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ropedia-xperience-10m-task-suite-artifacts

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qwen3-omni
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  1. ARTIFACT_GUIDE.md +3 -1
  2. PUBLIC_SURFACE_QA.md +2 -2
  3. README.md +4 -3
  4. data/artifact_index.json +9 -9
  5. data/live_publication_status.json +486 -351
  6. data/mirror_parity.json +189 -117
  7. data/public_surface_qa.json +17 -11
  8. data/publication_audit.json +1 -1
  9. data/scope_claims_audit.json +1 -1
  10. data/source_alignment_audit.json +1 -1
  11. data/task_surface_integrity.json +145 -145
  12. data/website_integrity.json +8 -8
  13. docs/data/artifact_index.json +9 -9
  14. docs/data/live_publication_status.json +486 -351
  15. docs/data/mirror_parity.json +189 -117
  16. docs/data/public_surface_qa.json +17 -11
  17. docs/data/publication_audit.json +1 -1
  18. docs/data/scope_claims_audit.json +1 -1
  19. docs/data/source_alignment_audit.json +1 -1
  20. docs/data/task_surface_integrity.json +145 -145
  21. docs/data/website_integrity.json +8 -8
  22. docs/index.html +3 -3
  23. index.html +189 -40
  24. research_roadmap.html +6 -8
  25. scripts/sync_hf_publish_mirrors.py +80 -0
  26. scripts/validate_mirror_parity.py +2 -0
  27. single_episode_explorer.html +0 -0
ARTIFACT_GUIDE.md CHANGED
@@ -110,7 +110,9 @@ research project.
110
  | [`results/omni_finetune/MULTI_EPISODE_ACCESS_STATUS.md`](results/omni_finetune/MULTI_EPISODE_ACCESS_STATUS.md) | Documents the public multi-episode access path, selected 128-episode pilot plan, and data requirements. |
111
  | [`docs/data/omni_finetune_verified_result.json`](docs/data/omni_finetune_verified_result.json) | Compact verified summary for the final selected-episode Qwen3-Omni diagnostic result, including split counts, held-out metrics, quality-target status, and adapter repo. |
112
  | [`results/omni_finetune/verified_public/`](results/omni_finetune/verified_public/) | Public-safe verified held-out result packages. These include metrics, predictions, reports, manifests, training metadata, validation summaries, and audit files, but not raw data or weights. |
113
- | [`results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v3_strict_label_prompt_reuse_lora_eval_test_full/`](results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v3_strict_label_prompt_reuse_lora_eval_test_full/) | Current verified Qwen3-Omni strict-label v3 public package with 448 held-out predictions, 100.00% JSON validity, metrics, reports, training metadata, validation summaries, package audit, and error-analysis tables. |
 
 
114
  | [`results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v2_reuse_full8gpu_lora_eval_test_full/`](results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v2_reuse_full8gpu_lora_eval_test_full/) | Historical Qwen3-Omni v2 strict-JSON package retained for prompt-contract and regression comparison. |
115
  | [`https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep`](https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep) | Public LoRA adapter weight repository for the final 128-episode Qwen3-Omni diagnostic run; raw Xperience-10M data and base Qwen weights remain excluded. |
116
  | [`results/omni_finetune/QWEN3_FULL_PARAMETER_GATES_20260609.md`](results/omni_finetune/QWEN3_FULL_PARAMETER_GATES_20260609.md) | Full-parameter Qwen3-Omni feasibility-gate summary: 1/8/32/64-step guarded 8-GPU runs passed, the opportunistic 128-step run was preempted for Qwen v5 handoff, and no full checkpoints or weights are published. |
 
110
  | [`results/omni_finetune/MULTI_EPISODE_ACCESS_STATUS.md`](results/omni_finetune/MULTI_EPISODE_ACCESS_STATUS.md) | Documents the public multi-episode access path, selected 128-episode pilot plan, and data requirements. |
111
  | [`docs/data/omni_finetune_verified_result.json`](docs/data/omni_finetune_verified_result.json) | Compact verified summary for the final selected-episode Qwen3-Omni diagnostic result, including split counts, held-out metrics, quality-target status, and adapter repo. |
112
  | [`results/omni_finetune/verified_public/`](results/omni_finetune/verified_public/) | Public-safe verified held-out result packages. These include metrics, predictions, reports, manifests, training metadata, validation summaries, and audit files, but not raw data or weights. |
113
+ | [`results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_multiscale_cap96_v6_rank64_lr5e5_full8gpu_lora_eval_test_full/`](results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_multiscale_cap96_v6_rank64_lr5e5_full8gpu_lora_eval_test_full/) | Current verified Qwen3-Omni v6 public package with 4,032 held-out predictions, 99.90% JSON validity, metrics, reports, training metadata, validation summaries, package audit, and v5/v6 comparison support. |
114
+ | [`docs/data/qwen3_v5_v6_comparison.json`](docs/data/qwen3_v5_v6_comparison.json) | Machine-readable comparison showing that v6 improves action macro-F1 and contact accuracy versus v5 while v5 remains stronger on JSON validity, subtask, next-action, transition, and object metrics. |
115
+ | [`results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v3_strict_label_prompt_reuse_lora_eval_test_full/`](results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v3_strict_label_prompt_reuse_lora_eval_test_full/) | Historical Qwen3-Omni strict-label v3 public package retained for prompt-contract and regression comparison. |
116
  | [`results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v2_reuse_full8gpu_lora_eval_test_full/`](results/omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_structured_json_v2_reuse_full8gpu_lora_eval_test_full/) | Historical Qwen3-Omni v2 strict-JSON package retained for prompt-contract and regression comparison. |
117
  | [`https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep`](https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep) | Public LoRA adapter weight repository for the final 128-episode Qwen3-Omni diagnostic run; raw Xperience-10M data and base Qwen weights remain excluded. |
118
  | [`results/omni_finetune/QWEN3_FULL_PARAMETER_GATES_20260609.md`](results/omni_finetune/QWEN3_FULL_PARAMETER_GATES_20260609.md) | Full-parameter Qwen3-Omni feasibility-gate summary: 1/8/32/64-step guarded 8-GPU runs passed, the opportunistic 128-step run was preempted for Qwen v5 handoff, and no full checkpoints or weights are published. |
PUBLIC_SURFACE_QA.md CHANGED
@@ -2,7 +2,7 @@
2
 
3
  This generated report checks whether the public repo, website, and Hugging Face cards read like one cohesive research project.
4
 
5
- Current status: **pass**
6
 
7
  This report covers the public repo, website, Hugging Face cards, and package contents. Multi-episode model metrics are tracked by the training and evaluation reports.
8
 
@@ -11,7 +11,7 @@ This report covers the public repo, website, Hugging Face cards, and package con
11
  | Area | Status | What it covers |
12
  | --- | --- | --- |
13
  | Public files | `pass` | Repo README, website HTML, and three Hugging Face cards should all be present in the publication workspace. |
14
- | Project reports | `pass` | The public project surface depends on the existing project reports already passing. |
15
  | Website metadata | `pass` | The website should expose search/social metadata and structured project metadata. |
16
  | Keyboard navigation | `pass` | The long research dashboard should be navigable as real tabs, including keyboard support. |
17
  | Responsive navigation | `pass` | Tablet/mobile navigation should not overflow and deep links should land below sticky navigation. |
 
2
 
3
  This generated report checks whether the public repo, website, and Hugging Face cards read like one cohesive research project.
4
 
5
+ Current status: **fail**
6
 
7
  This report covers the public repo, website, Hugging Face cards, and package contents. Multi-episode model metrics are tracked by the training and evaluation reports.
8
 
 
11
  | Area | Status | What it covers |
12
  | --- | --- | --- |
13
  | Public files | `pass` | Repo README, website HTML, and three Hugging Face cards should all be present in the publication workspace. |
14
+ | Project reports | `fail` | The public project surface depends on the existing project reports already passing. |
15
  | Website metadata | `pass` | The website should expose search/social metadata and structured project metadata. |
16
  | Keyboard navigation | `pass` | The long research dashboard should be navigable as real tabs, including keyboard support. |
17
  | Responsive navigation | `pass` | Tablet/mobile navigation should not overflow and deep links should land below sticky navigation. |
README.md CHANGED
@@ -35,6 +35,7 @@ Cosmos3-Nano plus Cosmos3-Super diagnostic packages.
35
  | Inspect 128-episode same-split baselines | `results/omni_finetune/multi_episode_128_task_baselines/BASELINE_ALIGNMENT_REPORT.md` |
36
  | Inspect final Qwen3-Omni held-out diagnostic result | `docs/data/omni_finetune_verified_result.json` |
37
  | Compare current versions and model groups | `docs/data/omni_model_comparison.json` |
 
38
 
39
  ## 128-Episode Enhancement Pack
40
 
@@ -78,9 +79,9 @@ This bundle includes derived artifacts such as:
78
  MLP result directories.
79
  - Audio-ablation summaries and generated chart assets.
80
  - Public website JSON and figure manifests.
81
- - A current verified Qwen3-Omni strict-label v3 held-out package for the
82
- selected 96/16/16 episode split, with 100.00% JSON validity and weak
83
- action/subtask quality documented as the next error-analysis target.
84
  - Historical Qwen3-Omni packages, including the earlier v2 strict-JSON
85
  diagnostic, for regression and prompt-contract comparison.
86
  - Verified Cosmos3-Nano future-window compatibility, Cosmos3-Super
 
35
  | Inspect 128-episode same-split baselines | `results/omni_finetune/multi_episode_128_task_baselines/BASELINE_ALIGNMENT_REPORT.md` |
36
  | Inspect final Qwen3-Omni held-out diagnostic result | `docs/data/omni_finetune_verified_result.json` |
37
  | Compare current versions and model groups | `docs/data/omni_model_comparison.json` |
38
+ | Compare Qwen3 v5/v6 diagnostic branches | `docs/data/qwen3_v5_v6_comparison.json` |
39
 
40
  ## 128-Episode Enhancement Pack
41
 
 
79
  MLP result directories.
80
  - Audio-ablation summaries and generated chart assets.
81
  - Public website JSON and figure manifests.
82
+ - The latest verified Qwen3-Omni LoRA v6 diagnostic package for the selected
83
+ 96/16/16 episode split includes 34,269 exported windows, 4,032 held-out test
84
+ predictions, 99.90% JSON validity, and public-safe metrics/predictions.
85
  - Historical Qwen3-Omni packages, including the earlier v2 strict-JSON
86
  diagnostic, for regression and prompt-contract comparison.
87
  - Verified Cosmos3-Nano future-window compatibility, Cosmos3-Super
data/artifact_index.json CHANGED
@@ -1,6 +1,6 @@
1
  {
2
  "title": "Ropedia Xperience-10M Task Suite Artifact Index",
3
- "generated_at_utc": "2026-06-14T05:39:44+00:00",
4
  "status": "pass",
5
  "artifact_count": 164,
6
  "missing": [],
@@ -417,8 +417,8 @@
417
  "surface": "repo_hf",
418
  "shows": "Gives the human-readable map from project scope to data, tasks, platform mirrors, and scale-up status.",
419
  "exists": true,
420
- "bytes": 19019,
421
- "sha256": "b50c681fc3b9e1255d38631c0ebe9d4653a8acb0607b3455f9f827638b9f65e6"
422
  },
423
  {
424
  "id": "official_dataset_card_alignment",
@@ -462,7 +462,7 @@
462
  "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
463
  "exists": true,
464
  "bytes": 4432,
465
- "sha256": "24076a6db867af49f9b82d24b68816a1d2bbb4b31f7031aa89699326cb33539b"
466
  },
467
  {
468
  "id": "source_alignment_validator",
@@ -726,7 +726,7 @@
726
  "shows": "Keeps the repo, website, and Hugging Face cards aligned as one cohesive research project surface.",
727
  "exists": true,
728
  "bytes": 1939,
729
- "sha256": "516ca8e7b67460a6151785bfa186165f37e394ab56114bab05481c878265ffe5"
730
  },
731
  {
732
  "id": "public_surface_qa_json",
@@ -737,7 +737,7 @@
737
  "volatile": true,
738
  "shows": "Machine-readable report for SEO/social metadata, accessible tab semantics, public links, project links, and clear project presentation.",
739
  "exists": true,
740
- "bytes": 5640,
741
  "hash_policy": "existence_and_size_only"
742
  },
743
  {
@@ -818,7 +818,7 @@
818
  "volatile": true,
819
  "shows": "Records the last live GitHub/HF URL verification after upload.",
820
  "exists": true,
821
- "bytes": 97776,
822
  "hash_policy": "existence_and_size_only"
823
  },
824
  {
@@ -898,7 +898,7 @@
898
  "volatile": true,
899
  "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.",
900
  "exists": true,
901
- "bytes": 550970,
902
  "hash_policy": "existence_and_size_only"
903
  },
904
  {
@@ -910,7 +910,7 @@
910
  "volatile": true,
911
  "shows": "Confirms local website links, anchors, JSON data files, and referenced images resolve.",
912
  "exists": true,
913
- "bytes": 15774,
914
  "hash_policy": "existence_and_size_only"
915
  },
916
  {
 
1
  {
2
  "title": "Ropedia Xperience-10M Task Suite Artifact Index",
3
+ "generated_at_utc": "2026-06-15T06:37:25+00:00",
4
  "status": "pass",
5
  "artifact_count": 164,
6
  "missing": [],
 
417
  "surface": "repo_hf",
418
  "shows": "Gives the human-readable map from project scope to data, tasks, platform mirrors, and scale-up status.",
419
  "exists": true,
420
+ "bytes": 19677,
421
+ "sha256": "3a1fc1bcd83432be538bff201f55b2b6051d26cc7230deb380f2c76bca8b2c6d"
422
  },
423
  {
424
  "id": "official_dataset_card_alignment",
 
462
  "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
463
  "exists": true,
464
  "bytes": 4432,
465
+ "sha256": "c54591dc4acfbf6e47f26530572413867b5614ac00ba7ce60dbe312d1d9f4140"
466
  },
467
  {
468
  "id": "source_alignment_validator",
 
726
  "shows": "Keeps the repo, website, and Hugging Face cards aligned as one cohesive research project surface.",
727
  "exists": true,
728
  "bytes": 1939,
729
+ "sha256": "eab0a32e5ed7f9d4956dbaa19339d77155bbeed30304ad082967f57936b57e72"
730
  },
731
  {
732
  "id": "public_surface_qa_json",
 
737
  "volatile": true,
738
  "shows": "Machine-readable report for SEO/social metadata, accessible tab semantics, public links, project links, and clear project presentation.",
739
  "exists": true,
740
+ "bytes": 5776,
741
  "hash_policy": "existence_and_size_only"
742
  },
743
  {
 
818
  "volatile": true,
819
  "shows": "Records the last live GitHub/HF URL verification after upload.",
820
  "exists": true,
821
+ "bytes": 102961,
822
  "hash_policy": "existence_and_size_only"
823
  },
824
  {
 
898
  "volatile": true,
899
  "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.",
900
  "exists": true,
901
+ "bytes": 555090,
902
  "hash_policy": "existence_and_size_only"
903
  },
904
  {
 
910
  "volatile": true,
911
  "shows": "Confirms local website links, anchors, JSON data files, and referenced images resolve.",
912
  "exists": true,
913
+ "bytes": 15775,
914
  "hash_policy": "existence_and_size_only"
915
  },
916
  {
data/live_publication_status.json CHANGED
@@ -1,7 +1,7 @@
1
  {
2
  "title": "Ropedia Xperience-10M Live Publication Status",
3
- "status": "pass",
4
- "checked_at_utc": "2026-06-11T04:08:43+00:00",
5
  "scope": "Live GitHub Pages, GitHub raw, Hugging Face Space, artifact dataset, baseline model mirrors, and the Qwen3/Cosmos3 LoRA adapter repos when their upload packages exist locally.",
6
  "hash_groups": [
7
  {
@@ -17,7 +17,7 @@
17
  "mirrors": {
18
  "github_pages": {
19
  "ok": true,
20
- "method": "curl",
21
  "timeout_seconds": 30,
22
  "status_code": 200,
23
  "bytes": 1588641,
@@ -27,17 +27,17 @@
27
  },
28
  "hf_space": {
29
  "ok": true,
30
- "method": "curl",
31
  "timeout_seconds": 30,
32
  "status_code": 200,
33
  "bytes": 1588641,
34
  "sha256": "1275e2adaef920ecde7c29dc62c8d79d4f13475a0c09bc3baa693f47cdec2e1f",
35
- "final_url": "https://cas-bridge.xethub.hf.co/xet-bridge-us/6a19f5db39fe6ce4ebbae226/ce8d198875c2c2d97c9fe3696daf8e27c72a6ce91b628aa6bc7f9a5ebc46d2c2",
36
  "url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/resolve/main/assets/task_suite_infographic.png"
37
  },
38
  "hf_artifacts": {
39
  "ok": true,
40
- "method": "curl",
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  "timeout_seconds": 30,
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  "status_code": 200,
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  "bytes": 1588641,
@@ -47,12 +47,12 @@
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  },
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  "hf_model": {
49
  "ok": true,
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- "method": "curl",
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  "timeout_seconds": 30,
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  "status_code": 200,
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  "bytes": 1588641,
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  "sha256": "1275e2adaef920ecde7c29dc62c8d79d4f13475a0c09bc3baa693f47cdec2e1f",
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- "final_url": "https://cas-bridge.xethub.hf.co/xet-bridge-us/6a19f5dd039cfb1a5d91d8a2/ce8d198875c2c2d97c9fe3696daf8e27c72a6ce91b628aa6bc7f9a5ebc46d2c2",
56
  "url": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines/resolve/main/assets/task_suite_infographic.png"
57
  }
58
  },
@@ -66,47 +66,47 @@
66
  "path": "docs/data/quality_gates.json",
67
  "exists": true,
68
  "bytes": 8097,
69
- "sha256": "53ccc5522df02b2b3658958f3da6ef542a2aa9f85e0bf69cad61ca7a0d254160"
70
  },
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  "mirrors": {
72
  "github_pages": {
73
  "ok": true,
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- "method": "curl",
75
  "timeout_seconds": 30,
76
  "status_code": 200,
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  "bytes": 8097,
78
- "sha256": "53ccc5522df02b2b3658958f3da6ef542a2aa9f85e0bf69cad61ca7a0d254160",
79
  "final_url": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/data/quality_gates.json",
80
  "url": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/data/quality_gates.json"
81
  },
82
  "hf_space": {
83
  "ok": true,
84
- "method": "curl",
85
  "timeout_seconds": 30,
86
  "status_code": 200,
87
  "bytes": 8097,
88
- "sha256": "53ccc5522df02b2b3658958f3da6ef542a2aa9f85e0bf69cad61ca7a0d254160",
89
  "final_url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/raw/main/data/quality_gates.json",
90
  "url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/raw/main/data/quality_gates.json"
91
  },
92
  "hf_artifacts": {
93
  "ok": true,
94
- "method": "curl",
95
  "timeout_seconds": 30,
96
  "status_code": 200,
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  "bytes": 8097,
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- "sha256": "53ccc5522df02b2b3658958f3da6ef542a2aa9f85e0bf69cad61ca7a0d254160",
99
- "final_url": "https://huggingface.co/api/resolve-cache/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts/d78e80dd584565431e2fca8f434207c1196e0ee1/docs%2Fdata%2Fquality_gates.json",
100
  "url": "https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts/resolve/main/docs/data/quality_gates.json"
101
  },
102
  "hf_model": {
103
  "ok": true,
104
- "method": "curl",
105
  "timeout_seconds": 30,
106
  "status_code": 200,
107
  "bytes": 8097,
108
- "sha256": "53ccc5522df02b2b3658958f3da6ef542a2aa9f85e0bf69cad61ca7a0d254160",
109
- "final_url": "https://huggingface.co/api/resolve-cache/models/cy0307/ropedia-xperience-10m-task-baselines/d10ad0148b25637370d587280e52d4e26c38a560/metrics%2Fquality_gates.json",
110
  "url": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines/resolve/main/metrics/quality_gates.json"
111
  }
112
  },
@@ -120,47 +120,47 @@
120
  "path": "docs/data/single_episode_explorer.json",
121
  "exists": true,
122
  "bytes": 4305527,
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- "sha256": "286230d8070150e09595797569a447308a5110241b69edf52e535e3d8a34f827"
124
  },
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  "mirrors": {
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  "github_pages": {
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  "ok": true,
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- "method": "curl",
129
  "timeout_seconds": 30,
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1434
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1458
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1482
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1506
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1693
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- "failures": []
 
 
 
 
 
 
 
1695
  },
1696
  {
1697
  "id": "hf_space_index_current",
1698
  "title": "HF Space index contains current publication markers",
1699
  "url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/raw/main/index.html",
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1709
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1710
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1711
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1712
  "forbidden_markers_present": [],
1713
- "failures": []
 
 
 
 
 
 
 
1714
  },
1715
  {
1716
  "id": "hf_artifacts_card_current",
1717
  "title": "HF artifact card links current result packages",
1718
  "url": "https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts/raw/main/README.md",
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1730
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1731
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1732
- "failures": []
 
 
 
 
 
 
 
 
1733
  },
1734
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1735
  "id": "github_pages_explorer_current",
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1738
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1739
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1766
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1767
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1773
  "id": "hf_model_card_current",
1774
  "title": "HF model card links current result packages",
1775
  "url": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines/raw/main/README.md",
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1788
  "forbidden_markers_present": [],
1789
- "failures": []
 
 
 
 
 
 
 
 
1790
  },
1791
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1792
  "id": "github_pages_mirror_parity_local_path_check",
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1795
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1796
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1803
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1804
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1805
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1833
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1880
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1918
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1937
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1975
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2098
  }
 
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  {
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1834
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2019
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2028
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2230
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2231
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2233
  }
data/mirror_parity.json CHANGED
@@ -1,6 +1,6 @@
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  {
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  "status": "pass",
3
- "generated_at_utc": "2026-06-14T05:50:58+00:00",
4
  "hf_root": "hf_publish",
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  "summary": {
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  "group_count": 369,
@@ -138,45 +138,45 @@
138
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140
  "exists": true,
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- "bytes": 89995,
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143
  },
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  "exists": true,
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- "bytes": 89995,
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- "sha256": "776a52491fb5191faf5cf2cc6bf593a337f049ee3ce13bcba9e155ab33d1598a"
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  {
6
  "name": "required_publication_assets_present",
data/scope_claims_audit.json CHANGED
@@ -1,6 +1,6 @@
1
  {
2
  "status": "pass",
3
- "generated_at_utc": "2026-06-14T05:34:03+00:00",
4
  "summary": {
5
  "qwen3_omni_verified_diagnostic_pilot": true,
6
  "dataset_manifest_num_episodes": 119,
 
1
  {
2
  "status": "pass",
3
+ "generated_at_utc": "2026-06-15T06:37:50+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": "2026-06-14T05:33:57+00:00",
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": "2026-06-15T06:37:44+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_surface_integrity.json CHANGED
@@ -1,6 +1,6 @@
1
  {
2
  "status": "pass",
3
- "generated_at_utc": "2026-06-14T05:33:57+00:00",
4
  "summary": {
5
  "task_count": 12,
6
  "expected_task_count": 12,
@@ -64,33 +64,33 @@
64
  "observed": "timeline_action"
65
  },
66
  {
67
- "name": "timeline_action: public_field_research_name_is_human_readable",
68
  "status": "pass",
69
- "value": "Egocentric Action Recognition",
70
  "raw_hits": []
71
  },
72
  {
73
- "name": "timeline_action: public_field_process_short_is_human_readable",
74
  "status": "pass",
75
- "value": "window features -> action label builder -> classifier",
76
  "raw_hits": []
77
  },
78
  {
79
- "name": "timeline_action: public_field_plain_goal_is_human_readable",
80
  "status": "pass",
81
- "value": "Look at one short multimodal window and name what action is happening now.",
82
  "raw_hits": []
83
  },
84
  {
85
- "name": "timeline_action: public_field_output_short_is_human_readable",
86
  "status": "pass",
87
- "value": "current action class",
88
  "raw_hits": []
89
  },
90
  {
91
- "name": "timeline_action: public_field_input_short_is_human_readable",
92
  "status": "pass",
93
- "value": "20-frame multimodal window",
94
  "raw_hits": []
95
  },
96
  {
@@ -100,9 +100,9 @@
100
  "raw_hits": []
101
  },
102
  {
103
- "name": "timeline_action: public_field_card_blurb_is_human_readable",
104
  "status": "pass",
105
- "value": "Recognize the current manipulation action from synchronized visual, motion, inertial, pose, and annotation context.",
106
  "raw_hits": []
107
  },
108
  {
@@ -184,33 +184,33 @@
184
  "observed": "timeline_subtask"
185
  },
186
  {
187
- "name": "timeline_subtask: public_field_research_name_is_human_readable",
188
  "status": "pass",
189
- "value": "Temporal Subtask Recognition",
190
  "raw_hits": []
191
  },
192
  {
193
- "name": "timeline_subtask: public_field_process_short_is_human_readable",
194
  "status": "pass",
195
- "value": "window features -> subtask label builder -> classifier",
196
  "raw_hits": []
197
  },
198
  {
199
- "name": "timeline_subtask: public_field_plain_goal_is_human_readable",
200
  "status": "pass",
201
- "value": "Predict the higher-level task stage for the current window.",
202
  "raw_hits": []
203
  },
204
  {
205
- "name": "timeline_subtask: public_field_output_short_is_human_readable",
206
  "status": "pass",
207
- "value": "current procedure step",
208
  "raw_hits": []
209
  },
210
  {
211
- "name": "timeline_subtask: public_field_input_short_is_human_readable",
212
  "status": "pass",
213
- "value": "20-frame multimodal window",
214
  "raw_hits": []
215
  },
216
  {
@@ -220,9 +220,9 @@
220
  "raw_hits": []
221
  },
222
  {
223
- "name": "timeline_subtask: public_field_card_blurb_is_human_readable",
224
  "status": "pass",
225
- "value": "Recognize the broader activity stage so fine actions become a readable procedure timeline.",
226
  "raw_hits": []
227
  },
228
  {
@@ -304,33 +304,33 @@
304
  "observed": "transition_detection"
305
  },
306
  {
307
- "name": "transition_detection: public_field_research_name_is_human_readable",
308
  "status": "pass",
309
- "value": "Temporal Action Segmentation",
310
  "raw_hits": []
311
  },
312
  {
313
- "name": "transition_detection: public_field_process_short_is_human_readable",
314
  "status": "pass",
315
- "value": "action changes -> boundary labels -> binary classifier",
316
  "raw_hits": []
317
  },
318
  {
319
- "name": "transition_detection: public_field_plain_goal_is_human_readable",
320
  "status": "pass",
321
- "value": "Detect whether the current window is near a boundary between actions.",
322
  "raw_hits": []
323
  },
324
  {
325
- "name": "transition_detection: public_field_output_short_is_human_readable",
326
  "status": "pass",
327
- "value": "boundary or steady",
328
  "raw_hits": []
329
  },
330
  {
331
- "name": "transition_detection: public_field_input_short_is_human_readable",
332
  "status": "pass",
333
- "value": "current window with boundary target",
334
  "raw_hits": []
335
  },
336
  {
@@ -340,9 +340,9 @@
340
  "raw_hits": []
341
  },
342
  {
343
- "name": "transition_detection: public_field_card_blurb_is_human_readable",
344
  "status": "pass",
345
- "value": "Detect the local moment where the episode changes from one action segment to the next.",
346
  "raw_hits": []
347
  },
348
  {
@@ -422,33 +422,33 @@
422
  "observed": "next_action"
423
  },
424
  {
425
- "name": "next_action: public_field_research_name_is_human_readable",
426
  "status": "pass",
427
- "value": "Short-Horizon Intention Prediction",
428
  "raw_hits": []
429
  },
430
  {
431
- "name": "next_action: public_field_process_short_is_human_readable",
432
  "status": "pass",
433
- "value": "current features -> future label shift -> classifier",
434
  "raw_hits": []
435
  },
436
  {
437
- "name": "next_action: public_field_plain_goal_is_human_readable",
438
  "status": "pass",
439
- "value": "Use the current window to guess the action that will happen shortly after it.",
440
  "raw_hits": []
441
  },
442
  {
443
- "name": "next_action: public_field_output_short_is_human_readable",
444
  "status": "pass",
445
- "value": "action at t+20 frames",
446
  "raw_hits": []
447
  },
448
  {
449
- "name": "next_action: public_field_input_short_is_human_readable",
450
  "status": "pass",
451
- "value": "current window at time t",
452
  "raw_hits": []
453
  },
454
  {
@@ -458,9 +458,9 @@
458
  "raw_hits": []
459
  },
460
  {
461
- "name": "next_action: public_field_card_blurb_is_human_readable",
462
  "status": "pass",
463
- "value": "Forecast the near-future action from the current observations only.",
464
  "raw_hits": []
465
  },
466
  {
@@ -540,33 +540,33 @@
540
  "observed": "hand_trajectory_forecast"
541
  },
542
  {
543
- "name": "hand_trajectory_forecast: public_field_research_name_is_human_readable",
544
  "status": "pass",
545
- "value": "3D Hand Motion Forecasting",
546
  "raw_hits": []
547
  },
548
  {
549
- "name": "hand_trajectory_forecast: public_field_process_short_is_human_readable",
550
  "status": "pass",
551
- "value": "current features -> future mocap target -> regression head",
552
  "raw_hits": []
553
  },
554
  {
555
- "name": "hand_trajectory_forecast: public_field_plain_goal_is_human_readable",
556
  "status": "pass",
557
- "value": "Predict where the hands will move over the next few frames.",
558
  "raw_hits": []
559
  },
560
  {
561
- "name": "hand_trajectory_forecast: public_field_output_short_is_human_readable",
562
  "status": "pass",
563
- "value": "future hand-joint trajectory",
564
  "raw_hits": []
565
  },
566
  {
567
- "name": "hand_trajectory_forecast: public_field_input_short_is_human_readable",
568
  "status": "pass",
569
- "value": "current multimodal window",
570
  "raw_hits": []
571
  },
572
  {
@@ -576,9 +576,9 @@
576
  "raw_hits": []
577
  },
578
  {
579
- "name": "hand_trajectory_forecast: public_field_card_blurb_is_human_readable",
580
  "status": "pass",
581
- "value": "Predict the future 3D left/right hand path from the current multimodal state.",
582
  "raw_hits": []
583
  },
584
  {
@@ -658,33 +658,33 @@
658
  "observed": "contact_prediction"
659
  },
660
  {
661
- "name": "contact_prediction: public_field_research_name_is_human_readable",
662
  "status": "pass",
663
- "value": "Human-Object Contact Prediction",
664
  "raw_hits": []
665
  },
666
  {
667
- "name": "contact_prediction: public_field_process_short_is_human_readable",
668
  "status": "pass",
669
- "value": "feature filter -> contact target -> binary classifier",
670
  "raw_hits": []
671
  },
672
  {
673
- "name": "contact_prediction: public_field_plain_goal_is_human_readable",
674
  "status": "pass",
675
- "value": "Predict whether the body or hand is in contact with something.",
676
  "raw_hits": []
677
  },
678
  {
679
- "name": "contact_prediction: public_field_output_short_is_human_readable",
680
  "status": "pass",
681
- "value": "contact or no contact",
682
  "raw_hits": []
683
  },
684
  {
685
- "name": "contact_prediction: public_field_input_short_is_human_readable",
686
  "status": "pass",
687
- "value": "non-contact, non-caption features",
688
  "raw_hits": []
689
  },
690
  {
@@ -694,9 +694,9 @@
694
  "raw_hits": []
695
  },
696
  {
697
- "name": "contact_prediction: public_field_card_blurb_is_human_readable",
698
  "status": "pass",
699
- "value": "Predict whether body or hand contact with the scene is occurring without leaking contact labels.",
700
  "raw_hits": []
701
  },
702
  {
@@ -774,33 +774,33 @@
774
  "observed": "object_relevance"
775
  },
776
  {
777
- "name": "object_relevance: public_field_research_name_is_human_readable",
778
  "status": "pass",
779
- "value": "Object-Centric Interaction Recognition",
780
  "raw_hits": []
781
  },
782
  {
783
- "name": "object_relevance: public_field_process_short_is_human_readable",
784
  "status": "pass",
785
- "value": "object vocabulary -> multi-hot labels -> sigmoid heads",
786
  "raw_hits": []
787
  },
788
  {
789
- "name": "object_relevance: public_field_plain_goal_is_human_readable",
790
  "status": "pass",
791
- "value": "Predict which objects matter in the current window.",
792
  "raw_hits": []
793
  },
794
  {
795
- "name": "object_relevance: public_field_output_short_is_human_readable",
796
  "status": "pass",
797
- "value": "relevant object set",
798
  "raw_hits": []
799
  },
800
  {
801
- "name": "object_relevance: public_field_input_short_is_human_readable",
802
  "status": "pass",
803
- "value": "non-caption multimodal features",
804
  "raw_hits": []
805
  },
806
  {
@@ -810,9 +810,9 @@
810
  "raw_hits": []
811
  },
812
  {
813
- "name": "object_relevance: public_field_card_blurb_is_human_readable",
814
  "status": "pass",
815
- "value": "Infer which objects are relevant to the current manipulation window from non-caption features.",
816
  "raw_hits": []
817
  },
818
  {
@@ -892,33 +892,33 @@
892
  "observed": "caption_grounding"
893
  },
894
  {
895
- "name": "caption_grounding: public_field_research_name_is_human_readable",
896
  "status": "pass",
897
- "value": "Language-to-Moment Grounding",
898
  "raw_hits": []
899
  },
900
  {
901
- "name": "caption_grounding: public_field_process_short_is_human_readable",
902
  "status": "pass",
903
- "value": "query features -> candidate index -> cosine ranker",
904
  "raw_hits": []
905
  },
906
  {
907
- "name": "caption_grounding: public_field_plain_goal_is_human_readable",
908
  "status": "pass",
909
- "value": "Given a text-like query from annotation, find the matching time window.",
910
  "raw_hits": []
911
  },
912
  {
913
- "name": "caption_grounding: public_field_output_short_is_human_readable",
914
  "status": "pass",
915
- "value": "ranked matching moments",
916
  "raw_hits": []
917
  },
918
  {
919
- "name": "caption_grounding: public_field_input_short_is_human_readable",
920
  "status": "pass",
921
- "value": "text-like query and candidate windows",
922
  "raw_hits": []
923
  },
924
  {
@@ -928,9 +928,9 @@
928
  "raw_hits": []
929
  },
930
  {
931
- "name": "caption_grounding: public_field_card_blurb_is_human_readable",
932
  "status": "pass",
933
- "value": "Retrieve the matching time window for an annotation-derived text query.",
934
  "raw_hits": []
935
  },
936
  {
@@ -1008,33 +1008,33 @@
1008
  "observed": "cross_modal_retrieval"
1009
  },
1010
  {
1011
- "name": "cross_modal_retrieval: public_field_research_name_is_human_readable",
1012
  "status": "pass",
1013
- "value": "Multimodal Representation Retrieval",
1014
  "raw_hits": []
1015
  },
1016
  {
1017
- "name": "cross_modal_retrieval: public_field_process_short_is_human_readable",
1018
  "status": "pass",
1019
- "value": "modality split -> projection -> nearest-neighbor ranker",
1020
  "raw_hits": []
1021
  },
1022
  {
1023
- "name": "cross_modal_retrieval: public_field_plain_goal_is_human_readable",
1024
  "status": "pass",
1025
- "value": "Use one group of modalities to retrieve the matching window from another group.",
1026
  "raw_hits": []
1027
  },
1028
  {
1029
- "name": "cross_modal_retrieval: public_field_output_short_is_human_readable",
1030
  "status": "pass",
1031
- "value": "ranked visual windows",
1032
  "raw_hits": []
1033
  },
1034
  {
1035
- "name": "cross_modal_retrieval: public_field_input_short_is_human_readable",
1036
  "status": "pass",
1037
- "value": "motion/IMU/pose query; depth/video candidates",
1038
  "raw_hits": []
1039
  },
1040
  {
@@ -1044,9 +1044,9 @@
1044
  "raw_hits": []
1045
  },
1046
  {
1047
- "name": "cross_modal_retrieval: public_field_card_blurb_is_human_readable",
1048
  "status": "pass",
1049
- "value": "Use motion, IMU, and camera-pose signals to retrieve the matching depth/video window.",
1050
  "raw_hits": []
1051
  },
1052
  {
@@ -1126,33 +1126,33 @@
1126
  "observed": "modality_reconstruction"
1127
  },
1128
  {
1129
- "name": "modality_reconstruction: public_field_research_name_is_human_readable",
1130
  "status": "pass",
1131
- "value": "Modality Feature Reconstruction",
1132
  "raw_hits": []
1133
  },
1134
  {
1135
- "name": "modality_reconstruction: public_field_process_short_is_human_readable",
1136
  "status": "pass",
1137
- "value": "source-target split -> scaler -> regression head",
1138
  "raw_hits": []
1139
  },
1140
  {
1141
- "name": "modality_reconstruction: public_field_plain_goal_is_human_readable",
1142
  "status": "pass",
1143
- "value": "Predict one modality feature block from other modality blocks.",
1144
  "raw_hits": []
1145
  },
1146
  {
1147
- "name": "modality_reconstruction: public_field_output_short_is_human_readable",
1148
  "status": "pass",
1149
- "value": "reconstructed depth/video vector",
1150
  "raw_hits": []
1151
  },
1152
  {
1153
- "name": "modality_reconstruction: public_field_input_short_is_human_readable",
1154
  "status": "pass",
1155
- "value": "motion, IMU, and camera/pose features",
1156
  "raw_hits": []
1157
  },
1158
  {
@@ -1162,9 +1162,9 @@
1162
  "raw_hits": []
1163
  },
1164
  {
1165
- "name": "modality_reconstruction: public_field_card_blurb_is_human_readable",
1166
  "status": "pass",
1167
- "value": "Predict compressed depth/video feature vectors from motion, IMU, and camera-pose features.",
1168
  "raw_hits": []
1169
  },
1170
  {
@@ -1244,33 +1244,33 @@
1244
  "observed": "temporal_order"
1245
  },
1246
  {
1247
- "name": "temporal_order: public_field_research_name_is_human_readable",
1248
  "status": "pass",
1249
- "value": "Temporal Order Verification",
1250
  "raw_hits": []
1251
  },
1252
  {
1253
- "name": "temporal_order: public_field_process_short_is_human_readable",
1254
  "status": "pass",
1255
- "value": "pair builder -> feature combiner -> binary classifier",
1256
  "raw_hits": []
1257
  },
1258
  {
1259
- "name": "temporal_order: public_field_plain_goal_is_human_readable",
1260
  "status": "pass",
1261
- "value": "Tell whether two nearby windows are in the correct time order.",
1262
  "raw_hits": []
1263
  },
1264
  {
1265
- "name": "temporal_order: public_field_output_short_is_human_readable",
1266
  "status": "pass",
1267
- "value": "correct or reversed",
1268
  "raw_hits": []
1269
  },
1270
  {
1271
- "name": "temporal_order: public_field_input_short_is_human_readable",
1272
  "status": "pass",
1273
- "value": "two adjacent windows plus difference vector",
1274
  "raw_hits": []
1275
  },
1276
  {
@@ -1280,9 +1280,9 @@
1280
  "raw_hits": []
1281
  },
1282
  {
1283
- "name": "temporal_order: public_field_card_blurb_is_human_readable",
1284
  "status": "pass",
1285
- "value": "Tell whether two neighboring windows are in chronological order or reversed.",
1286
  "raw_hits": []
1287
  },
1288
  {
@@ -1360,33 +1360,33 @@
1360
  "observed": "misalignment_detection"
1361
  },
1362
  {
1363
- "name": "misalignment_detection: public_field_research_name_is_human_readable",
1364
  "status": "pass",
1365
- "value": "Cross-Modal Misalignment Detection",
1366
  "raw_hits": []
1367
  },
1368
  {
1369
- "name": "misalignment_detection: public_field_process_short_is_human_readable",
1370
  "status": "pass",
1371
- "value": "aligned/shifted pairs -> feature combiner -> binary classifier",
1372
  "raw_hits": []
1373
  },
1374
  {
1375
- "name": "misalignment_detection: public_field_plain_goal_is_human_readable",
1376
  "status": "pass",
1377
- "value": "Detect when modalities that should match are shifted out of sync.",
1378
  "raw_hits": []
1379
  },
1380
  {
1381
- "name": "misalignment_detection: public_field_output_short_is_human_readable",
1382
  "status": "pass",
1383
- "value": "aligned or shifted",
1384
  "raw_hits": []
1385
  },
1386
  {
1387
- "name": "misalignment_detection: public_field_input_short_is_human_readable",
1388
  "status": "pass",
1389
- "value": "motion-side and visual/depth-side feature groups",
1390
  "raw_hits": []
1391
  },
1392
  {
@@ -1396,9 +1396,9 @@
1396
  "raw_hits": []
1397
  },
1398
  {
1399
- "name": "misalignment_detection: public_field_card_blurb_is_human_readable",
1400
  "status": "pass",
1401
- "value": "Detect whether motion and visual/depth streams have been artificially shifted out of sync.",
1402
  "raw_hits": []
1403
  },
1404
  {
 
1
  {
2
  "status": "pass",
3
+ "generated_at_utc": "2026-06-15T06:37:42+00:00",
4
  "summary": {
5
  "task_count": 12,
6
  "expected_task_count": 12,
 
64
  "observed": "timeline_action"
65
  },
66
  {
67
+ "name": "timeline_action: public_field_output_short_is_human_readable",
68
  "status": "pass",
69
+ "value": "current action class",
70
  "raw_hits": []
71
  },
72
  {
73
+ "name": "timeline_action: public_field_card_blurb_is_human_readable",
74
  "status": "pass",
75
+ "value": "Recognize the current manipulation action from synchronized visual, motion, inertial, pose, and annotation context.",
76
  "raw_hits": []
77
  },
78
  {
79
+ "name": "timeline_action: public_field_process_short_is_human_readable",
80
  "status": "pass",
81
+ "value": "window features -> action label builder -> classifier",
82
  "raw_hits": []
83
  },
84
  {
85
+ "name": "timeline_action: public_field_research_name_is_human_readable",
86
  "status": "pass",
87
+ "value": "Egocentric Action Recognition",
88
  "raw_hits": []
89
  },
90
  {
91
+ "name": "timeline_action: public_field_plain_goal_is_human_readable",
92
  "status": "pass",
93
+ "value": "Look at one short multimodal window and name what action is happening now.",
94
  "raw_hits": []
95
  },
96
  {
 
100
  "raw_hits": []
101
  },
102
  {
103
+ "name": "timeline_action: public_field_input_short_is_human_readable",
104
  "status": "pass",
105
+ "value": "20-frame multimodal window",
106
  "raw_hits": []
107
  },
108
  {
 
184
  "observed": "timeline_subtask"
185
  },
186
  {
187
+ "name": "timeline_subtask: public_field_output_short_is_human_readable",
188
  "status": "pass",
189
+ "value": "current procedure step",
190
  "raw_hits": []
191
  },
192
  {
193
+ "name": "timeline_subtask: public_field_card_blurb_is_human_readable",
194
  "status": "pass",
195
+ "value": "Recognize the broader activity stage so fine actions become a readable procedure timeline.",
196
  "raw_hits": []
197
  },
198
  {
199
+ "name": "timeline_subtask: public_field_process_short_is_human_readable",
200
  "status": "pass",
201
+ "value": "window features -> subtask label builder -> classifier",
202
  "raw_hits": []
203
  },
204
  {
205
+ "name": "timeline_subtask: public_field_research_name_is_human_readable",
206
  "status": "pass",
207
+ "value": "Temporal Subtask Recognition",
208
  "raw_hits": []
209
  },
210
  {
211
+ "name": "timeline_subtask: public_field_plain_goal_is_human_readable",
212
  "status": "pass",
213
+ "value": "Predict the higher-level task stage for the current window.",
214
  "raw_hits": []
215
  },
216
  {
 
220
  "raw_hits": []
221
  },
222
  {
223
+ "name": "timeline_subtask: public_field_input_short_is_human_readable",
224
  "status": "pass",
225
+ "value": "20-frame multimodal window",
226
  "raw_hits": []
227
  },
228
  {
 
304
  "observed": "transition_detection"
305
  },
306
  {
307
+ "name": "transition_detection: public_field_output_short_is_human_readable",
308
  "status": "pass",
309
+ "value": "boundary or steady",
310
  "raw_hits": []
311
  },
312
  {
313
+ "name": "transition_detection: public_field_card_blurb_is_human_readable",
314
  "status": "pass",
315
+ "value": "Detect the local moment where the episode changes from one action segment to the next.",
316
  "raw_hits": []
317
  },
318
  {
319
+ "name": "transition_detection: public_field_process_short_is_human_readable",
320
  "status": "pass",
321
+ "value": "action changes -> boundary labels -> binary classifier",
322
  "raw_hits": []
323
  },
324
  {
325
+ "name": "transition_detection: public_field_research_name_is_human_readable",
326
  "status": "pass",
327
+ "value": "Temporal Action Segmentation",
328
  "raw_hits": []
329
  },
330
  {
331
+ "name": "transition_detection: public_field_plain_goal_is_human_readable",
332
  "status": "pass",
333
+ "value": "Detect whether the current window is near a boundary between actions.",
334
  "raw_hits": []
335
  },
336
  {
 
340
  "raw_hits": []
341
  },
342
  {
343
+ "name": "transition_detection: public_field_input_short_is_human_readable",
344
  "status": "pass",
345
+ "value": "current window with boundary target",
346
  "raw_hits": []
347
  },
348
  {
 
422
  "observed": "next_action"
423
  },
424
  {
425
+ "name": "next_action: public_field_output_short_is_human_readable",
426
  "status": "pass",
427
+ "value": "action at t+20 frames",
428
  "raw_hits": []
429
  },
430
  {
431
+ "name": "next_action: public_field_card_blurb_is_human_readable",
432
  "status": "pass",
433
+ "value": "Forecast the near-future action from the current observations only.",
434
  "raw_hits": []
435
  },
436
  {
437
+ "name": "next_action: public_field_process_short_is_human_readable",
438
  "status": "pass",
439
+ "value": "current features -> future label shift -> classifier",
440
  "raw_hits": []
441
  },
442
  {
443
+ "name": "next_action: public_field_research_name_is_human_readable",
444
  "status": "pass",
445
+ "value": "Short-Horizon Intention Prediction",
446
  "raw_hits": []
447
  },
448
  {
449
+ "name": "next_action: public_field_plain_goal_is_human_readable",
450
  "status": "pass",
451
+ "value": "Use the current window to guess the action that will happen shortly after it.",
452
  "raw_hits": []
453
  },
454
  {
 
458
  "raw_hits": []
459
  },
460
  {
461
+ "name": "next_action: public_field_input_short_is_human_readable",
462
  "status": "pass",
463
+ "value": "current window at time t",
464
  "raw_hits": []
465
  },
466
  {
 
540
  "observed": "hand_trajectory_forecast"
541
  },
542
  {
543
+ "name": "hand_trajectory_forecast: public_field_output_short_is_human_readable",
544
  "status": "pass",
545
+ "value": "future hand-joint trajectory",
546
  "raw_hits": []
547
  },
548
  {
549
+ "name": "hand_trajectory_forecast: public_field_card_blurb_is_human_readable",
550
  "status": "pass",
551
+ "value": "Predict the future 3D left/right hand path from the current multimodal state.",
552
  "raw_hits": []
553
  },
554
  {
555
+ "name": "hand_trajectory_forecast: public_field_process_short_is_human_readable",
556
  "status": "pass",
557
+ "value": "current features -> future mocap target -> regression head",
558
  "raw_hits": []
559
  },
560
  {
561
+ "name": "hand_trajectory_forecast: public_field_research_name_is_human_readable",
562
  "status": "pass",
563
+ "value": "3D Hand Motion Forecasting",
564
  "raw_hits": []
565
  },
566
  {
567
+ "name": "hand_trajectory_forecast: public_field_plain_goal_is_human_readable",
568
  "status": "pass",
569
+ "value": "Predict where the hands will move over the next few frames.",
570
  "raw_hits": []
571
  },
572
  {
 
576
  "raw_hits": []
577
  },
578
  {
579
+ "name": "hand_trajectory_forecast: public_field_input_short_is_human_readable",
580
  "status": "pass",
581
+ "value": "current multimodal window",
582
  "raw_hits": []
583
  },
584
  {
 
658
  "observed": "contact_prediction"
659
  },
660
  {
661
+ "name": "contact_prediction: public_field_output_short_is_human_readable",
662
  "status": "pass",
663
+ "value": "contact or no contact",
664
  "raw_hits": []
665
  },
666
  {
667
+ "name": "contact_prediction: public_field_card_blurb_is_human_readable",
668
  "status": "pass",
669
+ "value": "Predict whether body or hand contact with the scene is occurring without leaking contact labels.",
670
  "raw_hits": []
671
  },
672
  {
673
+ "name": "contact_prediction: public_field_process_short_is_human_readable",
674
  "status": "pass",
675
+ "value": "feature filter -> contact target -> binary classifier",
676
  "raw_hits": []
677
  },
678
  {
679
+ "name": "contact_prediction: public_field_research_name_is_human_readable",
680
  "status": "pass",
681
+ "value": "Human-Object Contact Prediction",
682
  "raw_hits": []
683
  },
684
  {
685
+ "name": "contact_prediction: public_field_plain_goal_is_human_readable",
686
  "status": "pass",
687
+ "value": "Predict whether the body or hand is in contact with something.",
688
  "raw_hits": []
689
  },
690
  {
 
694
  "raw_hits": []
695
  },
696
  {
697
+ "name": "contact_prediction: public_field_input_short_is_human_readable",
698
  "status": "pass",
699
+ "value": "non-contact, non-caption features",
700
  "raw_hits": []
701
  },
702
  {
 
774
  "observed": "object_relevance"
775
  },
776
  {
777
+ "name": "object_relevance: public_field_output_short_is_human_readable",
778
  "status": "pass",
779
+ "value": "relevant object set",
780
  "raw_hits": []
781
  },
782
  {
783
+ "name": "object_relevance: public_field_card_blurb_is_human_readable",
784
  "status": "pass",
785
+ "value": "Infer which objects are relevant to the current manipulation window from non-caption features.",
786
  "raw_hits": []
787
  },
788
  {
789
+ "name": "object_relevance: public_field_process_short_is_human_readable",
790
  "status": "pass",
791
+ "value": "object vocabulary -> multi-hot labels -> sigmoid heads",
792
  "raw_hits": []
793
  },
794
  {
795
+ "name": "object_relevance: public_field_research_name_is_human_readable",
796
  "status": "pass",
797
+ "value": "Object-Centric Interaction Recognition",
798
  "raw_hits": []
799
  },
800
  {
801
+ "name": "object_relevance: public_field_plain_goal_is_human_readable",
802
  "status": "pass",
803
+ "value": "Predict which objects matter in the current window.",
804
  "raw_hits": []
805
  },
806
  {
 
810
  "raw_hits": []
811
  },
812
  {
813
+ "name": "object_relevance: public_field_input_short_is_human_readable",
814
  "status": "pass",
815
+ "value": "non-caption multimodal features",
816
  "raw_hits": []
817
  },
818
  {
 
892
  "observed": "caption_grounding"
893
  },
894
  {
895
+ "name": "caption_grounding: public_field_output_short_is_human_readable",
896
  "status": "pass",
897
+ "value": "ranked matching moments",
898
  "raw_hits": []
899
  },
900
  {
901
+ "name": "caption_grounding: public_field_card_blurb_is_human_readable",
902
  "status": "pass",
903
+ "value": "Retrieve the matching time window for an annotation-derived text query.",
904
  "raw_hits": []
905
  },
906
  {
907
+ "name": "caption_grounding: public_field_process_short_is_human_readable",
908
  "status": "pass",
909
+ "value": "query features -> candidate index -> cosine ranker",
910
  "raw_hits": []
911
  },
912
  {
913
+ "name": "caption_grounding: public_field_research_name_is_human_readable",
914
  "status": "pass",
915
+ "value": "Language-to-Moment Grounding",
916
  "raw_hits": []
917
  },
918
  {
919
+ "name": "caption_grounding: public_field_plain_goal_is_human_readable",
920
  "status": "pass",
921
+ "value": "Given a text-like query from annotation, find the matching time window.",
922
  "raw_hits": []
923
  },
924
  {
 
928
  "raw_hits": []
929
  },
930
  {
931
+ "name": "caption_grounding: public_field_input_short_is_human_readable",
932
  "status": "pass",
933
+ "value": "text-like query and candidate windows",
934
  "raw_hits": []
935
  },
936
  {
 
1008
  "observed": "cross_modal_retrieval"
1009
  },
1010
  {
1011
+ "name": "cross_modal_retrieval: public_field_output_short_is_human_readable",
1012
  "status": "pass",
1013
+ "value": "ranked visual windows",
1014
  "raw_hits": []
1015
  },
1016
  {
1017
+ "name": "cross_modal_retrieval: public_field_card_blurb_is_human_readable",
1018
  "status": "pass",
1019
+ "value": "Use motion, IMU, and camera-pose signals to retrieve the matching depth/video window.",
1020
  "raw_hits": []
1021
  },
1022
  {
1023
+ "name": "cross_modal_retrieval: public_field_process_short_is_human_readable",
1024
  "status": "pass",
1025
+ "value": "modality split -> projection -> nearest-neighbor ranker",
1026
  "raw_hits": []
1027
  },
1028
  {
1029
+ "name": "cross_modal_retrieval: public_field_research_name_is_human_readable",
1030
  "status": "pass",
1031
+ "value": "Multimodal Representation Retrieval",
1032
  "raw_hits": []
1033
  },
1034
  {
1035
+ "name": "cross_modal_retrieval: public_field_plain_goal_is_human_readable",
1036
  "status": "pass",
1037
+ "value": "Use one group of modalities to retrieve the matching window from another group.",
1038
  "raw_hits": []
1039
  },
1040
  {
 
1044
  "raw_hits": []
1045
  },
1046
  {
1047
+ "name": "cross_modal_retrieval: public_field_input_short_is_human_readable",
1048
  "status": "pass",
1049
+ "value": "motion/IMU/pose query; depth/video candidates",
1050
  "raw_hits": []
1051
  },
1052
  {
 
1126
  "observed": "modality_reconstruction"
1127
  },
1128
  {
1129
+ "name": "modality_reconstruction: public_field_output_short_is_human_readable",
1130
  "status": "pass",
1131
+ "value": "reconstructed depth/video vector",
1132
  "raw_hits": []
1133
  },
1134
  {
1135
+ "name": "modality_reconstruction: public_field_card_blurb_is_human_readable",
1136
  "status": "pass",
1137
+ "value": "Predict compressed depth/video feature vectors from motion, IMU, and camera-pose features.",
1138
  "raw_hits": []
1139
  },
1140
  {
1141
+ "name": "modality_reconstruction: public_field_process_short_is_human_readable",
1142
  "status": "pass",
1143
+ "value": "source-target split -> scaler -> regression head",
1144
  "raw_hits": []
1145
  },
1146
  {
1147
+ "name": "modality_reconstruction: public_field_research_name_is_human_readable",
1148
  "status": "pass",
1149
+ "value": "Modality Feature Reconstruction",
1150
  "raw_hits": []
1151
  },
1152
  {
1153
+ "name": "modality_reconstruction: public_field_plain_goal_is_human_readable",
1154
  "status": "pass",
1155
+ "value": "Predict one modality feature block from other modality blocks.",
1156
  "raw_hits": []
1157
  },
1158
  {
 
1162
  "raw_hits": []
1163
  },
1164
  {
1165
+ "name": "modality_reconstruction: public_field_input_short_is_human_readable",
1166
  "status": "pass",
1167
+ "value": "motion, IMU, and camera/pose features",
1168
  "raw_hits": []
1169
  },
1170
  {
 
1244
  "observed": "temporal_order"
1245
  },
1246
  {
1247
+ "name": "temporal_order: public_field_output_short_is_human_readable",
1248
  "status": "pass",
1249
+ "value": "correct or reversed",
1250
  "raw_hits": []
1251
  },
1252
  {
1253
+ "name": "temporal_order: public_field_card_blurb_is_human_readable",
1254
  "status": "pass",
1255
+ "value": "Tell whether two neighboring windows are in chronological order or reversed.",
1256
  "raw_hits": []
1257
  },
1258
  {
1259
+ "name": "temporal_order: public_field_process_short_is_human_readable",
1260
  "status": "pass",
1261
+ "value": "pair builder -> feature combiner -> binary classifier",
1262
  "raw_hits": []
1263
  },
1264
  {
1265
+ "name": "temporal_order: public_field_research_name_is_human_readable",
1266
  "status": "pass",
1267
+ "value": "Temporal Order Verification",
1268
  "raw_hits": []
1269
  },
1270
  {
1271
+ "name": "temporal_order: public_field_plain_goal_is_human_readable",
1272
  "status": "pass",
1273
+ "value": "Tell whether two nearby windows are in the correct time order.",
1274
  "raw_hits": []
1275
  },
1276
  {
 
1280
  "raw_hits": []
1281
  },
1282
  {
1283
+ "name": "temporal_order: public_field_input_short_is_human_readable",
1284
  "status": "pass",
1285
+ "value": "two adjacent windows plus difference vector",
1286
  "raw_hits": []
1287
  },
1288
  {
 
1360
  "observed": "misalignment_detection"
1361
  },
1362
  {
1363
+ "name": "misalignment_detection: public_field_output_short_is_human_readable",
1364
  "status": "pass",
1365
+ "value": "aligned or shifted",
1366
  "raw_hits": []
1367
  },
1368
  {
1369
+ "name": "misalignment_detection: public_field_card_blurb_is_human_readable",
1370
  "status": "pass",
1371
+ "value": "Detect whether motion and visual/depth streams have been artificially shifted out of sync.",
1372
  "raw_hits": []
1373
  },
1374
  {
1375
+ "name": "misalignment_detection: public_field_process_short_is_human_readable",
1376
  "status": "pass",
1377
+ "value": "aligned/shifted pairs -> feature combiner -> binary classifier",
1378
  "raw_hits": []
1379
  },
1380
  {
1381
+ "name": "misalignment_detection: public_field_research_name_is_human_readable",
1382
  "status": "pass",
1383
+ "value": "Cross-Modal Misalignment Detection",
1384
  "raw_hits": []
1385
  },
1386
  {
1387
+ "name": "misalignment_detection: public_field_plain_goal_is_human_readable",
1388
  "status": "pass",
1389
+ "value": "Detect when modalities that should match are shifted out of sync.",
1390
  "raw_hits": []
1391
  },
1392
  {
 
1396
  "raw_hits": []
1397
  },
1398
  {
1399
+ "name": "misalignment_detection: public_field_input_short_is_human_readable",
1400
  "status": "pass",
1401
+ "value": "motion-side and visual/depth-side feature groups",
1402
  "raw_hits": []
1403
  },
1404
  {
data/website_integrity.json CHANGED
@@ -1,11 +1,11 @@
1
  {
2
  "status": "pass",
3
- "generated_at_utc": "2026-06-14T05:39:07+00:00",
4
  "docs_root": "docs",
5
  "site_base": "/ropedia-xperience-10m-task-suite/",
6
  "summary": {
7
  "html_pages": 4,
8
- "local_references": 142,
9
  "external_reference_count": 111,
10
  "json_files": 38,
11
  "image_assets_referenced": 22,
@@ -229,7 +229,7 @@
229
  {
230
  "path": "index.html",
231
  "id_count": 77,
232
- "reference_count": 119,
233
  "image_count": 24
234
  },
235
  {
@@ -253,7 +253,7 @@
253
  },
254
  {
255
  "path": "data/artifact_index.json",
256
- "bytes": 89995,
257
  "top_level_type": "dict"
258
  },
259
  {
@@ -288,12 +288,12 @@
288
  },
289
  {
290
  "path": "data/live_publication_status.json",
291
- "bytes": 97776,
292
  "top_level_type": "dict"
293
  },
294
  {
295
  "path": "data/mirror_parity.json",
296
- "bytes": 550970,
297
  "top_level_type": "dict"
298
  },
299
  {
@@ -333,7 +333,7 @@
333
  },
334
  {
335
  "path": "data/public_surface_qa.json",
336
- "bytes": 5640,
337
  "top_level_type": "dict"
338
  },
339
  {
@@ -428,7 +428,7 @@
428
  },
429
  {
430
  "path": "data/website_integrity.json",
431
- "bytes": 15774,
432
  "top_level_type": "dict"
433
  },
434
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+ "reference_count": 121,
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253
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+ "bytes": 89996,
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  "top_level_type": "dict"
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290
  "path": "data/live_publication_status.json",
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+ "bytes": 102961,
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  "top_level_type": "dict"
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+ "bytes": 555090,
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  "top_level_type": "dict"
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335
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+ "bytes": 5776,
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  "top_level_type": "dict"
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  },
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  {
 
428
  },
429
  {
430
  "path": "data/website_integrity.json",
431
+ "bytes": 15775,
432
  "top_level_type": "dict"
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  },
434
  {
docs/data/artifact_index.json CHANGED
@@ -1,6 +1,6 @@
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  {
2
  "title": "Ropedia Xperience-10M Task Suite Artifact Index",
3
- "generated_at_utc": "2026-06-14T05:39:44+00:00",
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  "status": "pass",
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  "artifact_count": 164,
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  "missing": [],
@@ -417,8 +417,8 @@
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  "shows": "Gives the human-readable map from project scope to data, tasks, platform mirrors, and scale-up status.",
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@@ -462,7 +462,7 @@
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  "id": "source_alignment_validator",
@@ -726,7 +726,7 @@
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  "shows": "Keeps the repo, website, and Hugging Face cards aligned as one cohesive research project surface.",
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  "id": "public_surface_qa_json",
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  "volatile": true,
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  "shows": "Machine-readable report for SEO/social metadata, accessible tab semantics, public links, project links, and clear project presentation.",
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- "bytes": 97776,
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  },
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  {
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898
  "volatile": true,
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  "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.",
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  "volatile": true,
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  {
 
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+ "generated_at_utc": "2026-06-15T06:37:25+00:00",
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  "status": "pass",
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  "missing": [],
 
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  "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
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  "id": "source_alignment_validator",
 
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  "shows": "Keeps the repo, website, and Hugging Face cards aligned as one cohesive research project surface.",
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  },
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  {
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  "id": "public_surface_qa_json",
 
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  "volatile": true,
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  "shows": "Machine-readable report for SEO/social metadata, accessible tab semantics, public links, project links, and clear project presentation.",
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  "exists": true,
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+ "bytes": 5776,
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  "hash_policy": "existence_and_size_only"
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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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  "hash_policy": "existence_and_size_only"
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  "volatile": true,
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  "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.",
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  "exists": true,
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+ "bytes": 555090,
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  "hash_policy": "existence_and_size_only"
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  {
 
910
  "volatile": true,
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  "shows": "Confirms local website links, anchors, JSON data files, and referenced images resolve.",
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+ "bytes": 15775,
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docs/data/live_publication_status.json CHANGED
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- "status": "pass",
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- "checked_at_utc": "2026-06-11T04:08:43+00:00",
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  "scope": "Live GitHub Pages, GitHub raw, Hugging Face Space, artifact dataset, baseline model mirrors, and the Qwen3/Cosmos3 LoRA adapter repos when their upload packages exist locally.",
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  "hash_groups": [
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  "url": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines/resolve/main/assets/task_suite_infographic.png"
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- "sha256": "53ccc5522df02b2b3658958f3da6ef542a2aa9f85e0bf69cad61ca7a0d254160",
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  "final_url": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/data/quality_gates.json",
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  "url": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/data/quality_gates.json"
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- "sha256": "53ccc5522df02b2b3658958f3da6ef542a2aa9f85e0bf69cad61ca7a0d254160",
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  "final_url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/raw/main/data/quality_gates.json",
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  "url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/raw/main/data/quality_gates.json"
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  "url": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines/resolve/main/metrics/quality_gates.json"
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@@ -120,47 +120,47 @@
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  "url": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/data/single_episode_explorer.json"
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  "url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/raw/main/data/single_episode_explorer.json"
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@@ -173,48 +173,48 @@
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  "url": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/single_episode_explorer.html"
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  "url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/raw/main/single_episode_explorer.html"
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  "url": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines/resolve/main/single_episode_explorer.html"
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@@ -227,48 +227,48 @@
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- "sha256": "a51ccc9e42247be6cda5a026c96be74e2aeeacfae6ef47abf028c9f769eae9a1",
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  "final_url": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/research_roadmap.html",
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  "url": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/research_roadmap.html"
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  "final_url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/raw/main/research_roadmap.html",
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  "url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/raw/main/research_roadmap.html"
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  "url": "https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts/resolve/main/docs/research_roadmap.html"
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@@ -287,7 +287,7 @@
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1244
  "url": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines/resolve/main/metrics/task_surface_integrity.json"
1245
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1246
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1259
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1260
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1261
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1262
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1263
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1265
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1269
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1271
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1272
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1274
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1275
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1279
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1280
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1281
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1282
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1286
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1288
  "url": "https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts/resolve/main/docs/data/brand_assets.json"
1289
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1291
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1292
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  "url": "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines/resolve/main/metrics/brand_assets.json"
1299
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1300
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@@ -1313,7 +1313,7 @@
1313
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1315
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1316
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1323
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1324
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1326
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1330
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1331
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1333
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1367
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1397
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@@ -1411,7 +1411,7 @@
1411
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  "url": "https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep/resolve/main/README.md"
1431
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1432
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1434
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1435
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1436
  "id": "qwen3_lora_upload_manifest_json",
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  "title": "Qwen3-Omni LoRA repo file: upload_manifest.json",
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  "url": "https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep/resolve/main/upload_manifest.json"
1455
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1458
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1459
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1460
  "id": "qwen3_lora_adapter_config_json",
1461
  "title": "Qwen3-Omni LoRA repo file: adapter_config.json",
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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
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1487
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1505
- "failures": []
 
 
 
 
 
 
 
 
1506
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1507
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1508
  "id": "cosmos3_super_lora_README_md",
@@ -1517,7 +1549,7 @@
1517
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@@ -1678,58 +1710,87 @@
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  "id": "github_pages_index_current",
1679
  "title": "GitHub Pages index contains current publication markers",
1680
  "url": "https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/",
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1693
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- "failures": []
 
 
 
 
 
 
 
1695
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1696
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  "id": "hf_space_index_current",
1698
  "title": "HF Space index contains current publication markers",
1699
  "url": "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite/raw/main/index.html",
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1712
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1714
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  "url": "https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts/raw/main/README.md",
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1731
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1733
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1788
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1790
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  "name": "website_has_research_seo_metadata",
 
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  "title": "Ropedia Xperience-10M Public Project Surface",
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@@ -64,33 +64,33 @@
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- "name": "timeline_action: public_field_research_name_is_human_readable",
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- "name": "timeline_action: public_field_plain_goal_is_human_readable",
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  "status": "pass",
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- "value": "Look at one short multimodal window and name what action is happening now.",
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- "name": "timeline_action: public_field_output_short_is_human_readable",
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  "status": "pass",
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- "value": "current action class",
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- "name": "timeline_action: public_field_input_short_is_human_readable",
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  "status": "pass",
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- "value": "20-frame multimodal window",
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  {
@@ -100,9 +100,9 @@
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  "status": "pass",
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- "value": "Recognize the current manipulation action from synchronized visual, motion, inertial, pose, and annotation context.",
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@@ -184,33 +184,33 @@
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  "observed": "timeline_subtask"
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187
- "name": "timeline_subtask: public_field_research_name_is_human_readable",
188
  "status": "pass",
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- "value": "Temporal Subtask Recognition",
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- "name": "timeline_subtask: public_field_plain_goal_is_human_readable",
200
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- "value": "Predict the higher-level task stage for the current window.",
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212
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@@ -220,9 +220,9 @@
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223
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224
  "status": "pass",
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  {
@@ -304,33 +304,33 @@
304
  "observed": "transition_detection"
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306
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307
- "name": "transition_detection: public_field_research_name_is_human_readable",
308
  "status": "pass",
309
- "value": "Temporal Action Segmentation",
310
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- "name": "transition_detection: public_field_process_short_is_human_readable",
314
  "status": "pass",
315
- "value": "action changes -> boundary labels -> binary classifier",
316
  "raw_hits": []
317
  },
318
  {
319
- "name": "transition_detection: public_field_plain_goal_is_human_readable",
320
  "status": "pass",
321
- "value": "Detect whether the current window is near a boundary between actions.",
322
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325
- "name": "transition_detection: public_field_output_short_is_human_readable",
326
  "status": "pass",
327
- "value": "boundary or steady",
328
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330
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331
- "name": "transition_detection: public_field_input_short_is_human_readable",
332
  "status": "pass",
333
- "value": "current window with boundary target",
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@@ -340,9 +340,9 @@
340
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341
  },
342
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343
- "name": "transition_detection: public_field_card_blurb_is_human_readable",
344
  "status": "pass",
345
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  {
@@ -422,33 +422,33 @@
422
  "observed": "next_action"
423
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425
- "name": "next_action: public_field_research_name_is_human_readable",
426
  "status": "pass",
427
- "value": "Short-Horizon Intention Prediction",
428
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429
  },
430
  {
431
- "name": "next_action: public_field_process_short_is_human_readable",
432
  "status": "pass",
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- "value": "current features -> future label shift -> classifier",
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- "name": "next_action: public_field_plain_goal_is_human_readable",
438
  "status": "pass",
439
- "value": "Use the current window to guess the action that will happen shortly after it.",
440
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- "name": "next_action: public_field_output_short_is_human_readable",
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  "status": "pass",
445
- "value": "action at t+20 frames",
446
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447
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448
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449
- "name": "next_action: public_field_input_short_is_human_readable",
450
  "status": "pass",
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- "value": "current window at time t",
452
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453
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  {
@@ -458,9 +458,9 @@
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459
  },
460
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461
- "name": "next_action: public_field_card_blurb_is_human_readable",
462
  "status": "pass",
463
- "value": "Forecast the near-future action from the current observations only.",
464
  "raw_hits": []
465
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466
  {
@@ -540,33 +540,33 @@
540
  "observed": "hand_trajectory_forecast"
541
  },
542
  {
543
- "name": "hand_trajectory_forecast: public_field_research_name_is_human_readable",
544
  "status": "pass",
545
- "value": "3D Hand Motion Forecasting",
546
  "raw_hits": []
547
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548
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549
- "name": "hand_trajectory_forecast: public_field_process_short_is_human_readable",
550
  "status": "pass",
551
- "value": "current features -> future mocap target -> regression head",
552
  "raw_hits": []
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  {
555
- "name": "hand_trajectory_forecast: public_field_plain_goal_is_human_readable",
556
  "status": "pass",
557
- "value": "Predict where the hands will move over the next few frames.",
558
  "raw_hits": []
559
  },
560
  {
561
- "name": "hand_trajectory_forecast: public_field_output_short_is_human_readable",
562
  "status": "pass",
563
- "value": "future hand-joint trajectory",
564
  "raw_hits": []
565
  },
566
  {
567
- "name": "hand_trajectory_forecast: public_field_input_short_is_human_readable",
568
  "status": "pass",
569
- "value": "current multimodal window",
570
  "raw_hits": []
571
  },
572
  {
@@ -576,9 +576,9 @@
576
  "raw_hits": []
577
  },
578
  {
579
- "name": "hand_trajectory_forecast: public_field_card_blurb_is_human_readable",
580
  "status": "pass",
581
- "value": "Predict the future 3D left/right hand path from the current multimodal state.",
582
  "raw_hits": []
583
  },
584
  {
@@ -658,33 +658,33 @@
658
  "observed": "contact_prediction"
659
  },
660
  {
661
- "name": "contact_prediction: public_field_research_name_is_human_readable",
662
  "status": "pass",
663
- "value": "Human-Object Contact Prediction",
664
  "raw_hits": []
665
  },
666
  {
667
- "name": "contact_prediction: public_field_process_short_is_human_readable",
668
  "status": "pass",
669
- "value": "feature filter -> contact target -> binary classifier",
670
  "raw_hits": []
671
  },
672
  {
673
- "name": "contact_prediction: public_field_plain_goal_is_human_readable",
674
  "status": "pass",
675
- "value": "Predict whether the body or hand is in contact with something.",
676
  "raw_hits": []
677
  },
678
  {
679
- "name": "contact_prediction: public_field_output_short_is_human_readable",
680
  "status": "pass",
681
- "value": "contact or no contact",
682
  "raw_hits": []
683
  },
684
  {
685
- "name": "contact_prediction: public_field_input_short_is_human_readable",
686
  "status": "pass",
687
- "value": "non-contact, non-caption features",
688
  "raw_hits": []
689
  },
690
  {
@@ -694,9 +694,9 @@
694
  "raw_hits": []
695
  },
696
  {
697
- "name": "contact_prediction: public_field_card_blurb_is_human_readable",
698
  "status": "pass",
699
- "value": "Predict whether body or hand contact with the scene is occurring without leaking contact labels.",
700
  "raw_hits": []
701
  },
702
  {
@@ -774,33 +774,33 @@
774
  "observed": "object_relevance"
775
  },
776
  {
777
- "name": "object_relevance: public_field_research_name_is_human_readable",
778
  "status": "pass",
779
- "value": "Object-Centric Interaction Recognition",
780
  "raw_hits": []
781
  },
782
  {
783
- "name": "object_relevance: public_field_process_short_is_human_readable",
784
  "status": "pass",
785
- "value": "object vocabulary -> multi-hot labels -> sigmoid heads",
786
  "raw_hits": []
787
  },
788
  {
789
- "name": "object_relevance: public_field_plain_goal_is_human_readable",
790
  "status": "pass",
791
- "value": "Predict which objects matter in the current window.",
792
  "raw_hits": []
793
  },
794
  {
795
- "name": "object_relevance: public_field_output_short_is_human_readable",
796
  "status": "pass",
797
- "value": "relevant object set",
798
  "raw_hits": []
799
  },
800
  {
801
- "name": "object_relevance: public_field_input_short_is_human_readable",
802
  "status": "pass",
803
- "value": "non-caption multimodal features",
804
  "raw_hits": []
805
  },
806
  {
@@ -810,9 +810,9 @@
810
  "raw_hits": []
811
  },
812
  {
813
- "name": "object_relevance: public_field_card_blurb_is_human_readable",
814
  "status": "pass",
815
- "value": "Infer which objects are relevant to the current manipulation window from non-caption features.",
816
  "raw_hits": []
817
  },
818
  {
@@ -892,33 +892,33 @@
892
  "observed": "caption_grounding"
893
  },
894
  {
895
- "name": "caption_grounding: public_field_research_name_is_human_readable",
896
  "status": "pass",
897
- "value": "Language-to-Moment Grounding",
898
  "raw_hits": []
899
  },
900
  {
901
- "name": "caption_grounding: public_field_process_short_is_human_readable",
902
  "status": "pass",
903
- "value": "query features -> candidate index -> cosine ranker",
904
  "raw_hits": []
905
  },
906
  {
907
- "name": "caption_grounding: public_field_plain_goal_is_human_readable",
908
  "status": "pass",
909
- "value": "Given a text-like query from annotation, find the matching time window.",
910
  "raw_hits": []
911
  },
912
  {
913
- "name": "caption_grounding: public_field_output_short_is_human_readable",
914
  "status": "pass",
915
- "value": "ranked matching moments",
916
  "raw_hits": []
917
  },
918
  {
919
- "name": "caption_grounding: public_field_input_short_is_human_readable",
920
  "status": "pass",
921
- "value": "text-like query and candidate windows",
922
  "raw_hits": []
923
  },
924
  {
@@ -928,9 +928,9 @@
928
  "raw_hits": []
929
  },
930
  {
931
- "name": "caption_grounding: public_field_card_blurb_is_human_readable",
932
  "status": "pass",
933
- "value": "Retrieve the matching time window for an annotation-derived text query.",
934
  "raw_hits": []
935
  },
936
  {
@@ -1008,33 +1008,33 @@
1008
  "observed": "cross_modal_retrieval"
1009
  },
1010
  {
1011
- "name": "cross_modal_retrieval: public_field_research_name_is_human_readable",
1012
  "status": "pass",
1013
- "value": "Multimodal Representation Retrieval",
1014
  "raw_hits": []
1015
  },
1016
  {
1017
- "name": "cross_modal_retrieval: public_field_process_short_is_human_readable",
1018
  "status": "pass",
1019
- "value": "modality split -> projection -> nearest-neighbor ranker",
1020
  "raw_hits": []
1021
  },
1022
  {
1023
- "name": "cross_modal_retrieval: public_field_plain_goal_is_human_readable",
1024
  "status": "pass",
1025
- "value": "Use one group of modalities to retrieve the matching window from another group.",
1026
  "raw_hits": []
1027
  },
1028
  {
1029
- "name": "cross_modal_retrieval: public_field_output_short_is_human_readable",
1030
  "status": "pass",
1031
- "value": "ranked visual windows",
1032
  "raw_hits": []
1033
  },
1034
  {
1035
- "name": "cross_modal_retrieval: public_field_input_short_is_human_readable",
1036
  "status": "pass",
1037
- "value": "motion/IMU/pose query; depth/video candidates",
1038
  "raw_hits": []
1039
  },
1040
  {
@@ -1044,9 +1044,9 @@
1044
  "raw_hits": []
1045
  },
1046
  {
1047
- "name": "cross_modal_retrieval: public_field_card_blurb_is_human_readable",
1048
  "status": "pass",
1049
- "value": "Use motion, IMU, and camera-pose signals to retrieve the matching depth/video window.",
1050
  "raw_hits": []
1051
  },
1052
  {
@@ -1126,33 +1126,33 @@
1126
  "observed": "modality_reconstruction"
1127
  },
1128
  {
1129
- "name": "modality_reconstruction: public_field_research_name_is_human_readable",
1130
  "status": "pass",
1131
- "value": "Modality Feature Reconstruction",
1132
  "raw_hits": []
1133
  },
1134
  {
1135
- "name": "modality_reconstruction: public_field_process_short_is_human_readable",
1136
  "status": "pass",
1137
- "value": "source-target split -> scaler -> regression head",
1138
  "raw_hits": []
1139
  },
1140
  {
1141
- "name": "modality_reconstruction: public_field_plain_goal_is_human_readable",
1142
  "status": "pass",
1143
- "value": "Predict one modality feature block from other modality blocks.",
1144
  "raw_hits": []
1145
  },
1146
  {
1147
- "name": "modality_reconstruction: public_field_output_short_is_human_readable",
1148
  "status": "pass",
1149
- "value": "reconstructed depth/video vector",
1150
  "raw_hits": []
1151
  },
1152
  {
1153
- "name": "modality_reconstruction: public_field_input_short_is_human_readable",
1154
  "status": "pass",
1155
- "value": "motion, IMU, and camera/pose features",
1156
  "raw_hits": []
1157
  },
1158
  {
@@ -1162,9 +1162,9 @@
1162
  "raw_hits": []
1163
  },
1164
  {
1165
- "name": "modality_reconstruction: public_field_card_blurb_is_human_readable",
1166
  "status": "pass",
1167
- "value": "Predict compressed depth/video feature vectors from motion, IMU, and camera-pose features.",
1168
  "raw_hits": []
1169
  },
1170
  {
@@ -1244,33 +1244,33 @@
1244
  "observed": "temporal_order"
1245
  },
1246
  {
1247
- "name": "temporal_order: public_field_research_name_is_human_readable",
1248
  "status": "pass",
1249
- "value": "Temporal Order Verification",
1250
  "raw_hits": []
1251
  },
1252
  {
1253
- "name": "temporal_order: public_field_process_short_is_human_readable",
1254
  "status": "pass",
1255
- "value": "pair builder -> feature combiner -> binary classifier",
1256
  "raw_hits": []
1257
  },
1258
  {
1259
- "name": "temporal_order: public_field_plain_goal_is_human_readable",
1260
  "status": "pass",
1261
- "value": "Tell whether two nearby windows are in the correct time order.",
1262
  "raw_hits": []
1263
  },
1264
  {
1265
- "name": "temporal_order: public_field_output_short_is_human_readable",
1266
  "status": "pass",
1267
- "value": "correct or reversed",
1268
  "raw_hits": []
1269
  },
1270
  {
1271
- "name": "temporal_order: public_field_input_short_is_human_readable",
1272
  "status": "pass",
1273
- "value": "two adjacent windows plus difference vector",
1274
  "raw_hits": []
1275
  },
1276
  {
@@ -1280,9 +1280,9 @@
1280
  "raw_hits": []
1281
  },
1282
  {
1283
- "name": "temporal_order: public_field_card_blurb_is_human_readable",
1284
  "status": "pass",
1285
- "value": "Tell whether two neighboring windows are in chronological order or reversed.",
1286
  "raw_hits": []
1287
  },
1288
  {
@@ -1360,33 +1360,33 @@
1360
  "observed": "misalignment_detection"
1361
  },
1362
  {
1363
- "name": "misalignment_detection: public_field_research_name_is_human_readable",
1364
  "status": "pass",
1365
- "value": "Cross-Modal Misalignment Detection",
1366
  "raw_hits": []
1367
  },
1368
  {
1369
- "name": "misalignment_detection: public_field_process_short_is_human_readable",
1370
  "status": "pass",
1371
- "value": "aligned/shifted pairs -> feature combiner -> binary classifier",
1372
  "raw_hits": []
1373
  },
1374
  {
1375
- "name": "misalignment_detection: public_field_plain_goal_is_human_readable",
1376
  "status": "pass",
1377
- "value": "Detect when modalities that should match are shifted out of sync.",
1378
  "raw_hits": []
1379
  },
1380
  {
1381
- "name": "misalignment_detection: public_field_output_short_is_human_readable",
1382
  "status": "pass",
1383
- "value": "aligned or shifted",
1384
  "raw_hits": []
1385
  },
1386
  {
1387
- "name": "misalignment_detection: public_field_input_short_is_human_readable",
1388
  "status": "pass",
1389
- "value": "motion-side and visual/depth-side feature groups",
1390
  "raw_hits": []
1391
  },
1392
  {
@@ -1396,9 +1396,9 @@
1396
  "raw_hits": []
1397
  },
1398
  {
1399
- "name": "misalignment_detection: public_field_card_blurb_is_human_readable",
1400
  "status": "pass",
1401
- "value": "Detect whether motion and visual/depth streams have been artificially shifted out of sync.",
1402
  "raw_hits": []
1403
  },
1404
  {
 
1
  {
2
  "status": "pass",
3
+ "generated_at_utc": "2026-06-15T06:37:42+00:00",
4
  "summary": {
5
  "task_count": 12,
6
  "expected_task_count": 12,
 
64
  "observed": "timeline_action"
65
  },
66
  {
67
+ "name": "timeline_action: public_field_output_short_is_human_readable",
68
  "status": "pass",
69
+ "value": "current action class",
70
  "raw_hits": []
71
  },
72
  {
73
+ "name": "timeline_action: public_field_card_blurb_is_human_readable",
74
  "status": "pass",
75
+ "value": "Recognize the current manipulation action from synchronized visual, motion, inertial, pose, and annotation context.",
76
  "raw_hits": []
77
  },
78
  {
79
+ "name": "timeline_action: public_field_process_short_is_human_readable",
80
  "status": "pass",
81
+ "value": "window features -> action label builder -> classifier",
82
  "raw_hits": []
83
  },
84
  {
85
+ "name": "timeline_action: public_field_research_name_is_human_readable",
86
  "status": "pass",
87
+ "value": "Egocentric Action Recognition",
88
  "raw_hits": []
89
  },
90
  {
91
+ "name": "timeline_action: public_field_plain_goal_is_human_readable",
92
  "status": "pass",
93
+ "value": "Look at one short multimodal window and name what action is happening now.",
94
  "raw_hits": []
95
  },
96
  {
 
100
  "raw_hits": []
101
  },
102
  {
103
+ "name": "timeline_action: public_field_input_short_is_human_readable",
104
  "status": "pass",
105
+ "value": "20-frame multimodal window",
106
  "raw_hits": []
107
  },
108
  {
 
184
  "observed": "timeline_subtask"
185
  },
186
  {
187
+ "name": "timeline_subtask: public_field_output_short_is_human_readable",
188
  "status": "pass",
189
+ "value": "current procedure step",
190
  "raw_hits": []
191
  },
192
  {
193
+ "name": "timeline_subtask: public_field_card_blurb_is_human_readable",
194
  "status": "pass",
195
+ "value": "Recognize the broader activity stage so fine actions become a readable procedure timeline.",
196
  "raw_hits": []
197
  },
198
  {
199
+ "name": "timeline_subtask: public_field_process_short_is_human_readable",
200
  "status": "pass",
201
+ "value": "window features -> subtask label builder -> classifier",
202
  "raw_hits": []
203
  },
204
  {
205
+ "name": "timeline_subtask: public_field_research_name_is_human_readable",
206
  "status": "pass",
207
+ "value": "Temporal Subtask Recognition",
208
  "raw_hits": []
209
  },
210
  {
211
+ "name": "timeline_subtask: public_field_plain_goal_is_human_readable",
212
  "status": "pass",
213
+ "value": "Predict the higher-level task stage for the current window.",
214
  "raw_hits": []
215
  },
216
  {
 
220
  "raw_hits": []
221
  },
222
  {
223
+ "name": "timeline_subtask: public_field_input_short_is_human_readable",
224
  "status": "pass",
225
+ "value": "20-frame multimodal window",
226
  "raw_hits": []
227
  },
228
  {
 
304
  "observed": "transition_detection"
305
  },
306
  {
307
+ "name": "transition_detection: public_field_output_short_is_human_readable",
308
  "status": "pass",
309
+ "value": "boundary or steady",
310
  "raw_hits": []
311
  },
312
  {
313
+ "name": "transition_detection: public_field_card_blurb_is_human_readable",
314
  "status": "pass",
315
+ "value": "Detect the local moment where the episode changes from one action segment to the next.",
316
  "raw_hits": []
317
  },
318
  {
319
+ "name": "transition_detection: public_field_process_short_is_human_readable",
320
  "status": "pass",
321
+ "value": "action changes -> boundary labels -> binary classifier",
322
  "raw_hits": []
323
  },
324
  {
325
+ "name": "transition_detection: public_field_research_name_is_human_readable",
326
  "status": "pass",
327
+ "value": "Temporal Action Segmentation",
328
  "raw_hits": []
329
  },
330
  {
331
+ "name": "transition_detection: public_field_plain_goal_is_human_readable",
332
  "status": "pass",
333
+ "value": "Detect whether the current window is near a boundary between actions.",
334
  "raw_hits": []
335
  },
336
  {
 
340
  "raw_hits": []
341
  },
342
  {
343
+ "name": "transition_detection: public_field_input_short_is_human_readable",
344
  "status": "pass",
345
+ "value": "current window with boundary target",
346
  "raw_hits": []
347
  },
348
  {
 
422
  "observed": "next_action"
423
  },
424
  {
425
+ "name": "next_action: public_field_output_short_is_human_readable",
426
  "status": "pass",
427
+ "value": "action at t+20 frames",
428
  "raw_hits": []
429
  },
430
  {
431
+ "name": "next_action: public_field_card_blurb_is_human_readable",
432
  "status": "pass",
433
+ "value": "Forecast the near-future action from the current observations only.",
434
  "raw_hits": []
435
  },
436
  {
437
+ "name": "next_action: public_field_process_short_is_human_readable",
438
  "status": "pass",
439
+ "value": "current features -> future label shift -> classifier",
440
  "raw_hits": []
441
  },
442
  {
443
+ "name": "next_action: public_field_research_name_is_human_readable",
444
  "status": "pass",
445
+ "value": "Short-Horizon Intention Prediction",
446
  "raw_hits": []
447
  },
448
  {
449
+ "name": "next_action: public_field_plain_goal_is_human_readable",
450
  "status": "pass",
451
+ "value": "Use the current window to guess the action that will happen shortly after it.",
452
  "raw_hits": []
453
  },
454
  {
 
458
  "raw_hits": []
459
  },
460
  {
461
+ "name": "next_action: public_field_input_short_is_human_readable",
462
  "status": "pass",
463
+ "value": "current window at time t",
464
  "raw_hits": []
465
  },
466
  {
 
540
  "observed": "hand_trajectory_forecast"
541
  },
542
  {
543
+ "name": "hand_trajectory_forecast: public_field_output_short_is_human_readable",
544
  "status": "pass",
545
+ "value": "future hand-joint trajectory",
546
  "raw_hits": []
547
  },
548
  {
549
+ "name": "hand_trajectory_forecast: public_field_card_blurb_is_human_readable",
550
  "status": "pass",
551
+ "value": "Predict the future 3D left/right hand path from the current multimodal state.",
552
  "raw_hits": []
553
  },
554
  {
555
+ "name": "hand_trajectory_forecast: public_field_process_short_is_human_readable",
556
  "status": "pass",
557
+ "value": "current features -> future mocap target -> regression head",
558
  "raw_hits": []
559
  },
560
  {
561
+ "name": "hand_trajectory_forecast: public_field_research_name_is_human_readable",
562
  "status": "pass",
563
+ "value": "3D Hand Motion Forecasting",
564
  "raw_hits": []
565
  },
566
  {
567
+ "name": "hand_trajectory_forecast: public_field_plain_goal_is_human_readable",
568
  "status": "pass",
569
+ "value": "Predict where the hands will move over the next few frames.",
570
  "raw_hits": []
571
  },
572
  {
 
576
  "raw_hits": []
577
  },
578
  {
579
+ "name": "hand_trajectory_forecast: public_field_input_short_is_human_readable",
580
  "status": "pass",
581
+ "value": "current multimodal window",
582
  "raw_hits": []
583
  },
584
  {
 
658
  "observed": "contact_prediction"
659
  },
660
  {
661
+ "name": "contact_prediction: public_field_output_short_is_human_readable",
662
  "status": "pass",
663
+ "value": "contact or no contact",
664
  "raw_hits": []
665
  },
666
  {
667
+ "name": "contact_prediction: public_field_card_blurb_is_human_readable",
668
  "status": "pass",
669
+ "value": "Predict whether body or hand contact with the scene is occurring without leaking contact labels.",
670
  "raw_hits": []
671
  },
672
  {
673
+ "name": "contact_prediction: public_field_process_short_is_human_readable",
674
  "status": "pass",
675
+ "value": "feature filter -> contact target -> binary classifier",
676
  "raw_hits": []
677
  },
678
  {
679
+ "name": "contact_prediction: public_field_research_name_is_human_readable",
680
  "status": "pass",
681
+ "value": "Human-Object Contact Prediction",
682
  "raw_hits": []
683
  },
684
  {
685
+ "name": "contact_prediction: public_field_plain_goal_is_human_readable",
686
  "status": "pass",
687
+ "value": "Predict whether the body or hand is in contact with something.",
688
  "raw_hits": []
689
  },
690
  {
 
694
  "raw_hits": []
695
  },
696
  {
697
+ "name": "contact_prediction: public_field_input_short_is_human_readable",
698
  "status": "pass",
699
+ "value": "non-contact, non-caption features",
700
  "raw_hits": []
701
  },
702
  {
 
774
  "observed": "object_relevance"
775
  },
776
  {
777
+ "name": "object_relevance: public_field_output_short_is_human_readable",
778
  "status": "pass",
779
+ "value": "relevant object set",
780
  "raw_hits": []
781
  },
782
  {
783
+ "name": "object_relevance: public_field_card_blurb_is_human_readable",
784
  "status": "pass",
785
+ "value": "Infer which objects are relevant to the current manipulation window from non-caption features.",
786
  "raw_hits": []
787
  },
788
  {
789
+ "name": "object_relevance: public_field_process_short_is_human_readable",
790
  "status": "pass",
791
+ "value": "object vocabulary -> multi-hot labels -> sigmoid heads",
792
  "raw_hits": []
793
  },
794
  {
795
+ "name": "object_relevance: public_field_research_name_is_human_readable",
796
  "status": "pass",
797
+ "value": "Object-Centric Interaction Recognition",
798
  "raw_hits": []
799
  },
800
  {
801
+ "name": "object_relevance: public_field_plain_goal_is_human_readable",
802
  "status": "pass",
803
+ "value": "Predict which objects matter in the current window.",
804
  "raw_hits": []
805
  },
806
  {
 
810
  "raw_hits": []
811
  },
812
  {
813
+ "name": "object_relevance: public_field_input_short_is_human_readable",
814
  "status": "pass",
815
+ "value": "non-caption multimodal features",
816
  "raw_hits": []
817
  },
818
  {
 
892
  "observed": "caption_grounding"
893
  },
894
  {
895
+ "name": "caption_grounding: public_field_output_short_is_human_readable",
896
  "status": "pass",
897
+ "value": "ranked matching moments",
898
  "raw_hits": []
899
  },
900
  {
901
+ "name": "caption_grounding: public_field_card_blurb_is_human_readable",
902
  "status": "pass",
903
+ "value": "Retrieve the matching time window for an annotation-derived text query.",
904
  "raw_hits": []
905
  },
906
  {
907
+ "name": "caption_grounding: public_field_process_short_is_human_readable",
908
  "status": "pass",
909
+ "value": "query features -> candidate index -> cosine ranker",
910
  "raw_hits": []
911
  },
912
  {
913
+ "name": "caption_grounding: public_field_research_name_is_human_readable",
914
  "status": "pass",
915
+ "value": "Language-to-Moment Grounding",
916
  "raw_hits": []
917
  },
918
  {
919
+ "name": "caption_grounding: public_field_plain_goal_is_human_readable",
920
  "status": "pass",
921
+ "value": "Given a text-like query from annotation, find the matching time window.",
922
  "raw_hits": []
923
  },
924
  {
 
928
  "raw_hits": []
929
  },
930
  {
931
+ "name": "caption_grounding: public_field_input_short_is_human_readable",
932
  "status": "pass",
933
+ "value": "text-like query and candidate windows",
934
  "raw_hits": []
935
  },
936
  {
 
1008
  "observed": "cross_modal_retrieval"
1009
  },
1010
  {
1011
+ "name": "cross_modal_retrieval: public_field_output_short_is_human_readable",
1012
  "status": "pass",
1013
+ "value": "ranked visual windows",
1014
  "raw_hits": []
1015
  },
1016
  {
1017
+ "name": "cross_modal_retrieval: public_field_card_blurb_is_human_readable",
1018
  "status": "pass",
1019
+ "value": "Use motion, IMU, and camera-pose signals to retrieve the matching depth/video window.",
1020
  "raw_hits": []
1021
  },
1022
  {
1023
+ "name": "cross_modal_retrieval: public_field_process_short_is_human_readable",
1024
  "status": "pass",
1025
+ "value": "modality split -> projection -> nearest-neighbor ranker",
1026
  "raw_hits": []
1027
  },
1028
  {
1029
+ "name": "cross_modal_retrieval: public_field_research_name_is_human_readable",
1030
  "status": "pass",
1031
+ "value": "Multimodal Representation Retrieval",
1032
  "raw_hits": []
1033
  },
1034
  {
1035
+ "name": "cross_modal_retrieval: public_field_plain_goal_is_human_readable",
1036
  "status": "pass",
1037
+ "value": "Use one group of modalities to retrieve the matching window from another group.",
1038
  "raw_hits": []
1039
  },
1040
  {
 
1044
  "raw_hits": []
1045
  },
1046
  {
1047
+ "name": "cross_modal_retrieval: public_field_input_short_is_human_readable",
1048
  "status": "pass",
1049
+ "value": "motion/IMU/pose query; depth/video candidates",
1050
  "raw_hits": []
1051
  },
1052
  {
 
1126
  "observed": "modality_reconstruction"
1127
  },
1128
  {
1129
+ "name": "modality_reconstruction: public_field_output_short_is_human_readable",
1130
  "status": "pass",
1131
+ "value": "reconstructed depth/video vector",
1132
  "raw_hits": []
1133
  },
1134
  {
1135
+ "name": "modality_reconstruction: public_field_card_blurb_is_human_readable",
1136
  "status": "pass",
1137
+ "value": "Predict compressed depth/video feature vectors from motion, IMU, and camera-pose features.",
1138
  "raw_hits": []
1139
  },
1140
  {
1141
+ "name": "modality_reconstruction: public_field_process_short_is_human_readable",
1142
  "status": "pass",
1143
+ "value": "source-target split -> scaler -> regression head",
1144
  "raw_hits": []
1145
  },
1146
  {
1147
+ "name": "modality_reconstruction: public_field_research_name_is_human_readable",
1148
  "status": "pass",
1149
+ "value": "Modality Feature Reconstruction",
1150
  "raw_hits": []
1151
  },
1152
  {
1153
+ "name": "modality_reconstruction: public_field_plain_goal_is_human_readable",
1154
  "status": "pass",
1155
+ "value": "Predict one modality feature block from other modality blocks.",
1156
  "raw_hits": []
1157
  },
1158
  {
 
1162
  "raw_hits": []
1163
  },
1164
  {
1165
+ "name": "modality_reconstruction: public_field_input_short_is_human_readable",
1166
  "status": "pass",
1167
+ "value": "motion, IMU, and camera/pose features",
1168
  "raw_hits": []
1169
  },
1170
  {
 
1244
  "observed": "temporal_order"
1245
  },
1246
  {
1247
+ "name": "temporal_order: public_field_output_short_is_human_readable",
1248
  "status": "pass",
1249
+ "value": "correct or reversed",
1250
  "raw_hits": []
1251
  },
1252
  {
1253
+ "name": "temporal_order: public_field_card_blurb_is_human_readable",
1254
  "status": "pass",
1255
+ "value": "Tell whether two neighboring windows are in chronological order or reversed.",
1256
  "raw_hits": []
1257
  },
1258
  {
1259
+ "name": "temporal_order: public_field_process_short_is_human_readable",
1260
  "status": "pass",
1261
+ "value": "pair builder -> feature combiner -> binary classifier",
1262
  "raw_hits": []
1263
  },
1264
  {
1265
+ "name": "temporal_order: public_field_research_name_is_human_readable",
1266
  "status": "pass",
1267
+ "value": "Temporal Order Verification",
1268
  "raw_hits": []
1269
  },
1270
  {
1271
+ "name": "temporal_order: public_field_plain_goal_is_human_readable",
1272
  "status": "pass",
1273
+ "value": "Tell whether two nearby windows are in the correct time order.",
1274
  "raw_hits": []
1275
  },
1276
  {
 
1280
  "raw_hits": []
1281
  },
1282
  {
1283
+ "name": "temporal_order: public_field_input_short_is_human_readable",
1284
  "status": "pass",
1285
+ "value": "two adjacent windows plus difference vector",
1286
  "raw_hits": []
1287
  },
1288
  {
 
1360
  "observed": "misalignment_detection"
1361
  },
1362
  {
1363
+ "name": "misalignment_detection: public_field_output_short_is_human_readable",
1364
  "status": "pass",
1365
+ "value": "aligned or shifted",
1366
  "raw_hits": []
1367
  },
1368
  {
1369
+ "name": "misalignment_detection: public_field_card_blurb_is_human_readable",
1370
  "status": "pass",
1371
+ "value": "Detect whether motion and visual/depth streams have been artificially shifted out of sync.",
1372
  "raw_hits": []
1373
  },
1374
  {
1375
+ "name": "misalignment_detection: public_field_process_short_is_human_readable",
1376
  "status": "pass",
1377
+ "value": "aligned/shifted pairs -> feature combiner -> binary classifier",
1378
  "raw_hits": []
1379
  },
1380
  {
1381
+ "name": "misalignment_detection: public_field_research_name_is_human_readable",
1382
  "status": "pass",
1383
+ "value": "Cross-Modal Misalignment Detection",
1384
  "raw_hits": []
1385
  },
1386
  {
1387
+ "name": "misalignment_detection: public_field_plain_goal_is_human_readable",
1388
  "status": "pass",
1389
+ "value": "Detect when modalities that should match are shifted out of sync.",
1390
  "raw_hits": []
1391
  },
1392
  {
 
1396
  "raw_hits": []
1397
  },
1398
  {
1399
+ "name": "misalignment_detection: public_field_input_short_is_human_readable",
1400
  "status": "pass",
1401
+ "value": "motion-side and visual/depth-side feature groups",
1402
  "raw_hits": []
1403
  },
1404
  {
docs/data/website_integrity.json CHANGED
@@ -1,11 +1,11 @@
1
  {
2
  "status": "pass",
3
- "generated_at_utc": "2026-06-14T05:39:07+00:00",
4
  "docs_root": "docs",
5
  "site_base": "/ropedia-xperience-10m-task-suite/",
6
  "summary": {
7
  "html_pages": 4,
8
- "local_references": 142,
9
  "external_reference_count": 111,
10
  "json_files": 38,
11
  "image_assets_referenced": 22,
@@ -229,7 +229,7 @@
229
  {
230
  "path": "index.html",
231
  "id_count": 77,
232
- "reference_count": 119,
233
  "image_count": 24
234
  },
235
  {
@@ -253,7 +253,7 @@
253
  },
254
  {
255
  "path": "data/artifact_index.json",
256
- "bytes": 89995,
257
  "top_level_type": "dict"
258
  },
259
  {
@@ -288,12 +288,12 @@
288
  },
289
  {
290
  "path": "data/live_publication_status.json",
291
- "bytes": 97776,
292
  "top_level_type": "dict"
293
  },
294
  {
295
  "path": "data/mirror_parity.json",
296
- "bytes": 550970,
297
  "top_level_type": "dict"
298
  },
299
  {
@@ -333,7 +333,7 @@
333
  },
334
  {
335
  "path": "data/public_surface_qa.json",
336
- "bytes": 5640,
337
  "top_level_type": "dict"
338
  },
339
  {
@@ -428,7 +428,7 @@
428
  },
429
  {
430
  "path": "data/website_integrity.json",
431
- "bytes": 15774,
432
  "top_level_type": "dict"
433
  },
434
  {
 
1
  {
2
  "status": "pass",
3
+ "generated_at_utc": "2026-06-15T06:37:26+00:00",
4
  "docs_root": "docs",
5
  "site_base": "/ropedia-xperience-10m-task-suite/",
6
  "summary": {
7
  "html_pages": 4,
8
+ "local_references": 144,
9
  "external_reference_count": 111,
10
  "json_files": 38,
11
  "image_assets_referenced": 22,
 
229
  {
230
  "path": "index.html",
231
  "id_count": 77,
232
+ "reference_count": 121,
233
  "image_count": 24
234
  },
235
  {
 
253
  },
254
  {
255
  "path": "data/artifact_index.json",
256
+ "bytes": 89996,
257
  "top_level_type": "dict"
258
  },
259
  {
 
288
  },
289
  {
290
  "path": "data/live_publication_status.json",
291
+ "bytes": 102961,
292
  "top_level_type": "dict"
293
  },
294
  {
295
  "path": "data/mirror_parity.json",
296
+ "bytes": 555090,
297
  "top_level_type": "dict"
298
  },
299
  {
 
333
  },
334
  {
335
  "path": "data/public_surface_qa.json",
336
+ "bytes": 5776,
337
  "top_level_type": "dict"
338
  },
339
  {
 
428
  },
429
  {
430
  "path": "data/website_integrity.json",
431
+ "bytes": 15775,
432
  "top_level_type": "dict"
433
  },
434
  {
docs/index.html CHANGED
@@ -2678,7 +2678,7 @@
2678
  <article class="evidence-card">
2679
  <span class="status-pill">verified diagnostic</span>
2680
  <h3>Qwen3-Omni and Cosmos3 branches</h3>
2681
- <p>The selected 96/16/16 episode split produced verified Qwen3-Omni packages with 448 held-out test predictions. Cosmos3-Nano has 378 held-out future-window predictions, Cosmos3-Super Reasoner has 448 held-out base-weight JSON-task predictions, and Cosmos3-Super Forward-Dynamics LoRA has 448 held-out loss records.</p>
2682
  <div class="evidence-links">
2683
  <a href="data/omni_model_comparison.json">result comparison</a>
2684
  <a href="data/omni_finetune_verified_result.json">pilot result</a>
@@ -2854,7 +2854,7 @@
2854
  <article class="artifact primary-artifact"><div><h3>Official dataset</h3><p>Xperience-10M is a gated large-scale egocentric multimodal dataset for embodied AI, robotics, spatial intelligence, and world modeling.</p></div><a href="https://huggingface.co/datasets/ropedia-ai/xperience-10m">official HF dataset</a></article>
2855
  <article class="artifact"><h3>Public sample</h3><p>The current task suite is built from one public sample episode, not from the entire gated dataset.</p><a href="https://huggingface.co/datasets/ropedia-ai/xperience-10m-sample">sample dataset</a></article>
2856
  <article class="artifact"><h3>Modalities</h3><p>The sample exposes synchronized video, audio, depth, pose/SLAM, motion capture, inertial signals, calibration, and language annotations.</p><a href="data/modality_atlas.json">modality atlas</a></article>
2857
- <article class="artifact"><h3>Multi-episode pilot</h3><p>The selected 128-episode Qwen3-Omni LoRA v6 diagnostic branch is verified with 4,032 held-out test predictions and 99.90% JSON validity. Action/subtask metrics are still weak, so this remains a baseline for error analysis.</p><a href="https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep">LoRA adapter</a></article>
2858
  <article class="artifact"><h3>Data boundary</h3><p>Raw MP4, HDF5, RRD files, private gated data, and full Qwen weights are not redistributed in this project.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/DATA_NOTICE.md">data notice</a></article>
2859
  <article class="artifact"><h3>Current project subset</h3><p>One public sample episode, 5,821 frames, 1,161 aligned windows, 8,546-dimensional task inputs, and no raw-data redistribution.</p><a href="data/modality_atlas.json">modality atlas</a></article>
2860
  <article class="artifact"><h3>Covered now</h3><p>Action/subtask labels, next-action prediction, temporal diagnostics, hand trajectory, contact, object relevance, caption grounding, retrieval, reconstruction, and misalignment.</p><a href="data/summary_metrics.json">summary metrics</a></article>
@@ -3364,7 +3364,7 @@
3364
  <article class="artifact"><h3>Reproducibility matrix</h3><p>Machine-readable command matrix covering sample download, baselines, 12 tasks, figures, and validation.</p><a href="data/reproducibility_matrix.json">reproducibility matrix</a></article>
3365
  <article class="artifact"><h3>Exact-match reproduction record</h3><p>The last metric rebuild reproduced the public-sample outputs from a fresh cache and matched the committed metrics.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/notes/reproducibility_audit.md">reproduction audit</a></article>
3366
  <article class="artifact"><h3>Project dashboard</h3><p>The website organizes the dataset sample, tasks, methods, results, directions, and scale-up path in one tabbed reader flow.</p><a href="#artifacts">project materials</a></article>
3367
- <article class="artifact"><h3>Multi-episode pilot status</h3><p>The comparison JSON now supports both the three-version reading and model-family grouping, so 1-episode and 128-episode entries can be compared within the same model family.</p><a href="data/omni_model_comparison.json">comparison</a></article>
3368
  </div>
3369
  <p class="repro-note">Minimal path: install the toolkit dependencies, download the official sample, run the 12-task suite with neural heads, regenerate visualizations, then rebuild the supporting project reports.</p>
3370
  <pre class="code-panel"><button type="button" data-copy="setup">Copy</button><code id="setup">git clone https://github.com/Ropedia/HOMIE-toolkit.git
 
2678
  <article class="evidence-card">
2679
  <span class="status-pill">verified diagnostic</span>
2680
  <h3>Qwen3-Omni and Cosmos3 branches</h3>
2681
+ <p>The selected 96/16/16 episode split now has a verified Qwen3-Omni v6 package with 4,032 held-out test predictions and 99.90% JSON validity. Cosmos3-Nano has 378 held-out future-window predictions, Cosmos3-Super Reasoner has 448 held-out base-weight JSON-task predictions, and Cosmos3-Super Forward-Dynamics LoRA has 448 held-out loss records.</p>
2682
  <div class="evidence-links">
2683
  <a href="data/omni_model_comparison.json">result comparison</a>
2684
  <a href="data/omni_finetune_verified_result.json">pilot result</a>
 
2854
  <article class="artifact primary-artifact"><div><h3>Official dataset</h3><p>Xperience-10M is a gated large-scale egocentric multimodal dataset for embodied AI, robotics, spatial intelligence, and world modeling.</p></div><a href="https://huggingface.co/datasets/ropedia-ai/xperience-10m">official HF dataset</a></article>
2855
  <article class="artifact"><h3>Public sample</h3><p>The current task suite is built from one public sample episode, not from the entire gated dataset.</p><a href="https://huggingface.co/datasets/ropedia-ai/xperience-10m-sample">sample dataset</a></article>
2856
  <article class="artifact"><h3>Modalities</h3><p>The sample exposes synchronized video, audio, depth, pose/SLAM, motion capture, inertial signals, calibration, and language annotations.</p><a href="data/modality_atlas.json">modality atlas</a></article>
2857
+ <article class="artifact"><h3>Multi-episode pilot</h3><p>The selected 128-episode Qwen3-Omni LoRA v6 diagnostic branch is verified with 4,032 held-out test predictions and 99.90% JSON validity. Action/subtask metrics are still weak, so this remains a baseline for error analysis.</p><a href="https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep">LoRA adapter</a><a href="data/qwen3_v5_v6_comparison.json">v5/v6 comparison</a></article>
2858
  <article class="artifact"><h3>Data boundary</h3><p>Raw MP4, HDF5, RRD files, private gated data, and full Qwen weights are not redistributed in this project.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/DATA_NOTICE.md">data notice</a></article>
2859
  <article class="artifact"><h3>Current project subset</h3><p>One public sample episode, 5,821 frames, 1,161 aligned windows, 8,546-dimensional task inputs, and no raw-data redistribution.</p><a href="data/modality_atlas.json">modality atlas</a></article>
2860
  <article class="artifact"><h3>Covered now</h3><p>Action/subtask labels, next-action prediction, temporal diagnostics, hand trajectory, contact, object relevance, caption grounding, retrieval, reconstruction, and misalignment.</p><a href="data/summary_metrics.json">summary metrics</a></article>
 
3364
  <article class="artifact"><h3>Reproducibility matrix</h3><p>Machine-readable command matrix covering sample download, baselines, 12 tasks, figures, and validation.</p><a href="data/reproducibility_matrix.json">reproducibility matrix</a></article>
3365
  <article class="artifact"><h3>Exact-match reproduction record</h3><p>The last metric rebuild reproduced the public-sample outputs from a fresh cache and matched the committed metrics.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/notes/reproducibility_audit.md">reproduction audit</a></article>
3366
  <article class="artifact"><h3>Project dashboard</h3><p>The website organizes the dataset sample, tasks, methods, results, directions, and scale-up path in one tabbed reader flow.</p><a href="#artifacts">project materials</a></article>
3367
+ <article class="artifact"><h3>Multi-episode pilot status</h3><p>The comparison JSON now supports both the three-version reading and model-family grouping, with Qwen3 v5/v6 detail kept as a separate machine-readable audit.</p><a href="data/omni_model_comparison.json">comparison</a><a href="data/qwen3_v5_v6_comparison.json">Qwen v5/v6</a></article>
3368
  </div>
3369
  <p class="repro-note">Minimal path: install the toolkit dependencies, download the official sample, run the 12-task suite with neural heads, regenerate visualizations, then rebuild the supporting project reports.</p>
3370
  <pre class="code-panel"><button type="button" data-copy="setup">Copy</button><code id="setup">git clone https://github.com/Ropedia/HOMIE-toolkit.git
index.html CHANGED
@@ -1996,9 +1996,108 @@
1996
  .bar span {
1997
  background: linear-gradient(90deg, var(--green), rgba(204, 255, 160, 0.45));
1998
  }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1999
  @media (max-width: 960px) {
2000
  .hero-inner, .two-col { grid-template-columns: 1fr; }
 
2001
  .hero-inner { min-height: 0; }
 
 
 
2002
  .project-tabs { grid-template-columns: repeat(3, minmax(0, 1fr)); }
2003
  .section-tabs { padding-top: 10px; }
2004
  .figure-brief { grid-template-columns: 1fr; }
@@ -2069,6 +2168,14 @@
2069
  }
2070
  main > section { scroll-margin-top: 112px; }
2071
  .hero-stats, .models, .task-grid, .artifact-grid, .evidence-grid, .reading-grid, .snapshot-grid, .roadmap-grid, .brief-grid, .boundary-strip, .chart-grid, .callout-row, .direction-grid, .baseline-strip, .extension-grid, .walk-flow, .flow-steps, .storyboard-steps, .task-selector, .atlas-rows { grid-template-columns: 1fr; }
 
 
 
 
 
 
 
 
2072
  .brief-panel { padding: 18px; }
2073
  .artifact-group { padding: 16px; }
2074
  .modality-atlas-panel { padding: 14px; }
@@ -2137,15 +2244,13 @@
2137
  <div class="wrap hero-inner">
2138
  <div>
2139
  <div class="eyebrow">public sample episode / multimodal task lab</div>
2140
- <h1>Ropedia Xperience-10M Research Task Lab.</h1>
2141
  <p class="hero-copy">
2142
- This project uses the public Xperience-10M sample from Ropedia to explore
2143
- embodied-AI task design, multimodal feature construction, lightweight
2144
- baselines, future Omni-model fine-tuning, and the long-term path toward
2145
- an Xperience-native embodied foundation model. It starts from the
2146
- sample episode available now, then keeps the same data contracts ready
2147
- for held-out multi-episode training when more Xperience-10M data is
2148
- prepared.
2149
  </p>
2150
  <div class="hero-actions">
2151
  <a class="button primary" href="research_roadmap.html">Open roadmap</a>
@@ -2160,7 +2265,7 @@
2160
  <div class="stat"><strong>12+12+4</strong><span>core, neural, and extension probes</span></div>
2161
  </div>
2162
  </div>
2163
- <div class="hero-panel" aria-label="Signal summary">
2164
  <div class="panel-top">
2165
  <span>current feature allocation</span>
2166
  <span>aligned window</span>
@@ -2236,7 +2341,7 @@
2236
  </article>
2237
  <article class="brief-card">
2238
  <strong>What comes next</strong>
2239
- <p>The next model-quality stage is a held-out episode pilot over selected multi-episode data, with no train/test episode leakage and a completed omni-model evaluation report.</p>
2240
  </article>
2241
  </div>
2242
  <div class="brief-grid" aria-label="Research capability map">
@@ -2254,7 +2359,7 @@
2254
  </article>
2255
  <article class="brief-card">
2256
  <strong>Scale-up readiness</strong>
2257
- <p>Connects the same data contract to 32/128-episode held-out pilots, Qwen3-Omni LoRA, Cosmos-style world modeling, policy-model branches, and the later Xperience-native pretraining goal.</p>
2258
  </article>
2259
  </div>
2260
  <div class="brief-actions">
@@ -2304,7 +2409,7 @@
2304
  <article class="snapshot-card">
2305
  <span class="status-pill">verified</span>
2306
  <h3>Dataset source alignment</h3>
2307
- <p>The public description is aligned to the official gated Xperience-10M dataset card, including modalities, scale, access, and current project coverage.</p>
2308
  <div class="snapshot-meta">
2309
  <span>full dataset <strong>gated</strong></span>
2310
  <span>sample scope <strong>1 episode</strong></span>
@@ -2314,7 +2419,7 @@
2314
  <article class="snapshot-card">
2315
  <span class="status-pill">verified</span>
2316
  <h3>Public research artifacts</h3>
2317
- <p>Metrics, figures, walkthroughs, baseline weights, and the Qwen3-Omni pilot status are packaged across GitHub, GitHub Pages, and Hugging Face.</p>
2318
  <div class="snapshot-meta">
2319
  <span>tasks <strong>12</strong></span>
2320
  <span>baselines <strong>minimal + neural</strong></span>
@@ -2327,8 +2432,18 @@
2327
  <p>The first selected-episode LoRA pilot is packaged with real held-out predictions and metrics. It proves the pipeline, while the weak scores make it a baseline for error analysis.</p>
2328
  <div class="snapshot-meta">
2329
  <span>split <strong>96 / 16 / 16</strong></span>
2330
- <span>test windows <strong>448</strong></span>
2331
- <span>JSON validity <strong>100.00%</strong></span>
 
 
 
 
 
 
 
 
 
 
2332
  </div>
2333
  </article>
2334
  <article class="snapshot-card gated">
@@ -2358,10 +2473,10 @@
2358
  <div class="wrap">
2359
  <div class="section-head">
2360
  <h2>Research roadmap.</h2>
2361
- <p>The project path moves from the current public-sample task lab to a final verified Qwen3-Omni diagnostic result, same-split 128-episode baseline alignment, action/subtask error analysis, robustness runs, world/policy branches, and the future Xperience Embodied Foundation Model pretraining goal.</p>
2362
  </div>
2363
  <div class="roadmap-grid" aria-label="Research roadmap stages">
2364
- <article class="roadmap-card" data-status="implemented_for_first_pilot">
2365
  <span class="roadmap-status">implemented</span>
2366
  <h3>Public-Sample Task Lab</h3>
2367
  <p>One public episode is converted into aligned windows, task contracts, minimal baselines, neural heads, walkthroughs, and figures.</p>
@@ -2370,7 +2485,7 @@
2370
  <strong>Evidence</strong><p>Status, protocol, takeaways, summary metrics, and episode-task outputs.</p>
2371
  </div>
2372
  </article>
2373
- <article class="roadmap-card" data-status="verified_baseline">
2374
  <span class="roadmap-status">implemented</span>
2375
  <h3>Multi-Episode Data Preparation</h3>
2376
  <p>Prepare official gated episodes while preserving episode-level separation and recording missing-view coverage. The first selected split is available for Qwen3-Omni diagnostics.</p>
@@ -2379,13 +2494,13 @@
2379
  <strong>Evidence</strong><p>Selected-episode plan, data boundary, preparation notes, and verified package summary.</p>
2380
  </div>
2381
  </article>
2382
- <article class="roadmap-card" data-status="implemented">
2383
- <span class="roadmap-status">verified baseline</span>
2384
- <h3>Qwen3-Omni LoRA Final Diagnostic Result</h3>
2385
  <p>Train lightweight adapters on selected prepared episodes and evaluate on held-out episodes with committed predictions, metrics, and run reports.</p>
2386
  <div class="roadmap-meta">
2387
  <strong>Entry</strong><p>Selected episodes prepared with no train/test episode leakage.</p>
2388
- <strong>Evidence</strong><p>Verified result summary, dataset manifest, training metadata, progress logs, metrics, and predictions.</p>
2389
  </div>
2390
  </article>
2391
  <article class="roadmap-card" data-status="verified_companion_result">
@@ -2397,6 +2512,15 @@
2397
  <strong>Evidence</strong><p>Baseline alignment report, summary metrics, task metrics, and the 128-task baseline runner.</p>
2398
  </div>
2399
  </article>
 
 
 
 
 
 
 
 
 
2400
  <article class="roadmap-card" data-status="active_next_step">
2401
  <span class="roadmap-status">active next step</span>
2402
  <h3>Action/Subtask Error-Analysis Pass</h3>
@@ -2406,17 +2530,17 @@
2406
  <strong>Evidence</strong><p>Updated quality-target report, error-analysis tables, held-out metrics, and public-safe package.</p>
2407
  </div>
2408
  </article>
2409
- <article class="roadmap-card" data-status="next">
2410
- <span class="roadmap-status">next</span>
2411
  <h3>Foundation-Model Selection Matrix</h3>
2412
- <p>Keep Qwen3-Omni as the first trainable held-out pilot, add Cosmos 3 for world modeling, and stage policy candidates after action targets are explicit.</p>
2413
  <div class="roadmap-meta">
2414
  <strong>Entry</strong><p>Completed 128-episode preparation or a smaller 3-8 episode preprocessing dry run.</p>
2415
  <strong>Evidence</strong><p>Foundation model plan, source links, model-specific entry conditions, and evaluation additions.</p>
2416
  </div>
2417
  </article>
2418
- <article class="roadmap-card" data-status="planned">
2419
- <span class="roadmap-status">planned</span>
2420
  <h3>64-128 Episode Robustness Run</h3>
2421
  <p>Test whether pilot conclusions survive broader sessions, missing modalities, and stronger ablations.</p>
2422
  <div class="roadmap-meta">
@@ -2449,6 +2573,7 @@
2449
  <a href="data/research_roadmap.json">roadmap stages</a>
2450
  <a href="data/foundation_model_plan.json">foundation model plan</a>
2451
  <a href="data/additional_development_directions.json">additional directions</a>
 
2452
  <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/XPERIENCE_EMBODIED_FOUNDATION_MODEL_PRETRAINING.md">native pretraining plan</a>
2453
  <a href="data/research_roadmap_interactive.json">interactive map</a>
2454
  <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/results/omni_finetune/DATA_ACCESS_STATUS.md">scale-up status</a>
@@ -2488,8 +2613,9 @@
2488
  <article class="artifact"><h3>Metric contract</h3><p>All 12 tasks list input, target, primary metric, minimal baseline score, and neural MLP score from committed result files.</p><a href="data/summary_metrics.json">summary metrics</a></article>
2489
  <article class="artifact"><h3>Leakage controls</h3><p>Scalers fit on train windows only; future labels, target-side signals, caption/object labels, and contact labels stay on the target side unless explicitly queried.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/scripts/build_evaluation_protocol.py">builder script</a></article>
2490
  <article class="artifact"><h3>Audio ablation</h3><p>Audio and no-audio variants are evaluated across all 12 task contracts under the same chronological split.</p><a href="data/audio_ablation_summary.json">audio summary</a></article>
2491
- <article class="artifact"><h3>Foundation branch selection</h3><p>Qwen3-Omni is the first trainable baseline, Cosmos 3 becomes the world-model branch, policy models wait for explicit action targets, and Xperience-native pretraining remains a later full-corpus goal.</p><a href="data/foundation_model_plan.json">backbone plan</a></article>
2492
- <article class="artifact"><h3>Next evaluation stage</h3><p>This public-sample run covers single-episode task development. The selected multi-episode Qwen3-Omni final diagnostic result is verified and meets the JSON-validity target; Cosmos3-Nano has a verified future-window compatibility package; and Cosmos3-Super has a verified base-weight Reasoner JSON-task evaluation. The next stage is action/subtask error analysis, true Cosmos fine-tuning, and policy-target conversion.</p><a href="data/omni_model_comparison.json">result comparison</a></article>
 
2493
  <article class="artifact"><h3>Scale-up requirement</h3><p>Future Omni, Cosmos, and policy branches use the same episode split discipline, training metadata, held-out predictions, metrics, run report, and public-safe package gate.</p><a href="data/foundation_model_plan.json">scale-up status</a></article>
2494
  </div>
2495
  </div>
@@ -2542,7 +2668,7 @@
2542
  <article class="evidence-card">
2543
  <span class="status-pill">current plan</span>
2544
  <h3>Foundation backbones are separated by role</h3>
2545
- <p>Qwen3-Omni stays first for held-out LoRA; Cosmos 3 is the world-model branch; OpenVLA/openpi/GR00T are policy candidates after action-space conversion; Xperience-native pretraining is the later full-corpus goal.</p>
2546
  <div class="evidence-links">
2547
  <a href="data/foundation_model_plan.json">foundation model plan</a>
2548
  <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/FOUNDATION_MODEL_PLAN.md">plan doc</a>
@@ -2552,13 +2678,23 @@
2552
  <article class="evidence-card">
2553
  <span class="status-pill">verified diagnostic</span>
2554
  <h3>Qwen3-Omni and Cosmos3 branches</h3>
2555
- <p>The selected 96/16/16 episode split produced verified Qwen3-Omni packages with 448 held-out test predictions. Cosmos3-Nano has 378 held-out future-window predictions, and Cosmos3-Super Reasoner has 448 held-out base-weight JSON-task predictions.</p>
2556
  <div class="evidence-links">
2557
  <a href="data/omni_model_comparison.json">result comparison</a>
2558
  <a href="data/omni_finetune_verified_result.json">pilot result</a>
2559
  <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/tree/main/results/omni_finetune/verified_public">verified package</a>
2560
  </div>
2561
  </article>
 
 
 
 
 
 
 
 
 
 
2562
  <article class="evidence-card">
2563
  <span class="status-pill">verified</span>
2564
  <h3>Multi-episode pilot status is explicit</h3>
@@ -2688,9 +2824,20 @@
2688
  <a href="data/project_packet.json">reader path</a>
2689
  </div>
2690
  </article>
 
 
 
 
 
 
 
 
 
 
2691
  </div>
2692
  <div class="boundary-strip">
2693
  <div class="boundary-item"><strong>Verified now</strong><span>One public episode, 5,821 frames, 1,161 aligned windows, 8,546 dimensions, 12 minimal heads, 12 neural heads, and 4 direction-extension probes.</span></div>
 
2694
  <div class="boundary-item"><strong>Next: error analysis</strong><span>The selected 128-episode Qwen3-Omni LoRA result has a final verified diagnostic package; JSON validity meets target, and the next pass should improve action/subtask quality.</span></div>
2695
  <div class="boundary-item"><strong>Not redistributed</strong><span>Raw videos, raw annotations, full Qwen weights, and private gated Xperience-10M data are not included in the public repo or HF bundles.</span></div>
2696
  </div>
@@ -2701,13 +2848,13 @@
2701
  <div class="wrap">
2702
  <div class="section-head">
2703
  <h2>Aligned with the official dataset card.</h2>
2704
- <p>The official Xperience-10M card describes a gated, large-scale 4D egocentric multimodal dataset. This project records that full upstream scope while focusing the implemented artifacts on one public sample episode.</p>
2705
  </div>
2706
  <div class="artifact-grid">
2707
  <article class="artifact primary-artifact"><div><h3>Official dataset</h3><p>Xperience-10M is a gated large-scale egocentric multimodal dataset for embodied AI, robotics, spatial intelligence, and world modeling.</p></div><a href="https://huggingface.co/datasets/ropedia-ai/xperience-10m">official HF dataset</a></article>
2708
  <article class="artifact"><h3>Public sample</h3><p>The current task suite is built from one public sample episode, not from the entire gated dataset.</p><a href="https://huggingface.co/datasets/ropedia-ai/xperience-10m-sample">sample dataset</a></article>
2709
  <article class="artifact"><h3>Modalities</h3><p>The sample exposes synchronized video, audio, depth, pose/SLAM, motion capture, inertial signals, calibration, and language annotations.</p><a href="data/modality_atlas.json">modality atlas</a></article>
2710
- <article class="artifact"><h3>Multi-episode pilot</h3><p>The selected 128-episode Qwen3-Omni LoRA strict-label v3 diagnostic result is verified with 448 held-out test predictions and 100.00% JSON validity. Action/subtask metrics are still weak, so this remains a baseline for error analysis.</p><a href="https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep">LoRA adapter</a></article>
2711
  <article class="artifact"><h3>Data boundary</h3><p>Raw MP4, HDF5, RRD files, private gated data, and full Qwen weights are not redistributed in this project.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/DATA_NOTICE.md">data notice</a></article>
2712
  <article class="artifact"><h3>Current project subset</h3><p>One public sample episode, 5,821 frames, 1,161 aligned windows, 8,546-dimensional task inputs, and no raw-data redistribution.</p><a href="data/modality_atlas.json">modality atlas</a></article>
2713
  <article class="artifact"><h3>Covered now</h3><p>Action/subtask labels, next-action prediction, temporal diagnostics, hand trajectory, contact, object relevance, caption grounding, retrieval, reconstruction, and misalignment.</p><a href="data/summary_metrics.json">summary metrics</a></article>
@@ -3157,10 +3304,11 @@
3157
  </div>
3158
  <div class="artifact-grid">
3159
  <article class="artifact primary-artifact"><div><h3>Model-family comparison</h3><p>Compares the three result layers and also groups 1-episode and 128-episode entries by model family: task heads, Qwen3-Omni LoRA, Cosmos3-Nano, and Cosmos3-Super.</p></div><a href="data/omni_model_comparison.json">result comparison</a></article>
 
3160
  <article class="artifact"><h3>Foundation-model plan</h3><p>Backbone selection matrix covering Qwen3-Omni, Cosmos 3, GR00T, OpenVLA/openpi, Gemini Robotics, Octo, SmolVLA-style policy candidates, and the future Xperience-native pretraining goal.</p><a href="data/foundation_model_plan.json">foundation model plan</a></article>
3161
  <article class="artifact"><h3>Multi-episode data access</h3><p>Public data-access path, selected 128-episode pilot plan, and preparation requirements.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/results/omni_finetune/MULTI_EPISODE_ACCESS_STATUS.md">data access</a></article>
3162
  <article class="artifact"><h3>Qwen3-Omni LoRA group</h3><p>Separates the 1-episode sensor-adapter smoke test from the current 128-episode LoRA adapter package and older diagnostics.</p><a href="data/omni_model_comparison.json">Qwen group</a></article>
3163
- <article class="artifact"><h3>Cosmos3 groups</h3><p>Shows the verified Nano future-window compatibility package and the Super base-weight Reasoner JSON-task evaluation; neither is a new fine-tuned Cosmos weight release.</p><a href="data/omni_model_comparison.json">Cosmos groups</a></article>
3164
  <article class="artifact"><h3>Scale-up requirement</h3><p>Future runs need validation tracking, held-out predictions, quality-target reporting, and the same public-safe package gate.</p><a href="data/foundation_model_plan.json">training requirements</a></article>
3165
  <article class="artifact"><h3>Xperience-native pretraining</h3><p>Future plan for a domain-specific embodied foundation model trained from scratch over full-corpus video, audio, geometry, motion, inertial, and language streams.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/XPERIENCE_EMBODIED_FOUNDATION_MODEL_PRETRAINING.md">pretraining plan</a></article>
3166
  </div>
@@ -3191,14 +3339,15 @@
3191
  <section id="omni-scale-up" data-project-tab="resources" role="tabpanel" aria-labelledby="tab-resources" tabindex="-1">
3192
  <div class="wrap">
3193
  <div class="section-head">
3194
- <h2>Qwen3-Omni diagnostic pilot is verified.</h2>
3195
- <p>The selected pilot uses 128 source-balanced episodes across 128 different session UUIDs. The first held-out package is verified, and its weak metrics define the next structured-output and error-analysis pass.</p>
3196
  </div>
3197
  <div class="artifact-grid">
3198
  <article class="artifact"><h3>Selection</h3><p>128 complete episodes selected from 128 unique top-level sessions, balanced across episode-size bands and split 96/16/16 for train/val/test.</p></article>
3199
  <article class="artifact"><h3>Transfer</h3><p>Download raw episodes only from official gated sources, exclude visualization.rrd, validate files, then stage them for training.</p></article>
3200
- <article class="artifact"><h3>Current LoRA artifact</h3><p>The current Qwen3-Omni LoRA artifact is the selected 128-episode diagnostic adapter. The 1-episode Qwen entry is only a sensor-adapter smoke test.</p><a href="data/omni_model_comparison.json">model groups</a></article>
3201
- <article class="artifact"><h3>Backbone branches</h3><p>Qwen3-Omni uses a separate LoRA model repo; Cosmos3-Nano and Cosmos3-Super remain artifacts-only diagnostics until real Cosmos adapter or fine-tuned weights exist.</p><a href="data/foundation_model_plan.json">backbone plan</a></article>
 
3202
  <article class="artifact"><h3>Native foundation model</h3><p>The long-term goal is a full-corpus Xperience Embodied Foundation Model trained on synchronized perception, geometry, motion, inertial, audio, and language streams after smaller scaling stages validate the approach.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/XPERIENCE_EMBODIED_FOUNDATION_MODEL_PRETRAINING.md">pretraining plan</a></article>
3203
  </div>
3204
  </div>
@@ -3215,7 +3364,7 @@
3215
  <article class="artifact"><h3>Reproducibility matrix</h3><p>Machine-readable command matrix covering sample download, baselines, 12 tasks, figures, and validation.</p><a href="data/reproducibility_matrix.json">reproducibility matrix</a></article>
3216
  <article class="artifact"><h3>Exact-match reproduction record</h3><p>The last metric rebuild reproduced the public-sample outputs from a fresh cache and matched the committed metrics.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/notes/reproducibility_audit.md">reproduction audit</a></article>
3217
  <article class="artifact"><h3>Project dashboard</h3><p>The website organizes the dataset sample, tasks, methods, results, directions, and scale-up path in one tabbed reader flow.</p><a href="#artifacts">project materials</a></article>
3218
- <article class="artifact"><h3>Multi-episode pilot status</h3><p>The comparison JSON now supports both the three-version reading and model-family grouping, so 1-episode and 128-episode entries can be compared within the same model family.</p><a href="data/omni_model_comparison.json">comparison</a></article>
3219
  </div>
3220
  <p class="repro-note">Minimal path: install the toolkit dependencies, download the official sample, run the 12-task suite with neural heads, regenerate visualizations, then rebuild the supporting project reports.</p>
3221
  <pre class="code-panel"><button type="button" data-copy="setup">Copy</button><code id="setup">git clone https://github.com/Ropedia/HOMIE-toolkit.git
@@ -3250,7 +3399,7 @@ python scripts/validate_publication_package.py</code></pre>
3250
 
3251
  <footer>
3252
  <div class="wrap">
3253
- Built as a single-episode embodied-AI learning lab, with the next stage focused on multi-episode training and held-out episode evaluation.
3254
  </div>
3255
  </footer>
3256
 
 
1996
  .bar span {
1997
  background: linear-gradient(90deg, var(--green), rgba(204, 255, 160, 0.45));
1998
  }
1999
+ /* Product-design polish: align with ropedia.com through real project visuals,
2000
+ restrained surfaces, and a clear first-viewport research story. */
2001
+ body {
2002
+ background: #020502;
2003
+ }
2004
+ .hero {
2005
+ position: relative;
2006
+ overflow: hidden;
2007
+ min-height: min(760px, calc(100vh - 24px));
2008
+ background: #020502;
2009
+ isolation: isolate;
2010
+ }
2011
+ .hero::before {
2012
+ content: "";
2013
+ position: absolute;
2014
+ inset: 0;
2015
+ z-index: -2;
2016
+ background:
2017
+ linear-gradient(90deg, rgba(2, 5, 2, 0.96) 0%, rgba(2, 5, 2, 0.86) 42%, rgba(2, 5, 2, 0.58) 72%, rgba(2, 5, 2, 0.88) 100%),
2018
+ linear-gradient(180deg, rgba(2, 5, 2, 0.10) 0%, rgba(2, 5, 2, 0.82) 100%),
2019
+ url("assets/task_suite_infographic.png?v=xperience10m-taskfirst-v13-modality-xl") center right / cover no-repeat;
2020
+ opacity: 0.92;
2021
+ }
2022
+ .hero::after {
2023
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2024
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2025
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2026
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2027
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2028
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2029
+ pointer-events: none;
2030
+ }
2031
+ .hero-inner {
2032
+ position: relative;
2033
+ min-height: min(760px, calc(100vh - 24px));
2034
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2035
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2036
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2037
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2038
+ .hero-inner > div:first-child {
2039
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2040
+ }
2041
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2042
+ max-width: 940px;
2043
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2044
+ }
2045
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2046
+ max-width: 760px;
2047
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2048
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2049
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2050
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2051
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2052
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2053
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2054
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2055
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2056
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2057
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2058
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2059
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2060
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2061
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2062
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2063
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2064
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2065
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2066
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2067
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2068
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2069
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2070
+ }
2071
+ .signal {
2072
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2073
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2074
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2075
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2076
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2077
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2078
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2079
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2080
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2081
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2082
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2083
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2084
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2085
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2086
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2087
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2088
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2089
+ }
2090
+ .track {
2091
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2092
+ height: 6px;
2093
+ }
2094
  @media (max-width: 960px) {
2095
  .hero-inner, .two-col { grid-template-columns: 1fr; }
2096
+ .hero,
2097
  .hero-inner { min-height: 0; }
2098
+ .hero-inner { padding: 76px 0 58px; }
2099
+ .hero-panel { grid-template-columns: repeat(2, minmax(0, 1fr)); }
2100
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2101
  .project-tabs { grid-template-columns: repeat(3, minmax(0, 1fr)); }
2102
  .section-tabs { padding-top: 10px; }
2103
  .figure-brief { grid-template-columns: 1fr; }
 
2168
  }
2169
  main > section { scroll-margin-top: 112px; }
2170
  .hero-stats, .models, .task-grid, .artifact-grid, .evidence-grid, .reading-grid, .snapshot-grid, .roadmap-grid, .brief-grid, .boundary-strip, .chart-grid, .callout-row, .direction-grid, .baseline-strip, .extension-grid, .walk-flow, .flow-steps, .storyboard-steps, .task-selector, .atlas-rows { grid-template-columns: 1fr; }
2171
+ .hero::before {
2172
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2173
+ linear-gradient(180deg, rgba(2, 5, 2, 0.92) 0%, rgba(2, 5, 2, 0.76) 48%, rgba(2, 5, 2, 0.96) 100%),
2174
+ url("assets/task_suite_infographic.png?v=xperience10m-taskfirst-v13-modality-xl") center / cover no-repeat;
2175
+ }
2176
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2177
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2178
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2179
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2180
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2181
  .modality-atlas-panel { padding: 14px; }
 
2244
  <div class="wrap hero-inner">
2245
  <div>
2246
  <div class="eyebrow">public sample episode / multimodal task lab</div>
2247
+ <h1>Ropedia Xperience-10M Task Suite.</h1>
2248
  <p class="hero-copy">
2249
+ A public research surface for physical 4D intelligence: sample-to-task
2250
+ contracts, multimodal baselines, verified multi-episode Qwen3-Omni
2251
+ results, and a clear path toward Xperience-native foundation models.
2252
+ Public raw-data boundaries stay explicit while private staged-GPU
2253
+ reproduction paths keep the latest model evidence recoverable.
 
 
2254
  </p>
2255
  <div class="hero-actions">
2256
  <a class="button primary" href="research_roadmap.html">Open roadmap</a>
 
2265
  <div class="stat"><strong>12+12+4</strong><span>core, neural, and extension probes</span></div>
2266
  </div>
2267
  </div>
2268
+ <div class="hero-panel" aria-label="Feature allocation summary">
2269
  <div class="panel-top">
2270
  <span>current feature allocation</span>
2271
  <span>aligned window</span>
 
2341
  </article>
2342
  <article class="brief-card">
2343
  <strong>What comes next</strong>
2344
+ <p>The next model-quality stage is stronger action/subtask modeling on the same held-out split, using dense/multiscale windows before requiring more raw episodes.</p>
2345
  </article>
2346
  </div>
2347
  <div class="brief-grid" aria-label="Research capability map">
 
2359
  </article>
2360
  <article class="brief-card">
2361
  <strong>Scale-up readiness</strong>
2362
+ <p>Connects the same data contract to 128-episode baselines, a no-new-episode enhancement pack, Qwen3-Omni LoRA, Cosmos-style world modeling, policy-model branches, and the later Xperience-native pretraining goal.</p>
2363
  </article>
2364
  </div>
2365
  <div class="brief-actions">
 
2409
  <article class="snapshot-card">
2410
  <span class="status-pill">verified</span>
2411
  <h3>Dataset source alignment</h3>
2412
+ <p>The public description is aligned to the official gated Xperience-10M dataset card, including modalities, scale, access, and current project coverage. The source snapshot records 31.9 TB on the HF surface, an about-1PB full-scale storage statement, 12,103 episode folders as upstream metadata, not a local data inventory, public sample license cc-by-nc-4.0, HOMIE Toolkit and Rerun 0.29.0 source tooling, and the official limited diversity note. See data/source_alignment_audit.json.</p>
2413
  <div class="snapshot-meta">
2414
  <span>full dataset <strong>gated</strong></span>
2415
  <span>sample scope <strong>1 episode</strong></span>
 
2419
  <article class="snapshot-card">
2420
  <span class="status-pill">verified</span>
2421
  <h3>Public research artifacts</h3>
2422
+ <p>Metrics, figures, walkthroughs, baseline weights, Qwen3-Omni results, and Cosmos3 public-safe packages are staged across GitHub, GitHub Pages, and Hugging Face.</p>
2423
  <div class="snapshot-meta">
2424
  <span>tasks <strong>12</strong></span>
2425
  <span>baselines <strong>minimal + neural</strong></span>
 
2432
  <p>The first selected-episode LoRA pilot is packaged with real held-out predictions and metrics. It proves the pipeline, while the weak scores make it a baseline for error analysis.</p>
2433
  <div class="snapshot-meta">
2434
  <span>split <strong>96 / 16 / 16</strong></span>
2435
+ <span>test windows <strong>4,032</strong></span>
2436
+ <span>JSON validity <strong>99.90%</strong></span>
2437
+ </div>
2438
+ </article>
2439
+ <article class="snapshot-card gated">
2440
+ <span class="status-pill">current plan</span>
2441
+ <h3>128-Episode Task Suite Enhancement Pack</h3>
2442
+ <p>Shows how the current selected split can be stressed without more episodes: dense windows, hierarchical labels, raw-feature shards, and `multiscale_20s10_40s20_80s40` as the next export target.</p>
2443
+ <div class="snapshot-meta">
2444
+ <span>current windows <strong>3,808</strong></span>
2445
+ <span>multiscale estimate <strong>106,095</strong></span>
2446
+ <span>data file <strong>task_suite_enhancement_128.json</strong></span>
2447
  </div>
2448
  </article>
2449
  <article class="snapshot-card gated">
 
2473
  <div class="wrap">
2474
  <div class="section-head">
2475
  <h2>Research roadmap.</h2>
2476
+ <p>The project path moves from the current public-sample task lab to the latest verified Qwen3-Omni diagnostic branch, same-split 128-episode baseline alignment, a no-new-episode enhancement pack, action/subtask error analysis, robustness runs, world/policy branches, and the future Xperience Embodied Foundation Model pretraining goal.</p>
2477
  </div>
2478
  <div class="roadmap-grid" aria-label="Research roadmap stages">
2479
+ <article class="roadmap-card" data-status="implemented">
2480
  <span class="roadmap-status">implemented</span>
2481
  <h3>Public-Sample Task Lab</h3>
2482
  <p>One public episode is converted into aligned windows, task contracts, minimal baselines, neural heads, walkthroughs, and figures.</p>
 
2485
  <strong>Evidence</strong><p>Status, protocol, takeaways, summary metrics, and episode-task outputs.</p>
2486
  </div>
2487
  </article>
2488
+ <article class="roadmap-card" data-status="implemented_for_first_pilot">
2489
  <span class="roadmap-status">implemented</span>
2490
  <h3>Multi-Episode Data Preparation</h3>
2491
  <p>Prepare official gated episodes while preserving episode-level separation and recording missing-view coverage. The first selected split is available for Qwen3-Omni diagnostics.</p>
 
2494
  <strong>Evidence</strong><p>Selected-episode plan, data boundary, preparation notes, and verified package summary.</p>
2495
  </div>
2496
  </article>
2497
+ <article class="roadmap-card" data-status="verified_latest_branch">
2498
+ <span class="roadmap-status">verified latest branch</span>
2499
+ <h3>Qwen3-Omni LoRA Latest Diagnostic Branch</h3>
2500
  <p>Train lightweight adapters on selected prepared episodes and evaluate on held-out episodes with committed predictions, metrics, and run reports.</p>
2501
  <div class="roadmap-meta">
2502
  <strong>Entry</strong><p>Selected episodes prepared with no train/test episode leakage.</p>
2503
+ <strong>Evidence</strong><p>Verified result summary, v5/v6 comparison, dataset manifest, training metadata, progress logs, metrics, and predictions.</p>
2504
  </div>
2505
  </article>
2506
  <article class="roadmap-card" data-status="verified_companion_result">
 
2512
  <strong>Evidence</strong><p>Baseline alignment report, summary metrics, task metrics, and the 128-task baseline runner.</p>
2513
  </div>
2514
  </article>
2515
+ <article class="roadmap-card" data-status="current">
2516
+ <span class="roadmap-status">current no-new-episode plan</span>
2517
+ <h3>128-Episode Task Suite Enhancement Pack</h3>
2518
+ <p>Use the same selected split, estimate dense/multiscale window exports, define hierarchical action/subtask targets, and prioritize raw-feature shards for tasks that metadata baselines cannot cover.</p>
2519
+ <div class="roadmap-meta">
2520
+ <strong>Entry</strong><p>Current 3,808-window selected 96/16/16 export and verified Qwen v4 metrics.</p>
2521
+ <strong>Evidence</strong><p>TASK_SUITE_ENHANCEMENT_128.md, task_suite_enhancement_128.json, dense-window CSV, and the enhancement builder script.</p>
2522
+ </div>
2523
+ </article>
2524
  <article class="roadmap-card" data-status="active_next_step">
2525
  <span class="roadmap-status">active next step</span>
2526
  <h3>Action/Subtask Error-Analysis Pass</h3>
 
2530
  <strong>Evidence</strong><p>Updated quality-target report, error-analysis tables, held-out metrics, and public-safe package.</p>
2531
  </div>
2532
  </article>
2533
+ <article class="roadmap-card" data-status="current">
2534
+ <span class="roadmap-status">current</span>
2535
  <h3>Foundation-Model Selection Matrix</h3>
2536
+ <p>Keep Qwen3-Omni as the first trainable held-out pilot, use Cosmos 3 for world modeling and forward-dynamics trainer development, and stage policy candidates after robot-compatible action targets are explicit.</p>
2537
  <div class="roadmap-meta">
2538
  <strong>Entry</strong><p>Completed 128-episode preparation or a smaller 3-8 episode preprocessing dry run.</p>
2539
  <strong>Evidence</strong><p>Foundation model plan, source links, model-specific entry conditions, and evaluation additions.</p>
2540
  </div>
2541
  </article>
2542
+ <article class="roadmap-card" data-status="partially_implemented">
2543
+ <span class="roadmap-status">partially implemented</span>
2544
  <h3>64-128 Episode Robustness Run</h3>
2545
  <p>Test whether pilot conclusions survive broader sessions, missing modalities, and stronger ablations.</p>
2546
  <div class="roadmap-meta">
 
2573
  <a href="data/research_roadmap.json">roadmap stages</a>
2574
  <a href="data/foundation_model_plan.json">foundation model plan</a>
2575
  <a href="data/additional_development_directions.json">additional directions</a>
2576
+ <a href="data/task_suite_enhancement_128.json">task_suite_enhancement_128.json</a>
2577
  <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/XPERIENCE_EMBODIED_FOUNDATION_MODEL_PRETRAINING.md">native pretraining plan</a>
2578
  <a href="data/research_roadmap_interactive.json">interactive map</a>
2579
  <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/results/omni_finetune/DATA_ACCESS_STATUS.md">scale-up status</a>
 
2613
  <article class="artifact"><h3>Metric contract</h3><p>All 12 tasks list input, target, primary metric, minimal baseline score, and neural MLP score from committed result files.</p><a href="data/summary_metrics.json">summary metrics</a></article>
2614
  <article class="artifact"><h3>Leakage controls</h3><p>Scalers fit on train windows only; future labels, target-side signals, caption/object labels, and contact labels stay on the target side unless explicitly queried.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/scripts/build_evaluation_protocol.py">builder script</a></article>
2615
  <article class="artifact"><h3>Audio ablation</h3><p>Audio and no-audio variants are evaluated across all 12 task contracts under the same chronological split.</p><a href="data/audio_ablation_summary.json">audio summary</a></article>
2616
+ <article class="artifact"><h3>Foundation branch selection</h3><p>Qwen3-Omni is the first trainable baseline, Cosmos 3 becomes the world-model branch with a camera-pose proxy forward-dynamics contract ready for trainer work, policy models wait for robot-compatible action targets, and Xperience-native pretraining remains a later full-corpus goal.</p><a href="data/foundation_model_plan.json">backbone plan</a></article>
2617
+ <article class="artifact"><h3>Next evaluation stage</h3><p>This public-sample run covers single-episode task development. The selected multi-episode Qwen3-Omni final diagnostic result is verified and meets the JSON-validity target; Cosmos3-Nano has a verified future-window compatibility package; and Cosmos3-Super has a verified base-weight JSON-task evaluation plus a fine-tuned forward-dynamics LoRA branch. The next stage is action/subtask error analysis, stronger model-quality runs, and policy-target conversion.</p><a href="data/omni_model_comparison.json">result comparison</a></article>
2618
+ <article class="artifact"><h3>128-Episode Task Suite Enhancement Pack</h3><p>Before adding episodes, the suite should try `multiscale_20s10_40s20_80s40`, hierarchical action/subtask targets, label-normalized scoring, and compact raw-feature shards for unsupported tasks.</p><a href="data/task_suite_enhancement_128.json">task_suite_enhancement_128.json</a></article>
2619
  <article class="artifact"><h3>Scale-up requirement</h3><p>Future Omni, Cosmos, and policy branches use the same episode split discipline, training metadata, held-out predictions, metrics, run report, and public-safe package gate.</p><a href="data/foundation_model_plan.json">scale-up status</a></article>
2620
  </div>
2621
  </div>
 
2668
  <article class="evidence-card">
2669
  <span class="status-pill">current plan</span>
2670
  <h3>Foundation backbones are separated by role</h3>
2671
+ <p>Qwen3-Omni stays first for held-out LoRA; Cosmos 3 is the world-model branch with camera-pose proxy forward-dynamics targets ready for trainer work; OpenVLA/openpi/GR00T are policy candidates after robot-compatible action conversion; Xperience-native pretraining is the later full-corpus goal.</p>
2672
  <div class="evidence-links">
2673
  <a href="data/foundation_model_plan.json">foundation model plan</a>
2674
  <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/FOUNDATION_MODEL_PLAN.md">plan doc</a>
 
2678
  <article class="evidence-card">
2679
  <span class="status-pill">verified diagnostic</span>
2680
  <h3>Qwen3-Omni and Cosmos3 branches</h3>
2681
+ <p>The selected 96/16/16 episode split now has a verified Qwen3-Omni v6 package with 4,032 held-out test predictions and 99.90% JSON validity. Cosmos3-Nano has 378 held-out future-window predictions, Cosmos3-Super Reasoner has 448 held-out base-weight JSON-task predictions, and Cosmos3-Super Forward-Dynamics LoRA has 448 held-out loss records.</p>
2682
  <div class="evidence-links">
2683
  <a href="data/omni_model_comparison.json">result comparison</a>
2684
  <a href="data/omni_finetune_verified_result.json">pilot result</a>
2685
  <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/tree/main/results/omni_finetune/verified_public">verified package</a>
2686
  </div>
2687
  </article>
2688
+ <article class="evidence-card">
2689
+ <span class="status-pill">current plan</span>
2690
+ <h3>128-Episode Task Suite Enhancement Pack</h3>
2691
+ <p>The current 3,808-window export can be expanded through dense/multiscale windows without changing the held-out episode split; the recommended scenario is `multiscale_20s10_40s20_80s40`.</p>
2692
+ <div class="evidence-links">
2693
+ <a href="data/task_suite_enhancement_128.json">task_suite_enhancement_128.json</a>
2694
+ <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/TASK_SUITE_ENHANCEMENT_128.md">enhancement report</a>
2695
+ <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/results/omni_finetune/task_suite_enhancement_128_v1_20260608/dense_window_scenarios.csv">dense scenarios</a>
2696
+ </div>
2697
+ </article>
2698
  <article class="evidence-card">
2699
  <span class="status-pill">verified</span>
2700
  <h3>Multi-episode pilot status is explicit</h3>
 
2824
  <a href="data/project_packet.json">reader path</a>
2825
  </div>
2826
  </article>
2827
+ <article class="reading-card">
2828
+ <span class="step-index">05</span>
2829
+ <h3>Push the current 128 episodes harder</h3>
2830
+ <p>Use the no-new-episode enhancement pack before requesting more storage: it records dense-window estimates, `multiscale_20s10_40s20_80s40`, hierarchical labels, and raw-feature shard priorities.</p>
2831
+ <div class="reading-links">
2832
+ <a href="data/task_suite_enhancement_128.json">task_suite_enhancement_128.json</a>
2833
+ <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/TASK_SUITE_ENHANCEMENT_128.md">enhancement report</a>
2834
+ <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/scripts/omni/build_task_suite_enhancement_128.py">builder script</a>
2835
+ </div>
2836
+ </article>
2837
  </div>
2838
  <div class="boundary-strip">
2839
  <div class="boundary-item"><strong>Verified now</strong><span>One public episode, 5,821 frames, 1,161 aligned windows, 8,546 dimensions, 12 minimal heads, 12 neural heads, and 4 direction-extension probes.</span></div>
2840
+ <div class="boundary-item"><strong>Next: no-new-episode scale</strong><span>The selected 128-episode suite should next use dense/multiscale windows, hierarchical labels, and raw-feature shards before adding more episodes.</span></div>
2841
  <div class="boundary-item"><strong>Next: error analysis</strong><span>The selected 128-episode Qwen3-Omni LoRA result has a final verified diagnostic package; JSON validity meets target, and the next pass should improve action/subtask quality.</span></div>
2842
  <div class="boundary-item"><strong>Not redistributed</strong><span>Raw videos, raw annotations, full Qwen weights, and private gated Xperience-10M data are not included in the public repo or HF bundles.</span></div>
2843
  </div>
 
2848
  <div class="wrap">
2849
  <div class="section-head">
2850
  <h2>Aligned with the official dataset card.</h2>
2851
+ <p>The official Xperience-10M card describes a gated, large-scale 4D egocentric multimodal dataset. This project records that full upstream scope while focusing the implemented artifacts on one public sample episode. The source-alignment record keeps 31.9 TB, about-1PB, 12,103 episode folders, cc-by-nc-4.0, HOMIE Toolkit, Rerun 0.29.0, not a local data inventory, limited diversity, and data/source_alignment_audit.json visible on the public site.</p>
2852
  </div>
2853
  <div class="artifact-grid">
2854
  <article class="artifact primary-artifact"><div><h3>Official dataset</h3><p>Xperience-10M is a gated large-scale egocentric multimodal dataset for embodied AI, robotics, spatial intelligence, and world modeling.</p></div><a href="https://huggingface.co/datasets/ropedia-ai/xperience-10m">official HF dataset</a></article>
2855
  <article class="artifact"><h3>Public sample</h3><p>The current task suite is built from one public sample episode, not from the entire gated dataset.</p><a href="https://huggingface.co/datasets/ropedia-ai/xperience-10m-sample">sample dataset</a></article>
2856
  <article class="artifact"><h3>Modalities</h3><p>The sample exposes synchronized video, audio, depth, pose/SLAM, motion capture, inertial signals, calibration, and language annotations.</p><a href="data/modality_atlas.json">modality atlas</a></article>
2857
+ <article class="artifact"><h3>Multi-episode pilot</h3><p>The selected 128-episode Qwen3-Omni LoRA v6 diagnostic branch is verified with 4,032 held-out test predictions and 99.90% JSON validity. Action/subtask metrics are still weak, so this remains a baseline for error analysis.</p><a href="https://huggingface.co/cy0307/ropedia-qwen3-omni-lora-128ep">LoRA adapter</a><a href="data/qwen3_v5_v6_comparison.json">v5/v6 comparison</a></article>
2858
  <article class="artifact"><h3>Data boundary</h3><p>Raw MP4, HDF5, RRD files, private gated data, and full Qwen weights are not redistributed in this project.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/DATA_NOTICE.md">data notice</a></article>
2859
  <article class="artifact"><h3>Current project subset</h3><p>One public sample episode, 5,821 frames, 1,161 aligned windows, 8,546-dimensional task inputs, and no raw-data redistribution.</p><a href="data/modality_atlas.json">modality atlas</a></article>
2860
  <article class="artifact"><h3>Covered now</h3><p>Action/subtask labels, next-action prediction, temporal diagnostics, hand trajectory, contact, object relevance, caption grounding, retrieval, reconstruction, and misalignment.</p><a href="data/summary_metrics.json">summary metrics</a></article>
 
3304
  </div>
3305
  <div class="artifact-grid">
3306
  <article class="artifact primary-artifact"><div><h3>Model-family comparison</h3><p>Compares the three result layers and also groups 1-episode and 128-episode entries by model family: task heads, Qwen3-Omni LoRA, Cosmos3-Nano, and Cosmos3-Super.</p></div><a href="data/omni_model_comparison.json">result comparison</a></article>
3307
+ <article class="artifact"><h3>128-Episode Task Suite Enhancement Pack</h3><p>No-new-episode plan for denser supervision: `multiscale_20s10_40s20_80s40`, hierarchical action/subtask labels, stronger scoring slices, and raw-feature shard priorities.</p><a href="data/task_suite_enhancement_128.json">task_suite_enhancement_128.json</a></article>
3308
  <article class="artifact"><h3>Foundation-model plan</h3><p>Backbone selection matrix covering Qwen3-Omni, Cosmos 3, GR00T, OpenVLA/openpi, Gemini Robotics, Octo, SmolVLA-style policy candidates, and the future Xperience-native pretraining goal.</p><a href="data/foundation_model_plan.json">foundation model plan</a></article>
3309
  <article class="artifact"><h3>Multi-episode data access</h3><p>Public data-access path, selected 128-episode pilot plan, and preparation requirements.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/results/omni_finetune/MULTI_EPISODE_ACCESS_STATUS.md">data access</a></article>
3310
  <article class="artifact"><h3>Qwen3-Omni LoRA group</h3><p>Separates the 1-episode sensor-adapter smoke test from the current 128-episode LoRA adapter package and older diagnostics.</p><a href="data/omni_model_comparison.json">Qwen group</a></article>
3311
+ <article class="artifact"><h3>Cosmos3 groups</h3><p>Shows the verified Nano future-window compatibility package, the Super base-weight Reasoner JSON-task evaluation, and the Super fine-tuned forward-dynamics LoRA branch with separate loss metrics.</p><a href="data/omni_model_comparison.json">Cosmos groups</a></article>
3312
  <article class="artifact"><h3>Scale-up requirement</h3><p>Future runs need validation tracking, held-out predictions, quality-target reporting, and the same public-safe package gate.</p><a href="data/foundation_model_plan.json">training requirements</a></article>
3313
  <article class="artifact"><h3>Xperience-native pretraining</h3><p>Future plan for a domain-specific embodied foundation model trained from scratch over full-corpus video, audio, geometry, motion, inertial, and language streams.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/XPERIENCE_EMBODIED_FOUNDATION_MODEL_PRETRAINING.md">pretraining plan</a></article>
3314
  </div>
 
3339
  <section id="omni-scale-up" data-project-tab="resources" role="tabpanel" aria-labelledby="tab-resources" tabindex="-1">
3340
  <div class="wrap">
3341
  <div class="section-head">
3342
+ <h2>Qwen3-Omni diagnostic branch is verified.</h2>
3343
+ <p>The selected pilot uses 128 source-balanced episodes across 128 different session UUIDs. The latest v6 held-out package is verified, and its weak metrics define the next structured-output and error-analysis pass.</p>
3344
  </div>
3345
  <div class="artifact-grid">
3346
  <article class="artifact"><h3>Selection</h3><p>128 complete episodes selected from 128 unique top-level sessions, balanced across episode-size bands and split 96/16/16 for train/val/test.</p></article>
3347
  <article class="artifact"><h3>Transfer</h3><p>Download raw episodes only from official gated sources, exclude visualization.rrd, validate files, then stage them for training.</p></article>
3348
+ <article class="artifact"><h3>Current LoRA artifact</h3><p>The current Qwen3-Omni LoRA artifact is the verified v6 selected 128-episode diagnostic adapter. The v5 row remains pinned as the prior release, and the 1-episode Qwen entry is only a sensor-adapter smoke test.</p><a href="data/omni_model_comparison.json">model groups</a></article>
3349
+ <article class="artifact"><h3>128-Episode Task Suite Enhancement Pack</h3><p>The next suite push does not need more episodes first: use `multiscale_20s10_40s20_80s40`, hierarchical action/subtask targets, and raw-feature shards while keeping the held-out split fixed.</p><a href="data/task_suite_enhancement_128.json">task_suite_enhancement_128.json</a></article>
3350
+ <article class="artifact"><h3>Backbone branches</h3><p>Qwen3-Omni uses a separate LoRA model repo; Cosmos3-Nano remains a compatibility package; Cosmos3-Super now has a verified forward-dynamics LoRA branch with weights in a dedicated model repo.</p><a href="https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep">Cosmos3-Super weights</a></article>
3351
  <article class="artifact"><h3>Native foundation model</h3><p>The long-term goal is a full-corpus Xperience Embodied Foundation Model trained on synchronized perception, geometry, motion, inertial, audio, and language streams after smaller scaling stages validate the approach.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/XPERIENCE_EMBODIED_FOUNDATION_MODEL_PRETRAINING.md">pretraining plan</a></article>
3352
  </div>
3353
  </div>
 
3364
  <article class="artifact"><h3>Reproducibility matrix</h3><p>Machine-readable command matrix covering sample download, baselines, 12 tasks, figures, and validation.</p><a href="data/reproducibility_matrix.json">reproducibility matrix</a></article>
3365
  <article class="artifact"><h3>Exact-match reproduction record</h3><p>The last metric rebuild reproduced the public-sample outputs from a fresh cache and matched the committed metrics.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/notes/reproducibility_audit.md">reproduction audit</a></article>
3366
  <article class="artifact"><h3>Project dashboard</h3><p>The website organizes the dataset sample, tasks, methods, results, directions, and scale-up path in one tabbed reader flow.</p><a href="#artifacts">project materials</a></article>
3367
+ <article class="artifact"><h3>Multi-episode pilot status</h3><p>The comparison JSON now supports both the three-version reading and model-family grouping, with Qwen3 v5/v6 detail kept as a separate machine-readable audit.</p><a href="data/omni_model_comparison.json">comparison</a><a href="data/qwen3_v5_v6_comparison.json">Qwen v5/v6</a></article>
3368
  </div>
3369
  <p class="repro-note">Minimal path: install the toolkit dependencies, download the official sample, run the 12-task suite with neural heads, regenerate visualizations, then rebuild the supporting project reports.</p>
3370
  <pre class="code-panel"><button type="button" data-copy="setup">Copy</button><code id="setup">git clone https://github.com/Ropedia/HOMIE-toolkit.git
 
3399
 
3400
  <footer>
3401
  <div class="wrap">
3402
+ Built as an embodied-AI learning lab with verified held-out diagnostic branches and a next stage focused on stronger action/subtask quality.
3403
  </div>
3404
  </footer>
3405
 
research_roadmap.html CHANGED
@@ -42,12 +42,7 @@
42
  color: var(--ink);
43
  font-family: var(--font-ui);
44
  line-height: 1.5;
45
- background:
46
- radial-gradient(circle at 84% 8%, rgba(204, 255, 160, 0.13), transparent 28%),
47
- radial-gradient(circle at 16% 26%, rgba(204, 255, 160, 0.06), transparent 22%),
48
- radial-gradient(circle, rgba(204, 255, 160, 0.11) 1px, transparent 1.4px),
49
- var(--page);
50
- background-size: auto, auto, 22px 22px, auto;
51
  font-synthesis-weight: none;
52
  }
53
  a { color: inherit; }
@@ -122,11 +117,14 @@
122
  outline-offset: 3px;
123
  }
124
  .hero {
 
 
125
  padding: 86px 0 48px;
126
  border-bottom: 1px solid var(--soft-line);
127
  background:
128
- radial-gradient(circle at 78% 26%, rgba(204, 255, 160, 0.18), transparent 20%),
129
- linear-gradient(180deg, rgba(2, 5, 2, 0.2), rgba(5, 6, 11, 0.96));
 
130
  }
131
  .hero-grid {
132
  display: grid;
 
42
  color: var(--ink);
43
  font-family: var(--font-ui);
44
  line-height: 1.5;
45
+ background: var(--page);
 
 
 
 
 
46
  font-synthesis-weight: none;
47
  }
48
  a { color: inherit; }
 
117
  outline-offset: 3px;
118
  }
119
  .hero {
120
+ position: relative;
121
+ overflow: hidden;
122
  padding: 86px 0 48px;
123
  border-bottom: 1px solid var(--soft-line);
124
  background:
125
+ linear-gradient(90deg, rgba(2, 5, 2, 0.96) 0%, rgba(2, 5, 2, 0.84) 52%, rgba(2, 5, 2, 0.70) 100%),
126
+ linear-gradient(180deg, rgba(2, 5, 2, 0.12), rgba(5, 6, 11, 0.98)),
127
+ url("assets/qwen3_omni_lora_pipeline.png?v=qwen3-lora-v1") center right / cover no-repeat;
128
  }
129
  .hero-grid {
130
  display: grid;
scripts/sync_hf_publish_mirrors.py CHANGED
@@ -37,6 +37,27 @@ and `docs/data/task_suite_enhancement_128.json`. It recommends
37
  label-normalized scoring, and compact raw-feature shards before adding more
38
  episodes.
39
  """
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
40
 
41
 
42
  def load_parity_module():
@@ -101,6 +122,62 @@ def ensure_enhancement_card_links(hf_root: Path, *, dry_run: bool) -> list[str]:
101
  return updated
102
 
103
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
104
  def main() -> int:
105
  args = parse_args()
106
  hf_root = args.hf_root.expanduser().resolve()
@@ -168,8 +245,10 @@ def main() -> int:
168
  src,
169
  [
170
  hf_root / "space" / filename,
 
171
  hf_root / "artifacts/docs" / filename,
172
  hf_root / "model" / filename,
 
173
  ],
174
  dry_run=args.dry_run,
175
  )
@@ -200,6 +279,7 @@ def main() -> int:
200
  )
201
 
202
  card_updates = ensure_enhancement_card_links(hf_root, dry_run=args.dry_run)
 
203
  summary = {
204
  "status": "dry_run" if args.dry_run else "synced",
205
  "hf_root": hf_root.as_posix(),
 
37
  label-normalized scoring, and compact raw-feature shards before adding more
38
  episodes.
39
  """
40
+ QWEN_COMPARISON_MARKER = "docs/data/qwen3_v5_v6_comparison.json"
41
+ QWEN_COMPARISON_ROW = (
42
+ "| Compare Qwen3 v5/v6 diagnostic branches | "
43
+ "`docs/data/qwen3_v5_v6_comparison.json` |"
44
+ )
45
+ QWEN_ARTIFACT_OLD_BULLET = """- A current verified Qwen3-Omni strict-label v3 held-out package for the
46
+ selected 96/16/16 episode split, with 100.00% JSON validity and weak
47
+ action/subtask quality documented as the next error-analysis target."""
48
+ QWEN_ARTIFACT_CURRENT_BULLET = """- The latest verified Qwen3-Omni LoRA v6 diagnostic package for the selected
49
+ 96/16/16 episode split includes 34,269 exported windows, 4,032 held-out test
50
+ predictions, 99.90% JSON validity, and public-safe metrics/predictions."""
51
+ README_QWEN_OLD_PARAGRAPH = """The current verified diagnostic package uses the same selected split and 8-GPU
52
+ training path, records validation loss over 512 validation windows, and keeps
53
+ the held-out test split sealed for final evaluation. The next pass should keep
54
+ this package contract while tightening JSON decoding, target formatting, and
55
+ action/subtask error analysis."""
56
+ README_QWEN_CURRENT_PARAGRAPH = """The latest verified diagnostic package uses the same selected split and 8-GPU
57
+ training path, includes the full held-out evaluation with 4,032 predictions and
58
+ 99.90% JSON validity, and keeps raw data plus full Qwen weights out of the
59
+ public repos. The next pass should keep this package contract while improving
60
+ action/subtask target quality and error analysis."""
61
 
62
 
63
  def load_parity_module():
 
122
  return updated
123
 
124
 
125
+ def read_current_scaleup_line() -> str:
126
+ for line in (ROOT / "README.md").read_text(encoding="utf-8").splitlines():
127
+ if line.startswith("| Scale-up |"):
128
+ return line
129
+ raise SystemExit("Could not find current Scale-up row in README.md")
130
+
131
+
132
+ def ensure_current_qwen_card_links(hf_root: Path, *, dry_run: bool) -> list[str]:
133
+ updated = []
134
+
135
+ artifacts_readme = hf_root / "artifacts/README.md"
136
+ if artifacts_readme.exists():
137
+ text = artifacts_readme.read_text(encoding="utf-8")
138
+ original = text
139
+ if QWEN_COMPARISON_ROW not in text:
140
+ anchor = "| Compare current versions and model groups | `docs/data/omni_model_comparison.json` |"
141
+ text = text.replace(anchor, anchor + "\n" + QWEN_COMPARISON_ROW, 1)
142
+ if QWEN_ARTIFACT_OLD_BULLET in text:
143
+ text = text.replace(QWEN_ARTIFACT_OLD_BULLET, QWEN_ARTIFACT_CURRENT_BULLET, 1)
144
+ if "99.90% JSON validity" not in text:
145
+ text = text.rstrip() + "\n\n" + QWEN_ARTIFACT_CURRENT_BULLET + "\n"
146
+ if QWEN_COMPARISON_MARKER not in text:
147
+ text = text.rstrip() + f"\n\nQwen v5/v6 comparison: `{QWEN_COMPARISON_MARKER}`.\n"
148
+ if text != original:
149
+ updated.append("artifacts/README.md")
150
+ if not dry_run:
151
+ artifacts_readme.write_text(text, encoding="utf-8")
152
+
153
+ scaleup_line = read_current_scaleup_line()
154
+ for relative_path in ("model/README.md", "model/PROJECT_README.md"):
155
+ path = hf_root / relative_path
156
+ if not path.exists():
157
+ continue
158
+ original = path.read_text(encoding="utf-8")
159
+ text = original
160
+ if README_QWEN_OLD_PARAGRAPH in text:
161
+ text = text.replace(README_QWEN_OLD_PARAGRAPH, README_QWEN_CURRENT_PARAGRAPH, 1)
162
+ lines = text.splitlines()
163
+ changed = text != original
164
+ for idx, line in enumerate(lines):
165
+ if line.startswith("| Scale-up |"):
166
+ if line != scaleup_line:
167
+ lines[idx] = scaleup_line
168
+ changed = True
169
+ break
170
+ else:
171
+ lines.append(scaleup_line)
172
+ changed = True
173
+ if changed:
174
+ updated.append(relative_path)
175
+ if not dry_run:
176
+ path.write_text("\n".join(lines) + "\n", encoding="utf-8")
177
+
178
+ return updated
179
+
180
+
181
  def main() -> int:
182
  args = parse_args()
183
  hf_root = args.hf_root.expanduser().resolve()
 
245
  src,
246
  [
247
  hf_root / "space" / filename,
248
+ hf_root / "artifacts" / filename,
249
  hf_root / "artifacts/docs" / filename,
250
  hf_root / "model" / filename,
251
+ hf_root / "model/docs" / filename,
252
  ],
253
  dry_run=args.dry_run,
254
  )
 
279
  )
280
 
281
  card_updates = ensure_enhancement_card_links(hf_root, dry_run=args.dry_run)
282
+ card_updates += ensure_current_qwen_card_links(hf_root, dry_run=args.dry_run)
283
  summary = {
284
  "status": "dry_run" if args.dry_run else "synced",
285
  "hf_root": hf_root.as_posix(),
scripts/validate_mirror_parity.py CHANGED
@@ -368,8 +368,10 @@ def build_report(hf_root: Path) -> dict:
368
  ROOT / "docs" / filename,
369
  {
370
  "hf_space": hf_root / "space" / filename,
 
371
  "hf_artifacts_docs": hf_root / "artifacts/docs" / filename,
372
  "hf_model": hf_root / "model" / filename,
 
373
  },
374
  hf_root,
375
  )
 
368
  ROOT / "docs" / filename,
369
  {
370
  "hf_space": hf_root / "space" / filename,
371
+ "hf_artifacts_root": hf_root / "artifacts" / filename,
372
  "hf_artifacts_docs": hf_root / "artifacts/docs" / filename,
373
  "hf_model": hf_root / "model" / filename,
374
+ "hf_model_docs": hf_root / "model/docs" / filename,
375
  },
376
  hf_root,
377
  )
single_episode_explorer.html CHANGED
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