 |
-
"sha256": "
|
| 897 |
},
|
| 898 |
"hf_model_data": {
|
| 899 |
"path": "hf_model:data/public_surface_qa.json",
|
| 900 |
"exists": true,
|
| 901 |
-
"bytes":
|
| 902 |
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"sha256": "
|
| 903 |
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|
| 904 |
"hf_model_docs_data": {
|
| 905 |
"path": "hf_model:docs/data/public_surface_qa.json",
|
| 906 |
"exists": true,
|
| 907 |
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"bytes":
|
| 908 |
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|
| 909 |
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|
| 910 |
"hf_model": {
|
| 911 |
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|
| 912 |
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|
| 913 |
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| 914 |
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| 915 |
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|
| 916 |
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| 917 |
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|
@@ -1021,44 +1021,44 @@
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|
| 1021 |
"path": "repo:docs/data/quality_gates.json",
|
| 1022 |
"exists": true,
|
| 1023 |
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|
| 1024 |
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|
| 1025 |
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| 1026 |
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| 1027 |
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|
| 1028 |
"path": "hf_space:data/quality_gates.json",
|
| 1029 |
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|
| 1030 |
"bytes": 8100,
|
| 1031 |
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|
| 1032 |
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| 1033 |
"hf_artifacts_data": {
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| 1034 |
"path": "hf_artifacts:data/quality_gates.json",
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| 1035 |
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|
| 1036 |
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|
| 1037 |
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|
| 1038 |
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| 1039 |
"hf_artifacts": {
|
| 1040 |
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| 1041 |
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|
| 1042 |
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|
| 1043 |
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|
| 1044 |
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| 1045 |
"hf_model_data": {
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| 1046 |
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| 1047 |
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|
| 1048 |
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|
| 1049 |
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| 1050 |
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| 1051 |
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| 1052 |
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| 1053 |
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| 1054 |
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| 1055 |
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| 1056 |
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| 1057 |
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|
| 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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|
@@ -1462,44 +1462,44 @@
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|
| 1462 |
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|
| 1463 |
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| 1464 |
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| 1467 |
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| 1468 |
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| 1469 |
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| 1470 |
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| 1474 |
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| 1475 |
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| 1476 |
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| 1479 |
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| 1480 |
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| 1481 |
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| 1482 |
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| 1483 |
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| 1484 |
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|
| 1485 |
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| 1486 |
"hf_model_data": {
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| 1487 |
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| 1488 |
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|
| 1489 |
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|
| 1490 |
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| 1491 |
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| 1492 |
"hf_model_docs_data": {
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| 1493 |
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| 1494 |
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| 1495 |
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| 1497 |
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| 1498 |
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| 1499 |
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|
| 1500 |
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|
| 1501 |
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|
| 1502 |
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| 1503 |
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|
| 1504 |
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| 1505 |
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|
@@ -1560,44 +1560,44 @@
|
|
| 1560 |
"path": "repo:docs/data/source_alignment_audit.json",
|
| 1561 |
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|
| 1562 |
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| 1564 |
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| 1565 |
"mirrors": {
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| 1566 |
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| 1567 |
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| 1568 |
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| 1569 |
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|
| 1570 |
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| 1571 |
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| 1572 |
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| 1573 |
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| 1574 |
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|
| 1576 |
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| 1577 |
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| 1578 |
"hf_artifacts": {
|
| 1579 |
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|
| 1580 |
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| 1581 |
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|
| 1582 |
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|
| 1583 |
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| 1584 |
"hf_model_data": {
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| 1585 |
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| 1586 |
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| 1587 |
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| 1588 |
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|
| 1589 |
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| 1590 |
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| 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 |
"bytes": 4432,
|
| 1600 |
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|
| 1601 |
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|
| 1602 |
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| 1603 |
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|
@@ -1658,44 +1658,44 @@
|
|
| 1658 |
"path": "repo:docs/data/single_episode_task_model_radar.json",
|
| 1659 |
"exists": true,
|
| 1660 |
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|
| 1661 |
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| 1662 |
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| 1663 |
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| 1664 |
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|
| 1665 |
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|
| 1666 |
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|
| 1667 |
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|
| 1668 |
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|
| 1669 |
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| 1670 |
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|
| 1671 |
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| 1672 |
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|
| 1673 |
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|
| 1674 |
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| 1675 |
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| 1676 |
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| 1677 |
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| 1678 |
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|
| 1679 |
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|
| 1680 |
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|
| 1681 |
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|
| 1682 |
"hf_model_data": {
|
| 1683 |
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|
| 1684 |
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|
| 1685 |
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|
| 1686 |
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|
| 1687 |
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| 1688 |
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|
| 1689 |
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| 1690 |
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|
| 1691 |
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|
| 1692 |
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|
| 1693 |
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| 1694 |
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| 1695 |
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| 1696 |
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|
| 1697 |
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|
| 1698 |
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|
| 1699 |
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|
| 1700 |
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|
| 1701 |
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|
|
@@ -1707,44 +1707,44 @@
|
|
| 1707 |
"path": "repo:docs/data/episode128_task_model_radar.json",
|
| 1708 |
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|
| 1709 |
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|
| 1710 |
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|
| 1711 |
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| 1712 |
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| 1713 |
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| 1714 |
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| 1715 |
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|
| 1716 |
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|
| 1717 |
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| 1718 |
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| 1719 |
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| 1720 |
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|
| 1723 |
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| 1724 |
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| 1725 |
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| 1727 |
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| 1728 |
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|
| 1729 |
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|
| 1730 |
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| 1731 |
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| 1732 |
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| 1733 |
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| 1734 |
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|
| 1735 |
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|
| 1736 |
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| 1737 |
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| 1738 |
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| 1739 |
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|
| 1740 |
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|
| 1741 |
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|
| 1742 |
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|
| 1743 |
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|
| 1744 |
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|
| 1745 |
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|
| 1746 |
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|
| 1747 |
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|
| 1748 |
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|
| 1749 |
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|
| 1750 |
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|
|
@@ -1854,44 +1854,44 @@
|
|
| 1854 |
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|
| 1855 |
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|
| 1856 |
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| 1858 |
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|
| 4416 |
},
|
| 4417 |
"mirrors": {
|
| 4418 |
"hf_space": {
|
| 4419 |
"path": "hf_space:index.html",
|
| 4420 |
"exists": true,
|
| 4421 |
+
"bytes": 232044,
|
| 4422 |
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"sha256": "3db18256ec8b0326be776974742c5cf84a5d0f53ab606bb27848dcdfc887b433"
|
| 4423 |
},
|
| 4424 |
"hf_artifacts_root": {
|
| 4425 |
"path": "hf_artifacts:index.html",
|
| 4426 |
"exists": true,
|
| 4427 |
+
"bytes": 232044,
|
| 4428 |
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"sha256": "3db18256ec8b0326be776974742c5cf84a5d0f53ab606bb27848dcdfc887b433"
|
| 4429 |
},
|
| 4430 |
"hf_artifacts_docs": {
|
| 4431 |
"path": "hf_artifacts:docs/index.html",
|
| 4432 |
"exists": true,
|
| 4433 |
+
"bytes": 232044,
|
| 4434 |
+
"sha256": "3db18256ec8b0326be776974742c5cf84a5d0f53ab606bb27848dcdfc887b433"
|
| 4435 |
},
|
| 4436 |
"hf_model": {
|
| 4437 |
"path": "hf_model:index.html",
|
| 4438 |
"exists": true,
|
| 4439 |
+
"bytes": 232044,
|
| 4440 |
+
"sha256": "3db18256ec8b0326be776974742c5cf84a5d0f53ab606bb27848dcdfc887b433"
|
| 4441 |
},
|
| 4442 |
"hf_model_docs": {
|
| 4443 |
"path": "hf_model:docs/index.html",
|
| 4444 |
"exists": true,
|
| 4445 |
+
"bytes": 232044,
|
| 4446 |
+
"sha256": "3db18256ec8b0326be776974742c5cf84a5d0f53ab606bb27848dcdfc887b433"
|
| 4447 |
}
|
| 4448 |
},
|
| 4449 |
"failures": []
|
|
|
|
| 18069 |
"path": "repo:FIGURE_INDEX.md",
|
| 18070 |
"exists": true,
|
| 18071 |
"bytes": 6217,
|
| 18072 |
+
"sha256": "5ec54cfb09114042ada7aad54b3c8143b9b305bcd1f8ffd65d9f5116f3f19481"
|
| 18073 |
},
|
| 18074 |
"mirrors": {
|
| 18075 |
"hf_space": {
|
| 18076 |
"path": "hf_space:FIGURE_INDEX.md",
|
| 18077 |
"exists": true,
|
| 18078 |
"bytes": 6217,
|
| 18079 |
+
"sha256": "5ec54cfb09114042ada7aad54b3c8143b9b305bcd1f8ffd65d9f5116f3f19481"
|
| 18080 |
},
|
| 18081 |
"hf_artifacts": {
|
| 18082 |
"path": "hf_artifacts:FIGURE_INDEX.md",
|
| 18083 |
"exists": true,
|
| 18084 |
"bytes": 6217,
|
| 18085 |
+
"sha256": "5ec54cfb09114042ada7aad54b3c8143b9b305bcd1f8ffd65d9f5116f3f19481"
|
| 18086 |
},
|
| 18087 |
"hf_model": {
|
| 18088 |
"path": "hf_model:FIGURE_INDEX.md",
|
| 18089 |
"exists": true,
|
| 18090 |
"bytes": 6217,
|
| 18091 |
+
"sha256": "5ec54cfb09114042ada7aad54b3c8143b9b305bcd1f8ffd65d9f5116f3f19481"
|
| 18092 |
}
|
| 18093 |
},
|
| 18094 |
"failures": []
|
metrics/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": "2026-06-16T11:
|
| 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": "2026-06-16T11:
|
| 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": "2026-06-16T11:
|
| 32 |
},
|
| 33 |
"source_alignment": {
|
| 34 |
"exists": true,
|
| 35 |
"status": "pass",
|
| 36 |
-
"generated_at_utc": "2026-06-16T11:
|
| 37 |
},
|
| 38 |
"scale_up_status": {
|
| 39 |
"exists": true,
|
| 40 |
"status": "pass",
|
| 41 |
-
"generated_at_utc": "2026-06-16T11:
|
| 42 |
},
|
| 43 |
"publication_package": {
|
| 44 |
"exists": true,
|
| 45 |
"status": "pass",
|
| 46 |
-
"generated_at_utc": "2026-06-16T11:
|
| 47 |
},
|
| 48 |
"mirror_parity": {
|
| 49 |
"exists": true,
|
| 50 |
"status": "pass",
|
| 51 |
-
"generated_at_utc": "2026-06-16T11:
|
| 52 |
}
|
| 53 |
},
|
| 54 |
"failures": {}
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Public Project Surface",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T11:33:38+00:00",
|
| 5 |
"scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
|
| 6 |
"checks": [
|
| 7 |
{
|
|
|
|
| 18 |
"website_integrity": {
|
| 19 |
"exists": true,
|
| 20 |
"status": "pass",
|
| 21 |
+
"generated_at_utc": "2026-06-16T11:08:31+00:00"
|
| 22 |
},
|
| 23 |
"rendered_site_check": {
|
| 24 |
"exists": true,
|
|
|
|
| 28 |
"task_surface_integrity": {
|
| 29 |
"exists": true,
|
| 30 |
"status": "pass",
|
| 31 |
+
"generated_at_utc": "2026-06-16T11:08:48+00:00"
|
| 32 |
},
|
| 33 |
"source_alignment": {
|
| 34 |
"exists": true,
|
| 35 |
"status": "pass",
|
| 36 |
+
"generated_at_utc": "2026-06-16T11:08:48+00:00"
|
| 37 |
},
|
| 38 |
"scale_up_status": {
|
| 39 |
"exists": true,
|
| 40 |
"status": "pass",
|
| 41 |
+
"generated_at_utc": "2026-06-16T11:08:50+00:00"
|
| 42 |
},
|
| 43 |
"publication_package": {
|
| 44 |
"exists": true,
|
| 45 |
"status": "pass",
|
| 46 |
+
"generated_at_utc": "2026-06-16T11:08:38+00:00"
|
| 47 |
},
|
| 48 |
"mirror_parity": {
|
| 49 |
"exists": true,
|
| 50 |
"status": "pass",
|
| 51 |
+
"generated_at_utc": "2026-06-16T11:09:07+00:00"
|
| 52 |
}
|
| 53 |
},
|
| 54 |
"failures": {}
|
metrics/publication_audit.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-16T11:
|
| 4 |
"checks": [
|
| 5 |
{
|
| 6 |
"name": "required_publication_assets_present",
|
|
@@ -220,7 +220,7 @@
|
|
| 220 |
"hf_artifact_bundle": {
|
| 221 |
"root": "hf_publish/artifacts",
|
| 222 |
"exists": true,
|
| 223 |
-
"file_count":
|
| 224 |
"text_file_count": 1000,
|
| 225 |
"largest_file": {
|
| 226 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
|
@@ -231,7 +231,7 @@
|
|
| 231 |
"hf_model_bundle": {
|
| 232 |
"root": "hf_publish/model",
|
| 233 |
"exists": true,
|
| 234 |
-
"file_count":
|
| 235 |
"text_file_count": 1159,
|
| 236 |
"largest_file": {
|
| 237 |
"path": "pytorch_model.bin",
|
|
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
+
"generated_at_utc": "2026-06-16T11:34:16+00:00",
|
| 4 |
"checks": [
|
| 5 |
{
|
| 6 |
"name": "required_publication_assets_present",
|
|
|
|
| 220 |
"hf_artifact_bundle": {
|
| 221 |
"root": "hf_publish/artifacts",
|
| 222 |
"exists": true,
|
| 223 |
+
"file_count": 2306,
|
| 224 |
"text_file_count": 1000,
|
| 225 |
"largest_file": {
|
| 226 |
"path": "results/episode_task_suite/modality_reconstruction/predictions.npz",
|
|
|
|
| 231 |
"hf_model_bundle": {
|
| 232 |
"root": "hf_publish/model",
|
| 233 |
"exists": true,
|
| 234 |
+
"file_count": 2737,
|
| 235 |
"text_file_count": 1159,
|
| 236 |
"largest_file": {
|
| 237 |
"path": "pytorch_model.bin",
|
metrics/quality_gates.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Ropedia Xperience-10M Release Checks",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-16T11:
|
| 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": "2026-06-16T11:33:37+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 |
{
|
metrics/scope_claims_audit.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-16T11:
|
| 4 |
"summary": {
|
| 5 |
"qwen3_omni_verified_diagnostic_pilot": true,
|
| 6 |
"dataset_manifest_num_episodes": 119,
|
|
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
+
"generated_at_utc": "2026-06-16T11:33:54+00:00",
|
| 4 |
"summary": {
|
| 5 |
"qwen3_omni_verified_diagnostic_pilot": true,
|
| 6 |
"dataset_manifest_num_episodes": 119,
|
metrics/single_episode_task_model_radar.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Single-Episode 20-Task Radar",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-
|
| 5 |
"description": "Minimal and Neural MLP baselines on the one public sample episode, both scored on all 20 task contracts.",
|
| 6 |
"task_count": 20,
|
| 7 |
"method_count": 2,
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Single-Episode 20-Task Radar",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T11:26:57+00:00",
|
| 5 |
"description": "Minimal and Neural MLP baselines on the one public sample episode, both scored on all 20 task contracts.",
|
| 6 |
"task_count": 20,
|
| 7 |
"method_count": 2,
|
metrics/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": "2026-06-16T11:
|
| 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": "2026-06-16T11:33:38+00:00",
|
| 5 |
"alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
|
| 6 |
"alignment_summary": {
|
| 7 |
"full_dataset_repo": "ropedia-ai/xperience-10m",
|
metrics/task_method_20_result_matrix.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Task Method 20-Result Matrix",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-
|
| 5 |
"task_count": 20,
|
| 6 |
"method_count": 9,
|
| 7 |
"method_task_record_count": 180,
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Task Method 20-Result Matrix",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T11:26:57+00:00",
|
| 5 |
"task_count": 20,
|
| 6 |
"method_count": 9,
|
| 7 |
"method_task_record_count": 180,
|
metrics/task_surface_integrity.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-16T11:
|
| 4 |
"summary": {
|
| 5 |
"task_count": 12,
|
| 6 |
"expected_task_count": 12,
|
|
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
+
"generated_at_utc": "2026-06-16T11:33:38+00:00",
|
| 4 |
"summary": {
|
| 5 |
"task_count": 12,
|
| 6 |
"expected_task_count": 12,
|
metrics/unified_task_model_radar.json
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"title": "Unified 20-Task Model Radar",
|
| 3 |
"status": "pass",
|
| 4 |
-
"generated_at_utc": "2026-06-
|
| 5 |
"task_count": 20,
|
| 6 |
"method_count": 9,
|
| 7 |
"method_task_record_count": 180,
|
|
|
|
| 1 |
{
|
| 2 |
"title": "Unified 20-Task Model Radar",
|
| 3 |
"status": "pass",
|
| 4 |
+
"generated_at_utc": "2026-06-16T11:26:57+00:00",
|
| 5 |
"task_count": 20,
|
| 6 |
"method_count": 9,
|
| 7 |
"method_task_record_count": 180,
|
metrics/website_integrity.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
-
"generated_at_utc": "2026-06-16T11:
|
| 4 |
"docs_root": "docs",
|
| 5 |
"site_base": "/ropedia-xperience-10m-task-suite/",
|
| 6 |
"summary": {
|
|
@@ -391,7 +391,7 @@
|
|
| 391 |
},
|
| 392 |
{
|
| 393 |
"path": "data/publication_audit.json",
|
| 394 |
-
"bytes":
|
| 395 |
"top_level_type": "dict"
|
| 396 |
},
|
| 397 |
{
|
|
@@ -546,7 +546,7 @@
|
|
| 546 |
{
|
| 547 |
"path": "assets/charts/episode128_task_model_radar.svg",
|
| 548 |
"exists": true,
|
| 549 |
-
"bytes":
|
| 550 |
"format": "SVG",
|
| 551 |
"has_viewbox": true
|
| 552 |
},
|
|
@@ -602,7 +602,7 @@
|
|
| 602 |
{
|
| 603 |
"path": "assets/charts/single_episode_task_model_radar.svg",
|
| 604 |
"exists": true,
|
| 605 |
-
"bytes":
|
| 606 |
"format": "SVG",
|
| 607 |
"has_viewbox": true
|
| 608 |
},
|
|
@@ -616,7 +616,7 @@
|
|
| 616 |
{
|
| 617 |
"path": "assets/charts/unified_task_model_radar.svg",
|
| 618 |
"exists": true,
|
| 619 |
-
"bytes":
|
| 620 |
"format": "SVG",
|
| 621 |
"has_viewbox": true
|
| 622 |
},
|
|
|
|
| 1 |
{
|
| 2 |
"status": "pass",
|
| 3 |
+
"generated_at_utc": "2026-06-16T11:33:51+00:00",
|
| 4 |
"docs_root": "docs",
|
| 5 |
"site_base": "/ropedia-xperience-10m-task-suite/",
|
| 6 |
"summary": {
|
|
|
|
| 391 |
},
|
| 392 |
{
|
| 393 |
"path": "data/publication_audit.json",
|
| 394 |
+
"bytes": 8189,
|
| 395 |
"top_level_type": "dict"
|
| 396 |
},
|
| 397 |
{
|
|
|
|
| 546 |
{
|
| 547 |
"path": "assets/charts/episode128_task_model_radar.svg",
|
| 548 |
"exists": true,
|
| 549 |
+
"bytes": 43020,
|
| 550 |
"format": "SVG",
|
| 551 |
"has_viewbox": true
|
| 552 |
},
|
|
|
|
| 602 |
{
|
| 603 |
"path": "assets/charts/single_episode_task_model_radar.svg",
|
| 604 |
"exists": true,
|
| 605 |
+
"bytes": 35229,
|
| 606 |
"format": "SVG",
|
| 607 |
"has_viewbox": true
|
| 608 |
},
|
|
|
|
| 616 |
{
|
| 617 |
"path": "assets/charts/unified_task_model_radar.svg",
|
| 618 |
"exists": true,
|
| 619 |
+
"bytes": 49046,
|
| 620 |
"format": "SVG",
|
| 621 |
"has_viewbox": true
|
| 622 |
},
|
scripts/build_unified_task_model_radar.py
CHANGED
|
@@ -748,8 +748,8 @@ def render_svg(
|
|
| 748 |
chip_specs: list[tuple[str, str]] | None = None,
|
| 749 |
reading_rules: tuple[str, str, str] | None = None,
|
| 750 |
) -> str:
|
| 751 |
-
width, height =
|
| 752 |
-
cx, cy, radius =
|
| 753 |
tasks = payload["tasks"]
|
| 754 |
n = len(tasks)
|
| 755 |
angles = [-math.pi / 2 + 2 * math.pi * i / n for i in range(n)]
|
|
@@ -765,7 +765,7 @@ def render_svg(
|
|
| 765 |
"</defs>",
|
| 766 |
'<rect width="100%" height="100%" fill="#020502"/>',
|
| 767 |
'<rect width="100%" height="100%" fill="url(#dots)" opacity="0.45"/>',
|
| 768 |
-
'<rect x="28" y="28" width="
|
| 769 |
svg_text(70, 86, title or payload.get("title", "20-Task Model Radar"), size=36, weight=800),
|
| 770 |
svg_text(
|
| 771 |
70,
|
|
@@ -801,7 +801,7 @@ def render_svg(
|
|
| 801 |
parts.append(svg_text(chip_x + 16, 197, label, size=13, fill=color, weight=760))
|
| 802 |
chip_x += chip_w + 12
|
| 803 |
|
| 804 |
-
parts.append('<rect x="54" y="235" width="
|
| 805 |
parts.append(svg_text(84, 276, "Normalized task scores", size=23, weight=800))
|
| 806 |
parts.append(svg_text(84, 302, "Each axis is one task. Longer radius means better after metric-direction normalization.", size=13, fill="#a5afa2", weight=560))
|
| 807 |
|
|
@@ -815,14 +815,9 @@ def render_svg(
|
|
| 815 |
for task, angle in zip(tasks, angles):
|
| 816 |
x, y = point(cx, cy, radius, angle)
|
| 817 |
parts.append(f'<line x1="{cx:.1f}" y1="{cy:.1f}" x2="{x:.1f}" y2="{y:.1f}" stroke="#ccffa0" stroke-opacity="0.12" stroke-width="1"/>')
|
| 818 |
-
lx, ly = point(cx, cy, radius +
|
| 819 |
-
|
| 820 |
-
|
| 821 |
-
anchor = "start"
|
| 822 |
-
elif math.cos(angle) < -0.25:
|
| 823 |
-
anchor = "end"
|
| 824 |
-
parts.append(svg_text(lx, ly - 7, f"{task['task_number']:02d}", size=12, fill="#ccffa0", anchor=anchor, weight=800, opacity=0.95))
|
| 825 |
-
parts.append(svg_text(lx, ly + 14, task["short_label"], size=12, fill="#dce8d7", anchor=anchor, weight=700))
|
| 826 |
|
| 827 |
for series_id in series_ids:
|
| 828 |
if series_id not in polygon_series_set:
|
|
@@ -851,8 +846,8 @@ def render_svg(
|
|
| 851 |
f'stroke="#020502" stroke-width="2.0"/>'
|
| 852 |
)
|
| 853 |
|
| 854 |
-
legend_x, legend_y =
|
| 855 |
-
parts.append(f'<rect x="{legend_x - 30}" y="{legend_y - 38}" width="
|
| 856 |
parts.append(svg_text(legend_x, legend_y, "Methods compared", size=25, weight=800))
|
| 857 |
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))
|
| 858 |
|
|
@@ -863,39 +858,39 @@ def render_svg(
|
|
| 863 |
if record["id"] not in polygon_series_set:
|
| 864 |
parts.append(f'<circle cx="{legend_x + 25}" cy="{cursor - 7}" r="7" fill="{color}" stroke="#020502" stroke-width="2"/>')
|
| 865 |
parts.append(svg_text(legend_x + 66, cursor - 12, record["label"], size=15, weight=800))
|
| 866 |
-
parts.append(svg_text(legend_x +
|
| 867 |
-
detail_lines = split_text(METHOD_DETAILS.get(record["id"], record["scope"]),
|
| 868 |
parts.extend(svg_text_lines(legend_x + 66, cursor + 8, detail_lines, size=11, fill="#a5afa2", weight=560, line_height=15))
|
| 869 |
cursor += 50
|
| 870 |
|
| 871 |
-
key_x, key_y =
|
| 872 |
-
parts.append(f'<rect x="{key_x - 30}" y="{key_y - 44}" width="
|
| 873 |
parts.append(svg_text(key_x, key_y, "Task axis key", size=25, weight=800))
|
| 874 |
parts.append(svg_text(key_x, key_y + 30, "Full task names are listed here so the polygon remains readable at homepage scale.", size=13, fill="#a5afa2", weight=560))
|
| 875 |
for idx, task in enumerate(tasks):
|
| 876 |
col = 0 if idx < 10 else 1
|
| 877 |
row = idx if idx < 10 else idx - 10
|
| 878 |
-
x0 = key_x + col *
|
| 879 |
-
y0 = key_y + 74 + row *
|
| 880 |
proxy = task["task_id"] in PROXY_TASK_IDS
|
| 881 |
badge_fill = "#f472b6" if proxy else "#ccffa0"
|
| 882 |
parts.append(f'<rect x="{x0}" y="{y0 - 16}" width="36" height="26" rx="6" fill="{badge_fill}" fill-opacity="0.14" stroke="{badge_fill}" stroke-opacity="0.40"/>')
|
| 883 |
parts.append(svg_text(x0 + 18, y0 + 2, f"{task['task_number']:02d}", size=11, fill=badge_fill, anchor="middle", weight=800))
|
| 884 |
-
name_lines = split_text(str(task["label"]),
|
| 885 |
parts.extend(svg_text_lines(x0 + 48, y0 - 3, name_lines, size=12, fill="#f4f8ef", weight=760, line_height=14))
|
| 886 |
metric_label = f"{task.get('metric_name') or task.get('metric_key')} / {'lower better' if task.get('metric_direction') == 'lower' else 'higher better'}"
|
| 887 |
if proxy:
|
| 888 |
metric_label += " / raw128 proxy"
|
| 889 |
parts.append(svg_text(x0 + 48, y0 + 29, metric_label, size=10, fill="#a5afa2", weight=560))
|
| 890 |
|
| 891 |
-
table_y =
|
| 892 |
if reading_rules is None:
|
| 893 |
reading_rules = (
|
| 894 |
"Every method has 20 task records; radius appears only where a numeric task score exists.",
|
| 895 |
"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.",
|
| 896 |
"Scoreless metadata/Qwen/Cosmos records are explicit unsupported or not-evaluated cells in docs/data/task_method_20_result_matrix.json.",
|
| 897 |
)
|
| 898 |
-
parts.append(f'<rect x="70" y="{table_y - 38}" width="
|
| 899 |
parts.append(svg_text(100, table_y - 10, "Reading rules", size=16, fill="#ccffa0", weight=800))
|
| 900 |
parts.append(svg_text(220, table_y - 10, reading_rules[0], size=14, fill="#dce8d7", weight=650))
|
| 901 |
parts.append(svg_text(220, table_y + 18, reading_rules[1], size=13, fill="#a5afa2", weight=560))
|
|
|
|
| 748 |
chip_specs: list[tuple[str, str]] | None = None,
|
| 749 |
reading_rules: tuple[str, str, str] | None = None,
|
| 750 |
) -> str:
|
| 751 |
+
width, height = 2400, 1840
|
| 752 |
+
cx, cy, radius = 650, 860, 355
|
| 753 |
tasks = payload["tasks"]
|
| 754 |
n = len(tasks)
|
| 755 |
angles = [-math.pi / 2 + 2 * math.pi * i / n for i in range(n)]
|
|
|
|
| 765 |
"</defs>",
|
| 766 |
'<rect width="100%" height="100%" fill="#020502"/>',
|
| 767 |
'<rect width="100%" height="100%" fill="url(#dots)" opacity="0.45"/>',
|
| 768 |
+
'<rect x="28" y="28" width="2344" height="1784" rx="18" fill="#061006" fill-opacity="0.88" stroke="#ccffa0" stroke-opacity="0.22"/>',
|
| 769 |
svg_text(70, 86, title or payload.get("title", "20-Task Model Radar"), size=36, weight=800),
|
| 770 |
svg_text(
|
| 771 |
70,
|
|
|
|
| 801 |
parts.append(svg_text(chip_x + 16, 197, label, size=13, fill=color, weight=760))
|
| 802 |
chip_x += chip_w + 12
|
| 803 |
|
| 804 |
+
parts.append('<rect x="54" y="235" width="1190" height="1190" rx="14" fill="#020502" fill-opacity="0.42" stroke="#ccffa0" stroke-opacity="0.14"/>')
|
| 805 |
parts.append(svg_text(84, 276, "Normalized task scores", size=23, weight=800))
|
| 806 |
parts.append(svg_text(84, 302, "Each axis is one task. Longer radius means better after metric-direction normalization.", size=13, fill="#a5afa2", weight=560))
|
| 807 |
|
|
|
|
| 815 |
for task, angle in zip(tasks, angles):
|
| 816 |
x, y = point(cx, cy, radius, angle)
|
| 817 |
parts.append(f'<line x1="{cx:.1f}" y1="{cy:.1f}" x2="{x:.1f}" y2="{y:.1f}" stroke="#ccffa0" stroke-opacity="0.12" stroke-width="1"/>')
|
| 818 |
+
lx, ly = point(cx, cy, radius + 82, angle)
|
| 819 |
+
parts.append(f'<circle cx="{lx:.1f}" cy="{ly:.1f}" r="15.5" fill="#ccffa0" fill-opacity="0.12" stroke="#ccffa0" stroke-opacity="0.34"/>')
|
| 820 |
+
parts.append(svg_text(lx, ly + 4, f"{task['task_number']:02d}", size=11, fill="#ccffa0", anchor="middle", weight=800, opacity=0.98))
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 821 |
|
| 822 |
for series_id in series_ids:
|
| 823 |
if series_id not in polygon_series_set:
|
|
|
|
| 846 |
f'stroke="#020502" stroke-width="2.0"/>'
|
| 847 |
)
|
| 848 |
|
| 849 |
+
legend_x, legend_y = 1315, 178
|
| 850 |
+
parts.append(f'<rect x="{legend_x - 30}" y="{legend_y - 38}" width="1000" height="560" rx="14" fill="#020502" fill-opacity="0.58" stroke="#ccffa0" stroke-opacity="0.20"/>')
|
| 851 |
parts.append(svg_text(legend_x, legend_y, "Methods compared", size=25, weight=800))
|
| 852 |
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))
|
| 853 |
|
|
|
|
| 858 |
if record["id"] not in polygon_series_set:
|
| 859 |
parts.append(f'<circle cx="{legend_x + 25}" cy="{cursor - 7}" r="7" fill="{color}" stroke="#020502" stroke-width="2"/>')
|
| 860 |
parts.append(svg_text(legend_x + 66, cursor - 12, record["label"], size=15, weight=800))
|
| 861 |
+
parts.append(svg_text(legend_x + 392, cursor - 12, f"20 records / {record['scored_task_count']} scored", size=13, fill=color, weight=800))
|
| 862 |
+
detail_lines = split_text(METHOD_DETAILS.get(record["id"], record["scope"]), 78)[:2]
|
| 863 |
parts.extend(svg_text_lines(legend_x + 66, cursor + 8, detail_lines, size=11, fill="#a5afa2", weight=560, line_height=15))
|
| 864 |
cursor += 50
|
| 865 |
|
| 866 |
+
key_x, key_y = 1315, 780
|
| 867 |
+
parts.append(f'<rect x="{key_x - 30}" y="{key_y - 44}" width="1000" height="680" rx="14" fill="#020502" fill-opacity="0.58" stroke="#ccffa0" stroke-opacity="0.20"/>')
|
| 868 |
parts.append(svg_text(key_x, key_y, "Task axis key", size=25, weight=800))
|
| 869 |
parts.append(svg_text(key_x, key_y + 30, "Full task names are listed here so the polygon remains readable at homepage scale.", size=13, fill="#a5afa2", weight=560))
|
| 870 |
for idx, task in enumerate(tasks):
|
| 871 |
col = 0 if idx < 10 else 1
|
| 872 |
row = idx if idx < 10 else idx - 10
|
| 873 |
+
x0 = key_x + col * 500
|
| 874 |
+
y0 = key_y + 74 + row * 54
|
| 875 |
proxy = task["task_id"] in PROXY_TASK_IDS
|
| 876 |
badge_fill = "#f472b6" if proxy else "#ccffa0"
|
| 877 |
parts.append(f'<rect x="{x0}" y="{y0 - 16}" width="36" height="26" rx="6" fill="{badge_fill}" fill-opacity="0.14" stroke="{badge_fill}" stroke-opacity="0.40"/>')
|
| 878 |
parts.append(svg_text(x0 + 18, y0 + 2, f"{task['task_number']:02d}", size=11, fill=badge_fill, anchor="middle", weight=800))
|
| 879 |
+
name_lines = split_text(str(task["label"]), 42)[:2]
|
| 880 |
parts.extend(svg_text_lines(x0 + 48, y0 - 3, name_lines, size=12, fill="#f4f8ef", weight=760, line_height=14))
|
| 881 |
metric_label = f"{task.get('metric_name') or task.get('metric_key')} / {'lower better' if task.get('metric_direction') == 'lower' else 'higher better'}"
|
| 882 |
if proxy:
|
| 883 |
metric_label += " / raw128 proxy"
|
| 884 |
parts.append(svg_text(x0 + 48, y0 + 29, metric_label, size=10, fill="#a5afa2", weight=560))
|
| 885 |
|
| 886 |
+
table_y = 1680
|
| 887 |
if reading_rules is None:
|
| 888 |
reading_rules = (
|
| 889 |
"Every method has 20 task records; radius appears only where a numeric task score exists.",
|
| 890 |
"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.",
|
| 891 |
"Scoreless metadata/Qwen/Cosmos records are explicit unsupported or not-evaluated cells in docs/data/task_method_20_result_matrix.json.",
|
| 892 |
)
|
| 893 |
+
parts.append(f'<rect x="70" y="{table_y - 38}" width="2260" height="120" rx="12" fill="#020502" fill-opacity="0.58" stroke="#ccffa0" stroke-opacity="0.16"/>')
|
| 894 |
parts.append(svg_text(100, table_y - 10, "Reading rules", size=16, fill="#ccffa0", weight=800))
|
| 895 |
parts.append(svg_text(220, table_y - 10, reading_rules[0], size=14, fill="#dce8d7", weight=650))
|
| 896 |
parts.append(svg_text(220, table_y + 18, reading_rules[1], size=13, fill="#a5afa2", weight=560))
|