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PROJECT_README.md

@@ -9,7 +9,7 @@
 </p>
 
 <p align="center">
-  <strong>A multilingual public research surface for Xperience-10M: sample data, 20 embodied-AI tasks, baselines, Qwen3/Cosmos diagnostics, and foundation-model training directions.</strong>
+  <strong>A multilingual public research surface for Xperience-10M: sample data, 20 embodied-AI tasks, baselines, Qwen3-Omni and Cosmos3 diagnostics, and foundation-model training directions.</strong>
 </p>
 
 <!-- LANG-BAR:START -->
@@ -35,7 +35,7 @@
 </p>
 
 
-**Ropedia Xperience-10M Task Suite** is organized as two public result lines, not one blended benchmark. The 1-sample line is a fully inspectable task lab. The selected-128 line is the comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Every score points back to a source artifact and keeps direct-vs-proxy status visible.
+**Ropedia Xperience-10M Task Suite** is organized as two public result lines, not one blended benchmark. The 1-sample line is a fully inspectable task lab. The selected-128 line is the comparison surface for aligned baselines, the Qwen3-Omni series, and the Cosmos3 series. Every score points back to a source artifact and keeps direct-vs-proxy status visible.
 
 **Updated:** 2026-06-21.
 
@@ -89,7 +89,7 @@ The multilingual README files are reader guides. The canonical technical evidenc
     </tr>
     <tr>
       <td><strong>Line 2 methods</strong></td>
-      <td>Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano cover all 20 selected-128 task axes: 140/140 scores.</td>
+      <td>Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, and Cosmos3-Nano Future Window cover all 20 selected-128 task axes: 140/140 scores.</td>
     </tr>
     <tr>
       <td><strong>Foundation directions</strong></td>
@@ -97,7 +97,7 @@ The multilingual README files are reader guides. The canonical technical evidenc
     </tr>
     <tr>
       <td><strong>Public mirrors</strong></td>
-      <td>GitHub, GitHub Pages, HF Space, HF artifact dataset, HF baseline model repo, Qwen3/Cosmos model repos, and HF collection.</td>
+      <td>GitHub, GitHub Pages, HF Space, HF artifact dataset, HF baseline model repo, Qwen3-Omni and Cosmos3 model repos, and HF collection.</td>
     </tr>
   </tbody>
 </table>
@@ -179,11 +179,88 @@ The public suite is organized around two result lines. Keep them separate when r
   </tbody>
 </table>
 
+### Method Blocks
+
+<table>
+  <thead>
+    <tr>
+      <th width="20%">Evidence line</th>
+      <th width="20%">Method block</th>
+      <th width="24%">Methods</th>
+      <th width="18%">Score statement</th>
+      <th>Read as</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td><strong>1 sample episode</strong></td>
+      <td>Task-head baselines</td>
+      <td>Minimal; Neural MLP</td>
+      <td>40/40 direct scores.</td>
+      <td>Task-lab reproducibility and simple-vs-neural behavior.</td>
+    </tr>
+    <tr>
+      <td><strong>128 selected episodes</strong></td>
+      <td>Aligned baseline heads</td>
+      <td>Metadata simple/NN; raw-feature simple/NN</td>
+      <td>80/80 scores: 74 direct + 6 compact-proxy.</td>
+      <td>Same-split metadata/raw-feature baseline comparison.</td>
+    </tr>
+    <tr>
+      <td><strong>128 selected episodes</strong></td>
+      <td>Qwen3-Omni series</td>
+      <td>Qwen3-Omni v6 LoRA</td>
+      <td>20/20 direct scores from verified selected-128 Qwen3-Omni LoRA and task-specific probes.</td>
+      <td>Trainable Qwen3-Omni diagnostic baseline on the selected-128 surface.</td>
+    </tr>
+    <tr>
+      <td><strong>128 selected episodes</strong></td>
+      <td>Cosmos3 series</td>
+      <td>Cosmos3-Super Reasoner; Cosmos3-Nano Future Window</td>
+      <td>40/40 direct scores from verified public-safe reasoner and future-window artifacts.</td>
+      <td>Cosmos3 reasoner and future-window diagnostics on the selected-128 surface.</td>
+    </tr>
+  </tbody>
+</table>
+
+Cosmos3-Super Forward-Dynamics LoRA is published as a separate fine-tuned adapter artifact with weights/results; it is not counted as a 20-task matrix method row.
+
+### Qwen3-Omni Run Versions
+
+These are Qwen3-Omni run versions, not the three project-level public result layers. The 20-task matrix uses **Qwen3-Omni v6 LoRA**. v5 remains the pinned prior release. v1-v4 are lineage/ablation evidence.
+
+<table>
+  <thead>
+    <tr>
+      <th width="10%">Run</th>
+      <th width="26%">What changed</th>
+      <th width="12%">Eval samples</th>
+      <th width="12%">JSON validity</th>
+      <th width="12%">Contact acc.</th>
+      <th>Public role</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr><td><strong>v1</strong></td><td>Selected-128 validation-aware LoRA baseline.</td><td>448</td><td>0.8750</td><td>0.6451</td><td>Superseded lineage evidence.</td></tr>
+    <tr><td><strong>v2</strong></td><td>Structured-JSON reuse full-8-GPU LoRA.</td><td>448</td><td>0.9978</td><td>0.7188</td><td>Superseded lineage evidence.</td></tr>
+    <tr><td><strong>v3</strong></td><td>Strict-label prompt/eval over the v2 adapter.</td><td>448</td><td>1.0000</td><td>0.7210</td><td>Prompt/eval lineage evidence.</td></tr>
+    <tr><td><strong>v4</strong></td><td>Four-epoch structured-JSON LoRA.</td><td>448</td><td>1.0000</td><td>0.7299</td><td>Superseded metric tradeoff run.</td></tr>
+    <tr><td><strong>v5</strong></td><td>Multiscale cap96 LoRA.</td><td>4,032</td><td>1.0000</td><td>0.7865</td><td>Pinned prior release and comparison baseline.</td></tr>
+    <tr><td><strong>v6</strong></td><td>Rank64/lr5e-5 multiscale LoRA.</td><td>4,032</td><td>0.9990</td><td>0.8177</td><td>Current public 20-task Qwen row.</td></tr>
+  </tbody>
+</table>
+
+Detailed lineage:
+[`QWEN3_OMNI_RUN_LINEAGE.md`](QWEN3_OMNI_RUN_LINEAGE.md) and
+[`qwen3_omni_run_lineage.json`](docs/data/qwen3_omni_run_lineage.json).
+
 Result entry points:
 [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md),
 [`two_evidence_lines.json`](docs/data/two_evidence_lines.json),
 [`TWO_EVIDENCE_LINE_RESULT_SUMMARY.md`](TWO_EVIDENCE_LINE_RESULT_SUMMARY.md),
 [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json),
+[`QWEN3_OMNI_RUN_LINEAGE.md`](QWEN3_OMNI_RUN_LINEAGE.md),
+[`qwen3_omni_run_lineage.json`](docs/data/qwen3_omni_run_lineage.json),
 [`single_episode_task_model_radar.json`](docs/data/single_episode_task_model_radar.json),
 [`episode128_task_model_radar.json`](docs/data/episode128_task_model_radar.json),
 [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), and
@@ -310,7 +387,7 @@ and [`docs/data/project_brief.json`](docs/data/project_brief.json).
     <tr><td><strong>Hugging Face Space</strong></td><td>Hub-hosted copy of the dashboard and static app assets.</td></tr>
     <tr><td><strong>HF artifact dataset</strong></td><td>Public-safe metrics, reports, website JSON, result packages, and derived evidence files.</td></tr>
     <tr><td><strong>HF baseline model repo</strong></td><td>Minimal/neural baseline weights, figures, metrics, and mirrored task artifacts.</td></tr>
-    <tr><td><strong>Qwen3/Cosmos model repos</strong></td><td>Adapter-specific public weights or package cards when a model branch is verified and publishable.</td></tr>
+    <tr><td><strong>Qwen3-Omni and Cosmos3 model repos</strong></td><td>Adapter-specific public weights or package cards when Qwen3-Omni v6, Cosmos3-Super, or Cosmos3-Nano branches are verified and publishable.</td></tr>
   </tbody>
 </table>
 
@@ -719,11 +796,12 @@ For easier reading, the same source data is also split into two focused radars:
 ![128-episode 20-task model radar](docs/assets/charts/episode128_task_model_radar.svg)
 
 The single-episode radar isolates Minimal vs Neural MLP, both with 20/20 scored
-public-sample axes. The 128-episode radar isolates metadata/raw baselines and
-Qwen3/Cosmos branches: metadata and raw-feature simple/NN baselines are now
-complete 20/20 multi-episode records, with documented compact proxy notes where
-the public export lacks the original raw target. The current matrix has 180/180
-scored method-task records.
+public-sample axes. The 128-episode radar isolates metadata/raw baselines,
+Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, and Cosmos3-Nano Future Window:
+metadata and raw-feature simple/NN baselines are now complete 20/20
+multi-episode records, with documented compact proxy notes where the public
+export lacks the original raw target. The current matrix has 180/180 scored
+method-task records.
 
 The website also includes a responsive native modality atlas backed by
 [`docs/data/modality_atlas.json`](docs/data/modality_atlas.json) and
@@ -827,7 +905,7 @@ docs/
   assets/pipeline_diagram.png       # verified episode pipeline graphic
   assets/qwen3_omni_lora_pipeline.png # Qwen3-Omni LoRA training-flow figure
   assets/task_architectures.png     # verified task-head architecture map
-  assets/charts/unified_task_model_radar.svg # 20-task minimal/NN/Qwen/Cosmos radar
+  assets/charts/unified_task_model_radar.svg # 20-task minimal/NN/Qwen3-Omni/Cosmos3 radar
   assets/charts/single_episode_task_model_radar.svg # 1-episode split radar
   assets/charts/episode128_task_model_radar.svg # 128-episode split radar
   assets/charts/*.svg               # regenerated visualizations
@@ -987,7 +1065,7 @@ The current cross-version comparison is generated at
 [`docs/data/omni_model_comparison.json`](docs/data/omni_model_comparison.json)
 and [`results/omni_finetune/OMNI_MODEL_COMPARISON.md`](results/omni_finetune/OMNI_MODEL_COMPARISON.md);
 it separates the single-episode task suite, 128-episode aligned simple/NN
-baselines, and verified Qwen3/Cosmos model-branch packages. The same generated
+baselines, Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, and Cosmos3-Nano Future Window packages. The same generated
 files also include `model_groups`: a model-first view that pairs 1-episode and
 128-episode entries for the same family. Use that section when comparing task
 heads against task heads, Qwen3-Omni smoke/LoRA against Qwen3-Omni LoRA, or
@@ -996,7 +1074,7 @@ Cosmos3-Nano compatibility against future Cosmos weight releases.
 The no-new-episode enhancement layer is recorded in
 [`docs/data/task_suite_enhancement_128.json`](docs/data/task_suite_enhancement_128.json)
 and [`TASK_SUITE_ENHANCEMENT_128.md`](TASK_SUITE_ENHANCEMENT_128.md). It keeps
-the current Qwen/Cosmos packages as baselines, then defines dense-window
+the current Qwen3-Omni v6 and Cosmos3 packages as baselines, then defines dense-window
 scenarios, hierarchical action/subtask targets, task bottlenecks, and experiment
 cards for a stronger 128-episode v5 run without overwriting earlier results.
 

README.de.md

@@ -9,7 +9,7 @@
 </p>
 
 <p align="center">
-  <strong>Mehrsprachige öffentliche Forschungsoberfläche für Xperience-10M: Sample-Daten, 20 Embodied-AI-Aufgaben, Baselines, Qwen3/Cosmos-Diagnostik und Trainingsrichtungen.</strong>
+  <strong>Mehrsprachige öffentliche Forschungsoberfläche für Xperience-10M: Sample-Daten, 20 Embodied-AI-Aufgaben, Baselines, Qwen3-Omni- und Cosmos3-Diagnostik und Trainingsrichtungen.</strong>
 </p>
 
 <!-- LANG-BAR:START -->
@@ -51,6 +51,8 @@ Dieses Repository macht aus dem öffentlichen Xperience-10M-Sample eine prüfbar
 
 Formel: 2 Single-Episode-Methoden x 20 Aufgaben = 40; 7 128-Episode-Methoden x 20 Aufgaben = 140; öffentliche Gesamtmatrix = 180/180 gescorte Einträge.
 
+Methodenblöcke: Linie 1 enthält task-head baselines (Minimal, Neural MLP). Linie 2 trennt aligned baseline heads (metadata simple/NN, raw-feature simple/NN), die Qwen3-Omni series (Qwen3-Omni v6 LoRA) und die Cosmos3 series (Cosmos3-Super Reasoner, Cosmos3-Nano Future Window). Qwen3 v1-v6 ist eine LoRA-/Evaluationslinie, nicht die drei öffentlichen Projektebenen; die 20-Task-Matrix nutzt v6 und v5 bleibt der pinned prior release. Cosmos3-Super Forward-Dynamics LoRA ist ein separat veröffentlichter Adapter/Gewichts-/Ergebnis-Artefakt und zählt nicht als Methodenreihe der 20-Task-Matrix.
+
 Einstieg: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Schneller Einstieg

README.es.md

@@ -9,7 +9,7 @@
 </p>
 
 <p align="center">
-  <strong>Superficie pública multilingüe para Xperience-10M: datos de muestra, 20 tareas embodied-AI, baselines, diagnósticos Qwen3/Cosmos y direcciones de entrenamiento.</strong>
+  <strong>Superficie pública multilingüe para Xperience-10M: datos de muestra, 20 tareas embodied-AI, baselines, diagnósticos Qwen3-Omni y Cosmos3, y direcciones de entrenamiento.</strong>
 </p>
 
 <!-- LANG-BAR:START -->
@@ -51,6 +51,8 @@ Este repositorio convierte el episodio público de muestra de Xperience-10M en u
 
 Fórmula: 2 métodos de un episodio x 20 tareas = 40; 7 métodos de 128 episodios x 20 tareas = 140; matriz pública total = 180/180 registros con score.
 
+Bloques de métodos: la línea 1 contiene task-head baselines (Minimal, Neural MLP). La línea 2 separa aligned baseline heads (metadata simple/NN, raw-feature simple/NN), la serie Qwen3-Omni (Qwen3-Omni v6 LoRA) y la serie Cosmos3 (Cosmos3-Super Reasoner, Cosmos3-Nano Future Window). Qwen3 v1-v6 es una línea de evolución LoRA/evaluación, no las tres capas públicas del proyecto; la matriz de 20 tareas usa v6 y v5 queda como pinned prior release. Cosmos3-Super Forward-Dynamics LoRA se publica como adapter/pesos/resultados aparte y no cuenta como fila de método en la matriz de 20 tareas.
+
 Entradas: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Ruta Rápida

README.fr.md

@@ -9,7 +9,7 @@
 </p>
 
 <p align="center">
-  <strong>Surface publique multilingue pour Xperience-10M : échantillon, 20 tâches embodied-AI, baselines, diagnostics Qwen3/Cosmos et pistes d'entraînement.</strong>
+  <strong>Surface publique multilingue pour Xperience-10M : échantillon, 20 tâches embodied-AI, baselines, diagnostics Qwen3-Omni et Cosmos3, et pistes d'entraînement.</strong>
 </p>
 
 <!-- LANG-BAR:START -->
@@ -51,6 +51,8 @@ Ce dépôt transforme l'épisode public d'exemple Xperience-10M en laboratoire d
 
 Formule : 2 méthodes sur 1 épisode x 20 tâches = 40; 7 méthodes sur 128 épisodes x 20 tâches = 140; matrice publique totale = 180/180 enregistrements scorés.
 
+Blocs de méthodes : la ligne 1 contient les task-head baselines (Minimal, Neural MLP). La ligne 2 sépare les aligned baseline heads (metadata simple/NN, raw-feature simple/NN), la série Qwen3-Omni (Qwen3-Omni v6 LoRA) et la série Cosmos3 (Cosmos3-Super Reasoner, Cosmos3-Nano Future Window). Qwen3 v1-v6 est une lignée LoRA/évaluation, pas les trois couches publiques du projet; la matrice 20 tâches utilise v6 et v5 reste le pinned prior release. Cosmos3-Super Forward-Dynamics LoRA est publié comme adapter/poids/résultats séparé et ne compte pas comme ligne de méthode dans la matrice 20 tâches.
+
 Entrées : [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Parcours Rapide

README.ja.md

@@ -9,7 +9,7 @@
 </p>
 
 <p align="center">
-  <strong>Xperience-10M の多言語公開研究面: サンプルデータ、20 個の embodied-AI タスク、ベースライン、Qwen3/Cosmos 診断、基盤モデル訓練方向。</strong>
+  <strong>Xperience-10M の多言語公開研究面: サンプルデータ、20 個の embodied-AI タスク、ベースライン、Qwen3-Omni と Cosmos3 診断、基盤モデル訓練方向。</strong>
 </p>
 
 <!-- LANG-BAR:START -->
@@ -51,6 +51,8 @@
 
 式: 1-episode methods 2 個 x 20 tasks = 40、128-episode methods 7 個 x 20 tasks = 140、公開 matrix 合計は 180/180 scored records。
 
+Method blocks: Line 1 は task-head baselines（Minimal、Neural MLP）。Line 2 は aligned baseline heads（metadata simple/NN、raw-feature simple/NN）、Qwen3-Omni series（Qwen3-Omni v6 LoRA）、Cosmos3 series（Cosmos3-Super Reasoner、Cosmos3-Nano Future Window）に分かれます。Qwen3 v1-v6 は LoRA/eval の lineage で、project-level の 3 version とは別です。20-task matrix は v6 を使い、v5 は pinned prior release です。Cosmos3-Super Forward-Dynamics LoRA は別の adapter/weights/results artifact として公開され、20-task matrix の method row には含めません。
+
 入口: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md)、[`two_evidence_lines.json`](docs/data/two_evidence_lines.json)、[`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)、[`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json)。
 
 ## クイックルート

README.ko.md

@@ -9,7 +9,7 @@
 </p>
 
 <p align="center">
-  <strong>Xperience-10M을 위한 다국어 공개 연구 표면: 샘플 데이터, 20개 embodied-AI 과제, 베이스라인, Qwen3/Cosmos 진단, foundation 모델 학습 방향.</strong>
+  <strong>Xperience-10M을 위한 다국어 공개 연구 표면: 샘플 데이터, 20개 embodied-AI 과제, 베이스라인, Qwen3-Omni 및 Cosmos3 진단, foundation 모델 학습 방향.</strong>
 </p>
 
 <!-- LANG-BAR:START -->
@@ -51,6 +51,8 @@
 
 공식: single-episode 방법 2개 x 20 tasks = 40; 128-episode 방법 7개 x 20 tasks = 140; 전체 공개 matrix = 180/180 scored records.
 
+방법 블록: Line 1은 task-head baselines(Minimal, Neural MLP)입니다. Line 2는 aligned baseline heads(metadata simple/NN, raw-feature simple/NN), Qwen3-Omni series(Qwen3-Omni v6 LoRA), Cosmos3 series(Cosmos3-Super Reasoner, Cosmos3-Nano Future Window)로 분리됩니다. Qwen3 v1-v6은 LoRA/eval lineage이며 project-level 3개 버전과 다릅니다. 20-task matrix는 v6을 사용하고 v5는 pinned prior release입니다. Cosmos3-Super Forward-Dynamics LoRA는 별도의 adapter/weights/results artifact로 공개되며 20-task matrix method row에는 포함되지 않습니다.
+
 입구: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## 빠른 경로

README.pt.md

@@ -9,7 +9,7 @@
 </p>
 
 <p align="center">
-  <strong>Superfície pública multilíngue para Xperience-10M: dados de amostra, 20 tarefas embodied-AI, baselines, diagnósticos Qwen3/Cosmos e direções de treino.</strong>
+  <strong>Superfície pública multilíngue para Xperience-10M: dados de amostra, 20 tarefas embodied-AI, baselines, diagnósticos Qwen3-Omni e Cosmos3 e direções de treino.</strong>
 </p>
 
 <!-- LANG-BAR:START -->
@@ -51,6 +51,8 @@ Este repositório transforma o episódio público de amostra do Xperience-10M em
 
 Fórmula: 2 métodos de um episódio x 20 tarefas = 40; 7 métodos de 128 episódios x 20 tarefas = 140; matriz pública total = 180/180 registros com score.
 
+Blocos de métodos: a linha 1 contém task-head baselines (Minimal, Neural MLP). A linha 2 separa aligned baseline heads (metadata simple/NN, raw-feature simple/NN), a série Qwen3-Omni (Qwen3-Omni v6 LoRA) e a série Cosmos3 (Cosmos3-Super Reasoner, Cosmos3-Nano Future Window). Qwen3 v1-v6 é uma linhagem LoRA/eval, não as três camadas públicas do projeto; a matriz de 20 tarefas usa v6 e v5 fica como pinned prior release. Cosmos3-Super Forward-Dynamics LoRA é publicado como adapter/pesos/resultados separado e não conta como linha de método na matriz de 20 tarefas.
+
 Entradas: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Rota Rápida

README.zh.md

@@ -9,7 +9,7 @@
 </p>
 
 <p align="center">
-  <strong>面向 Xperience-10M 的多语言公开研究入口：样本数据、20 个具身智能任务、基线、Qwen3/Cosmos 诊断结果，以及基础模型训练方向。</strong>
+  <strong>面向 Xperience-10M 的多语言公开研究入口：样本数据、20 个具身智能任务、基线、Qwen3-Omni 与 Cosmos3 诊断结果，以及基础模型训练方向。</strong>
 </p>
 
 <!-- LANG-BAR:START -->
@@ -51,6 +51,8 @@
 
 公式：2 个单 episode 方法 x 20 个任务 = 40；7 个 128-episode 方法 x 20 个任务 = 140；公开矩阵总计 180/180 scored records。
 
+方法块：Line 1 是 task-head baselines（Minimal、Neural MLP）。Line 2 分成 aligned baseline heads（metadata simple/NN、raw-feature simple/NN）、Qwen3-Omni series（Qwen3-Omni v6 LoRA）和 Cosmos3 series（Cosmos3-Super Reasoner、Cosmos3-Nano Future Window）。Qwen3 run v1-v6 是 LoRA/评估演进线，不是项目级三层版本；20-task matrix 使用 v6，v5 是 pinned prior release。Cosmos3-Super Forward-Dynamics LoRA 是单独发布的 adapter 权重/结果，不计入 20-task matrix method row。
+
 入口：[`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md)、[`two_evidence_lines.json`](docs/data/two_evidence_lines.json)、[`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)、[`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json)。
 
 ## 快速入口
@@ -69,7 +71,7 @@
 
 - 数据层：公开 sample episode 被切成 20-frame 窗口，并连接视频、音频、深度、pose/SLAM、mocap、IMU、calibration 和语言标注。
 - 任务层：20 个统一任务覆盖识别、预测、检索、重建、同步、长时预测、action-object 关系和 sensor bridge。
-- 结果层：单 episode minimal/NN 覆盖 20/20；128-episode metadata/raw/Qwen3/Cosmos 分开标注；当前公开矩阵为 180/180 scored records，其中 174 direct、6 compact proxy，proxy target 显式保留。
+- 结果层：单 episode minimal/NN 覆盖 20/20；128-episode metadata/raw、Qwen3-Omni v6 LoRA、Cosmos3-Super Reasoner、Cosmos3-Nano Future Window 分开标注；当前公开矩阵为 180/180 scored records，其中 174 direct、6 compact proxy，proxy target 显式保留。
 - 训练方向：spatial intelligence、human-video world model、vision-language-action 三条 pipeline 已经有任务映射和需要的证据清单。
 
 ## 公开边界

TWO_EVIDENCE_LINES.md

@@ -9,7 +9,7 @@ Score formula: 2 single-episode methods x 20 tasks = 40 records; 7 selected-128
 | Line | Data unit | Score statement | Valid claim | Do not claim |
 | --- | --- | --- | --- | --- |
 | 1 sample episode | One public sample episode; 5,821 frames; 1,161 aligned 20-frame windows; 8,546 feature dimensions. | 40/40 direct scores from Minimal and Neural MLP heads. | Task construction, raw-file inspection, local reproducibility, and controlled single-episode baselines. | Multi-episode generalization. |
-| 128 selected episodes | Selected held-out 96/16/16 split; 34,269 exported windows; public-safe processed features linked to official gated episode paths. | 140/140 selected-128 scores: 134 direct + 6 compact-proxy. | Same-split baseline/model comparison, Qwen3/Cosmos diagnostics, and scale-up planning. | Reading compact-proxy cells as direct raw-target measurements. |
+| 128 selected episodes | Selected held-out 96/16/16 split; 34,269 exported windows; public-safe processed features linked to official gated episode paths. | 140/140 selected-128 scores: 134 direct + 6 compact-proxy. | Same-split baseline/model comparison, Qwen3-Omni v6 LoRA diagnostics, Cosmos3-Super/Cosmos3-Nano diagnostics, and scale-up planning. | Reading compact-proxy cells as direct raw-target measurements. |
 
 ## Result Ledger
 
@@ -19,6 +19,17 @@ Score formula: 2 single-episode methods x 20 tasks = 40 records; 7 selected-128
 | 128 selected episodes | 7 | 20 | 140/140 | 134 | 6 compact-proxy scores |
 | Total public matrix | 9 | 20 | 180/180 | 174 | 6 |
 
+## Method Blocks
+
+| Evidence line | Method block | Methods | Score statement | Read as |
+| --- | --- | --- | --- | --- |
+| 1 sample episode | Task-head baselines | Minimal; Neural MLP | 40/40 direct scores. | Task-lab reproducibility and simple-vs-neural behavior. |
+| 128 selected episodes | Aligned baseline heads | Metadata simple/NN; raw-feature simple/NN | 80/80 scores: 74 direct + 6 compact-proxy. | Same-split metadata/raw-feature baseline comparison. |
+| 128 selected episodes | Qwen3-Omni series | Qwen3-Omni v6 LoRA | 20/20 direct scores from verified selected-128 LoRA and task-specific probes. | Current trainable Qwen3-Omni diagnostic baseline on the selected-128 surface. |
+| 128 selected episodes | Cosmos3 series | Cosmos3-Super Reasoner; Cosmos3-Nano Future Window | 40/40 direct scores from verified public-safe reasoner and future-window artifacts. | Cosmos3 reasoner and future-window diagnostics on the selected-128 surface. |
+
+Qwen3 run v1-v6 is a LoRA/evaluation lineage, not the project-level result layer numbering. The 20-task matrix uses Qwen3-Omni v6 LoRA; v5 remains the pinned prior release. Cosmos3-Super Forward-Dynamics LoRA is a separate adapter artifact and is not counted as a 20-task matrix method row.
+
 ## Result Files
 
 | Purpose | Artifact |
@@ -26,6 +37,7 @@ Score formula: 2 single-episode methods x 20 tasks = 40 records; 7 selected-128
 | Two-line map figure | [`docs/assets/charts/two_evidence_line_map.svg`](docs/assets/charts/two_evidence_line_map.svg) |
 | Unified 9-method x 20-task matrix | [`docs/data/task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json) |
 | Two-line result summary | [`docs/data/two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json) |
+| Qwen3-Omni v1-v6 run lineage | [`docs/data/qwen3_omni_run_lineage.json`](docs/data/qwen3_omni_run_lineage.json), [`QWEN3_OMNI_RUN_LINEAGE.md`](QWEN3_OMNI_RUN_LINEAGE.md) |
 | 1-episode radar data | [`docs/data/single_episode_task_model_radar.json`](docs/data/single_episode_task_model_radar.json) |
 | 128-episode radar data | [`docs/data/episode128_task_model_radar.json`](docs/data/episode128_task_model_radar.json) |
 | 128-episode feature index | [`docs/data/xperience10m_128_episode_feature_index.json`](docs/data/xperience10m_128_episode_feature_index.json) |

TWO_EVIDENCE_LINE_RESULT_SUMMARY.md

@@ -1,6 +1,6 @@
 # Two Evidence-Line Result Summary
 
-Generated: `2026-06-21T08:38:20+00:00`.
+Generated: `2026-06-21T10:00:36+00:00`.
 
 Source matrix: [`docs/data/task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)
 
@@ -8,7 +8,7 @@ Interpretation rule: Use the 1-episode line for task construction and reproducib
 
 ## Read This First
 
-The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Do not mix the two when reading scores.
+The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, the Qwen3-Omni series, and the Cosmos3 series. Do not mix the two when reading scores.
 
 Score formula: 2 single-episode methods x 20 tasks = 40 records; 7 selected-128 methods x 20 tasks = 140 records; total public matrix = 180/180 scored records.
 
@@ -31,7 +31,16 @@ Score formula: 2 single-episode methods x 20 tasks = 40 records; 7 selected-128
 | Line | Methods | Tasks | Scored records | Direct scores | Proxy scores | Primary visuals | Source artifacts |
 | --- | --- | --- | --- | --- | --- | --- | --- |
 | 1 sample episode | 2 | 20 | 40/40 | 40 | 0 | docs/assets/charts/two_evidence_line_map.svg<br>docs/assets/charts/single_episode_task_model_radar.svg | docs/data/single_episode_task_model_radar.json<br>docs/data/two_evidence_line_result_summary.json<br>results/episode_task_suite/summary_report.json<br>results/episode_task_suite/feature_manifest.json<br>docs/single_episode_explorer.html |
-| 128 selected episodes | 7 | 20 | 140/140 | 134 | 6 | docs/assets/charts/two_evidence_line_map.svg<br>docs/assets/charts/episode128_task_model_radar.svg<br>docs/assets/charts/unified_task_model_radar.svg | docs/data/episode128_task_model_radar.json<br>docs/data/two_evidence_line_result_summary.json<br>docs/data/xperience10m_128_episode_feature_index.json<br>docs/data/omni_model_comparison.json<br>docs/data/task_method_20_gap_audit.json |
+| 128 selected episodes | 7 | 20 | 140/140 | 134 | 6 | docs/assets/charts/two_evidence_line_map.svg<br>docs/assets/charts/episode128_task_model_radar.svg<br>docs/assets/charts/unified_task_model_radar.svg | docs/data/episode128_task_model_radar.json<br>docs/data/two_evidence_line_result_summary.json<br>docs/data/xperience10m_128_episode_feature_index.json<br>docs/data/omni_model_comparison.json<br>docs/data/qwen3_omni_run_lineage.json<br>docs/data/task_method_20_gap_audit.json |
+
+## Method Blocks By Evidence Line
+
+| Line | Method block | Methods | Scored records | Direct scores | Proxy scores | Evidence type | Read as |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| 1 sample episode | Task-head baselines | Minimal, Neural MLP | 40/40 | 40 | 0 | Direct target metrics on the public sample windows. | Task construction, local reproducibility, and Minimal-vs-Neural behavior. |
+| 128 selected episodes | Aligned baseline heads | 128ep Aligned Simple, 128ep Aligned NN, 128ep Raw Simple, 128ep Raw NN | 80/80 | 74 | 6 | Direct processed-target metrics where available; compact proxies for documented raw-target gaps. | Same-split metadata/raw-feature baseline comparison. |
+| 128 selected episodes | Qwen3-Omni series | Qwen3-Omni v6 LoRA | 20/20 | 20 | 0 | Verified selected-128 Qwen3-Omni v6 LoRA plus source-linked task-specific probes. | Trainable Qwen3-Omni diagnostic baseline on the selected-128 surface. |
+| 128 selected episodes | Cosmos3 series | Cosmos3-Super Reasoner, Cosmos3-Nano Future Window | 40/40 | 40 | 0 | Verified Cosmos3-Super Reasoner and Cosmos3-Nano Future Window public-safe artifacts. | Cosmos3 reasoner and future-window diagnostics on the selected-128 surface. |
 
 ## Method Detail By Line
 
@@ -47,6 +56,13 @@ Score formula: 2 single-episode methods x 20 tasks = 40 records; 7 selected-128
 | 128 selected episodes | Cosmos3-Super Reasoner | Verified Cosmos3-Super base-weight Reasoner JSON-task evaluation, plus task 5/8/9/10/11/12/13/14/16/17/18/19/20 probes where public metrics exist. | 20/20 | 20 | 0 |
 | 128 selected episodes | Cosmos3-Nano Future Window | Verified Cosmos3-Nano future-window compatibility metrics, plus model-output probes for tasks 2/5/7/8/10/11/12/13/14/15/16/17/18/19 and a derived task-20 boundary timing probe scored from held-out future-window artifacts. | 20/20 | 20 | 0 |
 
+## Related Model Artifacts
+
+| Artifact | Role | Link or path |
+| --- | --- | --- |
+| Qwen3-Omni v1-v6 run lineage | Explains the LoRA/evaluation version ladder; v6 is the current 20-task matrix row, v5 remains the pinned prior release, and v1-v4 are lineage/ablation evidence. | docs/data/qwen3_omni_run_lineage.json |
+| Cosmos3-Super Forward-Dynamics LoRA | Separate fine-tuned adapter artifact for forward-dynamics loss metrics; published with weights/results but not counted as a 20-task matrix method row. | https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep |
+
 ## Proxy-Scored Cells
 
 | Task | Task label | Method | Metric | Reason |
@@ -70,5 +86,5 @@ Score formula: 2 single-episode methods x 20 tasks = 40 records; 7 selected-128
 ## Reader Policy
 
 - 1 sample episode: Use for task construction, raw-file inspection, local reproducibility, and controlled Minimal-vs-Neural baseline behavior.
-- 128 selected episodes: Use for held-out comparison, metadata/raw-feature baselines, Qwen3/Cosmos branches, and scale-up decisions.
+- 128 selected episodes: Use for held-out comparison, metadata/raw-feature baselines, Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, Cosmos3-Nano Future Window, and scale-up decisions.
 - Proxy scores: Proxy-scored cells stay numeric only when the source artifact and reason are attached; they should not be read as direct raw-target measurements.

data/mirror_parity.json

@@ -1,6 +1,6 @@
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-  "generated_at_utc": "2026-06-21T09:22:27+00:00",
+  "generated_at_utc": "2026-06-21T10:10:44+00:00",
   "rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
   "automated_gates": [
     {

data/scope_claims_audit.json

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:21:17+00:00",
+  "generated_at_utc": "2026-06-21T10:03:08+00:00",
   "summary": {
     "qwen3_omni_verified_diagnostic_pilot": true,
     "dataset_manifest_num_episodes": 119,

data/source_alignment_audit.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:21:08+00:00",
+  "generated_at_utc": "2026-06-21T10:03:08+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",

data/task_method_20_source_audit.json

@@ -2,7 +2,7 @@
   "checked_json_metric_count": 180,
   "failure_count": 0,
   "failures": [],
-  "generated_at_utc": "2026-06-21T09:21:09+00:00",
+  "generated_at_utc": "2026-06-21T10:03:08+00:00",
   "method_task_record_count": 180,
   "rule": "Every scored row that declares a JSON metric source must have the same numeric value under that row's metric_key.",
   "scored_method_task_count": 180,

data/task_surface_integrity.json

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:21:08+00:00",
+  "generated_at_utc": "2026-06-21T10:03:08+00:00",
   "summary": {
     "original_walkthrough_task_count": 12,
     "expected_original_walkthrough_task_count": 12,

data/two_evidence_line_result_summary.json

@@ -1,5 +1,5 @@
 {
-  "generated_at_utc": "2026-06-21T08:38:20+00:00",
+  "generated_at_utc": "2026-06-21T10:00:36+00:00",
   "interpretation_rule": "Use the 1-episode line for task construction and reproducibility claims. Use the 128-episode line for held-out comparison and model-branch claims.",
   "lines": [
     {
@@ -63,6 +63,7 @@
         "docs/data/two_evidence_line_result_summary.json",
         "docs/data/xperience10m_128_episode_feature_index.json",
         "docs/data/omni_model_comparison.json",
+        "docs/data/qwen3_omni_run_lineage.json",
         "docs/data/task_method_20_gap_audit.json"
       ],
       "claim_boundary": "Supports same-split comparison, model-branch diagnostics, and scale-up planning on public-safe processed artifacts.",
@@ -183,6 +184,86 @@
       "task_count": 20
     }
   ],
+  "method_blocks": [
+    {
+      "block": "Task-head baselines",
+      "direct_scored_method_task_count": 40,
+      "evidence_type": "Direct target metrics on the public sample windows.",
+      "line_id": "single_public_sample_episode",
+      "line_label": "1 sample episode",
+      "method_ids": [
+        "minimal",
+        "neural_mlp"
+      ],
+      "method_task_record_count": 40,
+      "methods": [
+        "Minimal",
+        "Neural MLP"
+      ],
+      "proxy_scored_method_task_count": 0,
+      "read_as": "Task construction, local reproducibility, and Minimal-vs-Neural behavior.",
+      "scored_method_task_count": 40
+    },
+    {
+      "block": "Aligned baseline heads",
+      "direct_scored_method_task_count": 74,
+      "evidence_type": "Direct processed-target metrics where available; compact proxies for documented raw-target gaps.",
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "method_ids": [
+        "metadata128_simple",
+        "metadata128_neural_mlp",
+        "raw128_simple",
+        "raw128_neural_mlp"
+      ],
+      "method_task_record_count": 80,
+      "methods": [
+        "128ep Aligned Simple",
+        "128ep Aligned NN",
+        "128ep Raw Simple",
+        "128ep Raw NN"
+      ],
+      "proxy_scored_method_task_count": 6,
+      "read_as": "Same-split metadata/raw-feature baseline comparison.",
+      "scored_method_task_count": 80
+    },
+    {
+      "block": "Qwen3-Omni series",
+      "direct_scored_method_task_count": 20,
+      "evidence_type": "Verified selected-128 Qwen3-Omni v6 LoRA plus source-linked task-specific probes.",
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "method_ids": [
+        "qwen3_omni_v6_lora"
+      ],
+      "method_task_record_count": 20,
+      "methods": [
+        "Qwen3-Omni v6 LoRA"
+      ],
+      "proxy_scored_method_task_count": 0,
+      "read_as": "Trainable Qwen3-Omni diagnostic baseline on the selected-128 surface.",
+      "scored_method_task_count": 20
+    },
+    {
+      "block": "Cosmos3 series",
+      "direct_scored_method_task_count": 40,
+      "evidence_type": "Verified Cosmos3-Super Reasoner and Cosmos3-Nano Future Window public-safe artifacts.",
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "method_ids": [
+        "cosmos3_super_reasoner",
+        "cosmos3_nano_future_window"
+      ],
+      "method_task_record_count": 40,
+      "methods": [
+        "Cosmos3-Super Reasoner",
+        "Cosmos3-Nano Future Window"
+      ],
+      "proxy_scored_method_task_count": 0,
+      "read_as": "Cosmos3 reasoner and future-window diagnostics on the selected-128 surface.",
+      "scored_method_task_count": 40
+    }
+  ],
   "proxy_records": [
     {
       "line_id": "selected_128_episode_surface",
@@ -253,10 +334,10 @@
   ],
   "reader_policy": {
     "proxy_policy": "Proxy-scored cells stay numeric only when the source artifact and reason are attached; they should not be read as direct raw-target measurements.",
-    "selected_128_episode_surface": "Use for held-out comparison, metadata/raw-feature baselines, Qwen3/Cosmos branches, and scale-up decisions.",
+    "selected_128_episode_surface": "Use for held-out comparison, metadata/raw-feature baselines, Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, Cosmos3-Nano Future Window, and scale-up decisions.",
     "single_public_sample_episode": "Use for task construction, raw-file inspection, local reproducibility, and controlled Minimal-vs-Neural baseline behavior."
   },
-  "reader_summary": "The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Do not mix the two when reading scores.",
+  "reader_summary": "The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, the Qwen3-Omni series, and the Cosmos3 series. Do not mix the two when reading scores.",
   "reading_order": [
     {
       "reason": "Line 1 answers task-lab and reproducibility questions; line 2 answers selected-128 comparison questions.",
@@ -275,6 +356,18 @@
       "step": "Check proxy cells before interpreting totals"
     }
   ],
+  "related_model_artifacts": [
+    {
+      "name": "Qwen3-Omni v1-v6 run lineage",
+      "repo": "docs/data/qwen3_omni_run_lineage.json",
+      "role": "Explains the LoRA/evaluation version ladder; v6 is the current 20-task matrix row, v5 remains the pinned prior release, and v1-v4 are lineage/ablation evidence."
+    },
+    {
+      "name": "Cosmos3-Super Forward-Dynamics LoRA",
+      "repo": "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep",
+      "role": "Separate fine-tuned adapter artifact for forward-dynamics loss metrics; published with weights/results but not counted as a 20-task matrix method row."
+    }
+  ],
   "score_formula": "2 single-episode methods x 20 tasks = 40 records; 7 selected-128 methods x 20 tasks = 140 records; total public matrix = 180/180 scored records.",
   "source_lines": "docs/data/two_evidence_lines.json",
   "source_matrix": "docs/data/task_method_20_result_matrix.json",

data/two_evidence_lines.json

@@ -2,7 +2,7 @@
   "status": "current",
   "updated_utc": "2026-06-21T00:00:00Z",
   "interpretation_rule": "Use the 1-episode line for task construction and reproducibility claims. Use the 128-episode line for held-out comparison and model-branch claims.",
-  "reader_summary": "The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Do not mix the two when reading scores.",
+  "reader_summary": "The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, the Qwen3-Omni series, and the Cosmos3 series. Do not mix the two when reading scores.",
   "score_formula": "2 single-episode methods x 20 tasks = 40 records; 7 selected-128 methods x 20 tasks = 140 records; total public matrix = 180/180 scored records.",
   "lines": [
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@@ -80,10 +80,82 @@
         "docs/data/two_evidence_line_result_summary.json",
         "docs/data/xperience10m_128_episode_feature_index.json",
         "docs/data/omni_model_comparison.json",
+        "docs/data/qwen3_omni_run_lineage.json",
         "docs/data/task_method_20_gap_audit.json"
       ]
     }
   ],
+  "method_blocks": [
+    {
+      "line_id": "single_public_sample_episode",
+      "line_label": "1 sample episode",
+      "block": "Task-head baselines",
+      "methods": [
+        "Minimal",
+        "Neural MLP"
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+      "direct_scored_records": 40,
+      "proxy_scored_records": 0,
+      "evidence_type": "Direct target metrics on the public sample windows.",
+      "read_as": "Task-lab reproducibility and simple-vs-neural behavior."
+    },
+    {
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "block": "Aligned baseline heads",
+      "methods": [
+        "Metadata simple",
+        "Metadata NN",
+        "Raw-feature simple",
+        "Raw-feature NN"
+      ],
+      "scored_records": 80,
+      "direct_scored_records": 74,
+      "proxy_scored_records": 6,
+      "evidence_type": "Direct processed-target metrics where available; compact proxies for documented raw-target gaps.",
+      "read_as": "Same-split metadata/raw-feature baseline comparison."
+    },
+    {
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "block": "Qwen3-Omni series",
+      "methods": [
+        "Qwen3-Omni v6 LoRA"
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+      "scored_records": 20,
+      "direct_scored_records": 20,
+      "proxy_scored_records": 0,
+      "evidence_type": "Verified selected-128 Qwen3-Omni v6 LoRA plus source-linked task-specific probes.",
+      "read_as": "Trainable Qwen3-Omni diagnostic baseline on the selected-128 surface."
+    },
+    {
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "block": "Cosmos3 series",
+      "methods": [
+        "Cosmos3-Super Reasoner",
+        "Cosmos3-Nano Future Window"
+      ],
+      "scored_records": 40,
+      "direct_scored_records": 40,
+      "proxy_scored_records": 0,
+      "evidence_type": "Verified Cosmos3-Super Reasoner and Cosmos3-Nano Future Window public-safe artifacts.",
+      "read_as": "Cosmos3 reasoner and future-window diagnostics on the selected-128 surface."
+    }
+  ],
+  "related_model_artifacts": [
+    {
+      "name": "Qwen3-Omni v1-v6 run lineage",
+      "role": "Explains the LoRA/evaluation version ladder; v6 is the current 20-task matrix row, v5 remains the pinned prior release, and v1-v4 are lineage/ablation evidence.",
+      "repo": "docs/data/qwen3_omni_run_lineage.json"
+    },
+    {
+      "name": "Cosmos3-Super Forward-Dynamics LoRA",
+      "role": "Separate fine-tuned adapter artifact for forward-dynamics loss metrics; published with weights/results but not counted as a 20-task matrix method row.",
+      "repo": "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep"
+    }
+  ],
   "combined_public_matrix": {
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     "methods": 9,

data/website_integrity.json

@@ -1,13 +1,13 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:20:28+00:00",
+  "generated_at_utc": "2026-06-21T10:08:12+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
     "html_pages": 4,
-    "local_references": 241,
-    "external_reference_count": 152,
-    "json_files": 53,
+    "local_references": 247,
+    "external_reference_count": 153,
+    "json_files": 54,
     "image_assets_referenced": 29,
     "failure_count": 0
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@@ -80,8 +80,8 @@
       "name": "project_overview_precedes_progress_ledger",
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-      "overview_index": 116163,
-      "evidence_index": 156473
+      "overview_index": 118264,
+      "evidence_index": 163038
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@@ -159,9 +159,9 @@
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       "reason": "The evaluation protocol should appear before the deeper evidence ledger.",
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-      "protocol_index": 152654,
-      "evidence_index": 156473
+      "overview_index": 118264,
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@@ -180,7 +180,7 @@
       "status": "pass",
       "reason": "The Suite anchor should show the task-suite map before the modality atlas.",
       "first_marker_index": 471,
-      "second_marker_index": 3762
+      "second_marker_index": 3794
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@@ -277,7 +277,7 @@
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       "image_count": 35
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@@ -414,6 +414,11 @@
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@@ -531,12 +536,12 @@
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@@ -546,7 +551,7 @@
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docs/data/mirror_parity.json

@@ -1,6 +1,6 @@
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-  "generated_at_utc": "2026-06-21T09:22:17+00:00",
+  "generated_at_utc": "2026-06-21T10:09:43+00:00",
   "hf_root": "hf_publish",
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@@ -923,44 +923,44 @@
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@@ -972,44 +972,44 @@
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@@ -1119,44 +1119,44 @@
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           "exists": true,
-          "bytes": 6684,
-          "sha256": "a2e9708dfda9069b2e1a818a1f43593f319c48ceb1e23345b92882142054b621"
+          "bytes": 8603,
+          "sha256": "4424e131a7d6a22a89f9f522f15fbdde6419d7debcffd6e6755ca4c3f47731b9"
         },
         "hf_model": {
           "path": "hf_model:TWO_EVIDENCE_LINE_RESULT_SUMMARY.md",
           "exists": true,
-          "bytes": 6684,
-          "sha256": "a2e9708dfda9069b2e1a818a1f43593f319c48ceb1e23345b92882142054b621"
+          "bytes": 8603,
+          "sha256": "4424e131a7d6a22a89f9f522f15fbdde6419d7debcffd6e6755ca4c3f47731b9"
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       "failures": []

docs/data/public_surface_qa.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Public Project Surface",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:20:20+00:00",
+  "generated_at_utc": "2026-06-21T10:02:48+00:00",
   "scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
   "checks": [
     {
@@ -18,7 +18,7 @@
         "website_integrity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T09:02:49+00:00"
+          "generated_at_utc": "2026-06-21T10:02:48+00:00"
         },
         "rendered_site_check": {
           "exists": true,
@@ -28,27 +28,27 @@
         "task_surface_integrity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T08:38:50+00:00"
+          "generated_at_utc": "2026-06-21T09:35:37+00:00"
         },
         "source_alignment": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T08:38:50+00:00"
+          "generated_at_utc": "2026-06-21T09:35:37+00:00"
         },
         "scale_up_status": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T08:38:55+00:00"
+          "generated_at_utc": "2026-06-21T09:35:40+00:00"
         },
         "publication_package": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T09:03:23+00:00"
+          "generated_at_utc": "2026-06-21T09:35:32+00:00"
         },
         "mirror_parity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T09:04:19+00:00"
+          "generated_at_utc": "2026-06-21T09:36:59+00:00"
         }
       },
       "failures": {}
@@ -97,8 +97,8 @@
       "marker_counts": {
         "Ropedia Xperience-10M Task Suite": 20,
         "Xperience-10M": 166,
-        "20-task": 71,
-        "Qwen3-Omni": 154,
+        "20-task": 78,
+        "Qwen3-Omni": 191,
         "128-episode pilot": 1
       }
     },
@@ -107,7 +107,7 @@
       "status": "pass",
       "reason": "Public cards should link the repo, Space, artifacts, model baselines, upstream dataset, and Ropedia dataset page.",
       "marker_counts": {
-        "https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite": 86,
+        "https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite": 87,
         "https://huggingface.co/spaces/cy0307/ropedia-xperience-10m-task-suite": 11,
         "https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts": 11,
         "https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines": 14,
@@ -135,10 +135,10 @@
         "data/two_evidence_lines.json": 5,
         "data/two_evidence_line_result_summary.json": 10,
         "data/unified_task_model_radar.json": 21,
-        "data/single_episode_task_model_radar.json": 16,
+        "data/single_episode_task_model_radar.json": 17,
         "data/episode128_task_model_radar.json": 16,
         "data/task_method_20_result_matrix.json": 24,
-        "data/task_method_20_gap_audit.json": 21,
+        "data/task_method_20_gap_audit.json": 22,
         "data/language_versions.json": 3,
         "assets/charts/two_evidence_line_map.svg": 5,
         "assets/charts/unified_task_model_radar.svg": 17,

docs/data/publication_audit.json

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:20:53+00:00",
+  "generated_at_utc": "2026-06-21T10:08:29+00:00",
   "checks": [
     {
       "name": "required_publication_assets_present",
@@ -233,8 +233,8 @@
     "github_repo": {
       "root": "repo",
       "exists": true,
-      "file_count": 1519,
-      "text_file_count": 1258,
+      "file_count": 1522,
+      "text_file_count": 1261,
       "largest_file": {
         "path": "results/omni_finetune/a100_128_metadata_task_baselines_20260616_v2/interaction_text_prediction/confusion_matrix.csv",
         "bytes": 73057076

docs/data/quality_gates.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Release Checks",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:22:27+00:00",
+  "generated_at_utc": "2026-06-21T10:10:44+00:00",
   "rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
   "automated_gates": [
     {

docs/data/scope_claims_audit.json

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:21:17+00:00",
+  "generated_at_utc": "2026-06-21T10:03:08+00:00",
   "summary": {
     "qwen3_omni_verified_diagnostic_pilot": true,
     "dataset_manifest_num_episodes": 119,

docs/data/source_alignment_audit.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:21:08+00:00",
+  "generated_at_utc": "2026-06-21T10:03:08+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",

docs/data/task_method_20_source_audit.json

@@ -2,7 +2,7 @@
   "checked_json_metric_count": 180,
   "failure_count": 0,
   "failures": [],
-  "generated_at_utc": "2026-06-21T09:21:09+00:00",
+  "generated_at_utc": "2026-06-21T10:03:08+00:00",
   "method_task_record_count": 180,
   "rule": "Every scored row that declares a JSON metric source must have the same numeric value under that row's metric_key.",
   "scored_method_task_count": 180,

docs/data/task_surface_integrity.json

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:21:08+00:00",
+  "generated_at_utc": "2026-06-21T10:03:08+00:00",
   "summary": {
     "original_walkthrough_task_count": 12,
     "expected_original_walkthrough_task_count": 12,

docs/data/two_evidence_line_result_summary.json

@@ -1,5 +1,5 @@
 {
-  "generated_at_utc": "2026-06-21T08:38:20+00:00",
+  "generated_at_utc": "2026-06-21T10:00:36+00:00",
   "interpretation_rule": "Use the 1-episode line for task construction and reproducibility claims. Use the 128-episode line for held-out comparison and model-branch claims.",
   "lines": [
     {
@@ -63,6 +63,7 @@
         "docs/data/two_evidence_line_result_summary.json",
         "docs/data/xperience10m_128_episode_feature_index.json",
         "docs/data/omni_model_comparison.json",
+        "docs/data/qwen3_omni_run_lineage.json",
         "docs/data/task_method_20_gap_audit.json"
       ],
       "claim_boundary": "Supports same-split comparison, model-branch diagnostics, and scale-up planning on public-safe processed artifacts.",
@@ -183,6 +184,86 @@
       "task_count": 20
     }
   ],
+  "method_blocks": [
+    {
+      "block": "Task-head baselines",
+      "direct_scored_method_task_count": 40,
+      "evidence_type": "Direct target metrics on the public sample windows.",
+      "line_id": "single_public_sample_episode",
+      "line_label": "1 sample episode",
+      "method_ids": [
+        "minimal",
+        "neural_mlp"
+      ],
+      "method_task_record_count": 40,
+      "methods": [
+        "Minimal",
+        "Neural MLP"
+      ],
+      "proxy_scored_method_task_count": 0,
+      "read_as": "Task construction, local reproducibility, and Minimal-vs-Neural behavior.",
+      "scored_method_task_count": 40
+    },
+    {
+      "block": "Aligned baseline heads",
+      "direct_scored_method_task_count": 74,
+      "evidence_type": "Direct processed-target metrics where available; compact proxies for documented raw-target gaps.",
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "method_ids": [
+        "metadata128_simple",
+        "metadata128_neural_mlp",
+        "raw128_simple",
+        "raw128_neural_mlp"
+      ],
+      "method_task_record_count": 80,
+      "methods": [
+        "128ep Aligned Simple",
+        "128ep Aligned NN",
+        "128ep Raw Simple",
+        "128ep Raw NN"
+      ],
+      "proxy_scored_method_task_count": 6,
+      "read_as": "Same-split metadata/raw-feature baseline comparison.",
+      "scored_method_task_count": 80
+    },
+    {
+      "block": "Qwen3-Omni series",
+      "direct_scored_method_task_count": 20,
+      "evidence_type": "Verified selected-128 Qwen3-Omni v6 LoRA plus source-linked task-specific probes.",
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "method_ids": [
+        "qwen3_omni_v6_lora"
+      ],
+      "method_task_record_count": 20,
+      "methods": [
+        "Qwen3-Omni v6 LoRA"
+      ],
+      "proxy_scored_method_task_count": 0,
+      "read_as": "Trainable Qwen3-Omni diagnostic baseline on the selected-128 surface.",
+      "scored_method_task_count": 20
+    },
+    {
+      "block": "Cosmos3 series",
+      "direct_scored_method_task_count": 40,
+      "evidence_type": "Verified Cosmos3-Super Reasoner and Cosmos3-Nano Future Window public-safe artifacts.",
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "method_ids": [
+        "cosmos3_super_reasoner",
+        "cosmos3_nano_future_window"
+      ],
+      "method_task_record_count": 40,
+      "methods": [
+        "Cosmos3-Super Reasoner",
+        "Cosmos3-Nano Future Window"
+      ],
+      "proxy_scored_method_task_count": 0,
+      "read_as": "Cosmos3 reasoner and future-window diagnostics on the selected-128 surface.",
+      "scored_method_task_count": 40
+    }
+  ],
   "proxy_records": [
     {
       "line_id": "selected_128_episode_surface",
@@ -253,10 +334,10 @@
   ],
   "reader_policy": {
     "proxy_policy": "Proxy-scored cells stay numeric only when the source artifact and reason are attached; they should not be read as direct raw-target measurements.",
-    "selected_128_episode_surface": "Use for held-out comparison, metadata/raw-feature baselines, Qwen3/Cosmos branches, and scale-up decisions.",
+    "selected_128_episode_surface": "Use for held-out comparison, metadata/raw-feature baselines, Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, Cosmos3-Nano Future Window, and scale-up decisions.",
     "single_public_sample_episode": "Use for task construction, raw-file inspection, local reproducibility, and controlled Minimal-vs-Neural baseline behavior."
   },
-  "reader_summary": "The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Do not mix the two when reading scores.",
+  "reader_summary": "The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, the Qwen3-Omni series, and the Cosmos3 series. Do not mix the two when reading scores.",
   "reading_order": [
     {
       "reason": "Line 1 answers task-lab and reproducibility questions; line 2 answers selected-128 comparison questions.",
@@ -275,6 +356,18 @@
       "step": "Check proxy cells before interpreting totals"
     }
   ],
+  "related_model_artifacts": [
+    {
+      "name": "Qwen3-Omni v1-v6 run lineage",
+      "repo": "docs/data/qwen3_omni_run_lineage.json",
+      "role": "Explains the LoRA/evaluation version ladder; v6 is the current 20-task matrix row, v5 remains the pinned prior release, and v1-v4 are lineage/ablation evidence."
+    },
+    {
+      "name": "Cosmos3-Super Forward-Dynamics LoRA",
+      "repo": "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep",
+      "role": "Separate fine-tuned adapter artifact for forward-dynamics loss metrics; published with weights/results but not counted as a 20-task matrix method row."
+    }
+  ],
   "score_formula": "2 single-episode methods x 20 tasks = 40 records; 7 selected-128 methods x 20 tasks = 140 records; total public matrix = 180/180 scored records.",
   "source_lines": "docs/data/two_evidence_lines.json",
   "source_matrix": "docs/data/task_method_20_result_matrix.json",

docs/data/two_evidence_lines.json

@@ -2,7 +2,7 @@
   "status": "current",
   "updated_utc": "2026-06-21T00:00:00Z",
   "interpretation_rule": "Use the 1-episode line for task construction and reproducibility claims. Use the 128-episode line for held-out comparison and model-branch claims.",
-  "reader_summary": "The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Do not mix the two when reading scores.",
+  "reader_summary": "The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, the Qwen3-Omni series, and the Cosmos3 series. Do not mix the two when reading scores.",
   "score_formula": "2 single-episode methods x 20 tasks = 40 records; 7 selected-128 methods x 20 tasks = 140 records; total public matrix = 180/180 scored records.",
   "lines": [
     {
@@ -80,10 +80,82 @@
         "docs/data/two_evidence_line_result_summary.json",
         "docs/data/xperience10m_128_episode_feature_index.json",
         "docs/data/omni_model_comparison.json",
+        "docs/data/qwen3_omni_run_lineage.json",
         "docs/data/task_method_20_gap_audit.json"
       ]
     }
   ],
+  "method_blocks": [
+    {
+      "line_id": "single_public_sample_episode",
+      "line_label": "1 sample episode",
+      "block": "Task-head baselines",
+      "methods": [
+        "Minimal",
+        "Neural MLP"
+      ],
+      "scored_records": 40,
+      "direct_scored_records": 40,
+      "proxy_scored_records": 0,
+      "evidence_type": "Direct target metrics on the public sample windows.",
+      "read_as": "Task-lab reproducibility and simple-vs-neural behavior."
+    },
+    {
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "block": "Aligned baseline heads",
+      "methods": [
+        "Metadata simple",
+        "Metadata NN",
+        "Raw-feature simple",
+        "Raw-feature NN"
+      ],
+      "scored_records": 80,
+      "direct_scored_records": 74,
+      "proxy_scored_records": 6,
+      "evidence_type": "Direct processed-target metrics where available; compact proxies for documented raw-target gaps.",
+      "read_as": "Same-split metadata/raw-feature baseline comparison."
+    },
+    {
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "block": "Qwen3-Omni series",
+      "methods": [
+        "Qwen3-Omni v6 LoRA"
+      ],
+      "scored_records": 20,
+      "direct_scored_records": 20,
+      "proxy_scored_records": 0,
+      "evidence_type": "Verified selected-128 Qwen3-Omni v6 LoRA plus source-linked task-specific probes.",
+      "read_as": "Trainable Qwen3-Omni diagnostic baseline on the selected-128 surface."
+    },
+    {
+      "line_id": "selected_128_episode_surface",
+      "line_label": "128 selected episodes",
+      "block": "Cosmos3 series",
+      "methods": [
+        "Cosmos3-Super Reasoner",
+        "Cosmos3-Nano Future Window"
+      ],
+      "scored_records": 40,
+      "direct_scored_records": 40,
+      "proxy_scored_records": 0,
+      "evidence_type": "Verified Cosmos3-Super Reasoner and Cosmos3-Nano Future Window public-safe artifacts.",
+      "read_as": "Cosmos3 reasoner and future-window diagnostics on the selected-128 surface."
+    }
+  ],
+  "related_model_artifacts": [
+    {
+      "name": "Qwen3-Omni v1-v6 run lineage",
+      "role": "Explains the LoRA/evaluation version ladder; v6 is the current 20-task matrix row, v5 remains the pinned prior release, and v1-v4 are lineage/ablation evidence.",
+      "repo": "docs/data/qwen3_omni_run_lineage.json"
+    },
+    {
+      "name": "Cosmos3-Super Forward-Dynamics LoRA",
+      "role": "Separate fine-tuned adapter artifact for forward-dynamics loss metrics; published with weights/results but not counted as a 20-task matrix method row.",
+      "repo": "https://huggingface.co/cy0307/ropedia-cosmos3-super-forward-dynamics-lora-128ep"
+    }
+  ],
   "combined_public_matrix": {
     "task_axes": 20,
     "methods": 9,

docs/data/website_integrity.json

@@ -1,13 +1,13 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T09:20:28+00:00",
+  "generated_at_utc": "2026-06-21T10:08:12+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
     "html_pages": 4,
-    "local_references": 241,
-    "external_reference_count": 152,
-    "json_files": 53,
+    "local_references": 247,
+    "external_reference_count": 153,
+    "json_files": 54,
     "image_assets_referenced": 29,
     "failure_count": 0
   },
@@ -80,8 +80,8 @@
       "name": "project_overview_precedes_progress_ledger",
       "status": "pass",
       "reason": "The project overview should appear before the deeper progress ledger.",
-      "overview_index": 116163,
-      "evidence_index": 156473
+      "overview_index": 118264,
+      "evidence_index": 163038
     },
     {
       "name": "project_status_links_json",
@@ -159,9 +159,9 @@
       "name": "evaluation_protocol_between_overview_and_progress",
       "status": "pass",
       "reason": "The evaluation protocol should appear before the deeper evidence ledger.",
-      "overview_index": 116163,
-      "protocol_index": 152654,
-      "evidence_index": 156473
+      "overview_index": 118264,
+      "protocol_index": 159219,
+      "evidence_index": 163038
     },
     {
       "name": "evaluation_protocol_links_json",
@@ -180,7 +180,7 @@
       "status": "pass",
       "reason": "The Suite anchor should show the task-suite map before the modality atlas.",
       "first_marker_index": 471,
-      "second_marker_index": 3762
+      "second_marker_index": 3794
     },
     {
       "name": "suite_modality_atlas_contains_seven_cards",
@@ -277,7 +277,7 @@
     {
       "path": "index.html",
       "id_count": 95,
-      "reference_count": 213,
+      "reference_count": 219,
       "image_count": 35
     },
     {
@@ -414,6 +414,11 @@
       "bytes": 12181,
       "top_level_type": "dict"
     },
+    {
+      "path": "data/qwen3_omni_run_lineage.json",
+      "bytes": 9211,
+      "top_level_type": "dict"
+    },
     {
       "path": "data/qwen3_v5_v6_comparison.json",
       "bytes": 2814,
@@ -531,12 +536,12 @@
     },
     {
       "path": "data/two_evidence_line_result_summary.json",
-      "bytes": 13689,
+      "bytes": 17223,
       "top_level_type": "dict"
     },
     {
       "path": "data/two_evidence_lines.json",
-      "bytes": 4388,
+      "bytes": 7196,
       "top_level_type": "dict"
     },
     {
@@ -546,7 +551,7 @@
     },
     {
       "path": "data/website_integrity.json",
-      "bytes": 20542,
+      "bytes": 20657,
       "top_level_type": "dict"
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     {

docs/index.html

@@ -4,7 +4,7 @@
   <meta charset="utf-8">
   <meta name="viewport" content="width=device-width, initial-scale=1">
   <title>Ropedia Xperience-10M Task Suite</title>
-  <meta name="description" content="Ropedia Xperience-10M Task Suite organized into two evidence lines: one public sample episode for reproducible task construction and 128 selected episodes for aligned baselines plus Qwen3/Cosmos comparison.">
+  <meta name="description" content="Ropedia Xperience-10M Task Suite organized into two evidence lines: one public sample episode for reproducible task construction and 128 selected episodes for aligned baselines, Qwen3-Omni v6 LoRA, and Cosmos3 series comparison.">
   <meta name="theme-color" content="#020502">
   <meta name="robots" content="index, follow">
   <link rel="canonical" href="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/">
@@ -12,7 +12,7 @@
   <link rel="apple-touch-icon" href="apple-touch-icon.png">
   <link rel="manifest" href="site.webmanifest">
   <meta property="og:title" content="Ropedia Xperience-10M Task Suite">
-  <meta property="og:description" content="A two-line Ropedia Xperience-10M public suite: 1 sample episode for task construction, 128 selected episodes for same-split baselines and Qwen3/Cosmos comparison.">
+  <meta property="og:description" content="A two-line Ropedia Xperience-10M public suite: 1 sample episode for task construction, 128 selected episodes for same-split baselines, Qwen3-Omni v6 LoRA, and Cosmos3 series comparison.">
   <meta property="og:type" content="website">
   <meta property="og:url" content="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/">
   <meta property="og:image" content="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/assets/brand/xperience10m-logo-social-card.png?v=xperience10m-logo-v4">
@@ -1153,6 +1153,16 @@
       text-decoration: none;
     }
     .line-table a:hover { color: var(--green); }
+    .line-table td[data-label]::before {
+      display: none;
+    }
+    .table-note {
+      margin: -14px 0 28px;
+      color: var(--muted);
+      font-size: 13px;
+      line-height: 1.45;
+      max-width: 900px;
+    }
     .task-suite-image {
       display: block;
       margin-top: 30px;
@@ -3432,10 +3442,11 @@
       .site-nav {
         min-height: var(--nav-height);
       }
-      .wrap { width: min(100% - 28px, var(--max)); }
+      .wrap { width: calc(100vw - 28px); max-width: calc(100vw - 28px); }
       .site-nav .wrap,
       .project-tabs-shell .wrap {
-        width: min(100% - 28px, var(--max));
+        width: calc(100vw - 28px);
+        max-width: calc(100vw - 28px);
       }
       .nav-inner {
         position: relative;
@@ -3598,6 +3609,61 @@
         min-height: 52px;
       }
       main > section { scroll-margin-top: 112px; }
+      html,
+      body {
+        max-width: 100%;
+        overflow-x: hidden;
+      }
+      .hero-inner,
+      .hero-inner > *,
+      .hero-radar-panel,
+      .hero-radar-layout,
+      .hero-radar-copy {
+        min-width: 0;
+        max-width: 100%;
+      }
+      .hero-inner {
+        display: block;
+        width: 100%;
+      }
+      .hero,
+      main,
+      .site-nav {
+        max-width: 100vw;
+        overflow-x: hidden;
+      }
+      .hero .wrap {
+        width: min(360px, calc(100% - 28px));
+        max-width: 360px;
+        margin-inline: auto;
+        padding-inline: 0;
+      }
+      h1 {
+        max-width: 100%;
+        font-size: 34px;
+        line-height: 1.04;
+        text-wrap: balance;
+        overflow-wrap: normal;
+      }
+      .eyebrow {
+        display: flex;
+        flex-wrap: wrap;
+        justify-content: center;
+        max-width: 100%;
+        font-size: 11px;
+        line-height: 1.25;
+        text-align: center;
+      }
+      .eyebrow::before {
+        display: none;
+      }
+      .hero-copy {
+        max-width: 100%;
+        font-size: 16px;
+        line-height: 1.56;
+        white-space: normal;
+        overflow-wrap: break-word;
+      }
       .hero-actions {
         display: grid;
         grid-template-columns: 1fr;
@@ -3628,6 +3694,17 @@
         border-bottom: 0;
         padding: 10px 12px;
       }
+      .line-table td[data-label]::before {
+        content: attr(data-label);
+        display: block;
+        margin-bottom: 4px;
+        color: var(--green);
+        font-family: var(--font-mono);
+        font-size: 10px;
+        font-weight: 800;
+        letter-spacing: 0.07em;
+        text-transform: uppercase;
+      }
       .line-table td:first-child {
         width: auto;
         padding-top: 14px;
@@ -3807,8 +3884,8 @@
         <p class="hero-copy">
           The public suite has two result lines. Line 1 uses one public sample
           episode to make the 20-task lab inspectable and reproducible. Line 2
-          uses 128 selected episodes to compare aligned baselines, Qwen3-Omni,
-          and Cosmos branches. The public matrix is complete at 180/180 scored
+          uses 128 selected episodes to compare aligned baselines, Qwen3-Omni
+          v6 LoRA, Cosmos3-Super Reasoner, and Cosmos3-Nano Future Window. The public matrix is complete at 180/180 scored
           method-task records, with six compact-proxy cells explicitly marked.
         </p>
         <div class="hero-actions">
@@ -3899,7 +3976,8 @@
             <div class="hero-method-list" aria-label="Method families shown in the radar">
               <div class="hero-method" style="--method-color:#67e8d1"><strong>Line 1: Minimal + Neural MLP</strong><span>Single public-sample episode; 40/40 direct task scores.</span></div>
               <div class="hero-method" style="--method-color:#f59e0b"><strong>Line 2: metadata + raw baselines</strong><span>Same selected-128 split; all four baseline rows have 20 records, with proxy notes where direct raw targets are absent.</span></div>
-              <div class="hero-method" style="--method-color:#9bb8ff"><strong>Line 2: Qwen3-Omni + Cosmos</strong><span>Qwen3, Cosmos3-Super, and Cosmos3-Nano are represented as selected-128 method rows with source notes in the matrix.</span></div>
+              <div class="hero-method" style="--method-color:#9bb8ff"><strong>Line 2: Qwen3-Omni v6 LoRA</strong><span>One trainable selected-128 model row; 20/20 direct scores from verified LoRA and task-specific probe artifacts.</span></div>
+              <div class="hero-method" style="--method-color:#d8f4a5"><strong>Line 2: Cosmos3 series</strong><span>Cosmos3-Super Reasoner and Cosmos3-Nano Future Window are separate selected-128 method rows; 40/40 direct scores.</span></div>
             </div>
             <div class="hero-task-strip" aria-label="Radar task axis examples">
               <span>01 Action Recognition</span>
@@ -3995,12 +4073,117 @@
               <td>128 selected episodes</td>
               <td>Selected held-out 96/16/16 split; 34,269 exported windows; public-safe metadata/raw-feature artifacts linked to official gated episode paths.</td>
               <td>140/140 selected-128 scores: 134 direct + 6 compact-proxy.</td>
-              <td>Same-split comparison, model-branch diagnostics, Qwen/Cosmos evidence, and scale-up decisions.</td>
+              <td>Same-split comparison, Qwen3-Omni v6 LoRA diagnostics, Cosmos3-Super/Cosmos3-Nano diagnostics, and scale-up decisions.</td>
               <td>Reading compact-proxy cells as direct raw-target measurements.</td>
               <td><a href="data/episode128_task_model_radar.json">128-episode radar JSON</a><br><a href="data/xperience10m_128_episode_feature_index.json">feature index JSON</a><br><a href="data/two_evidence_line_result_summary.json">result summary JSON</a><br><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/TWO_EVIDENCE_LINES.md">line doc</a></td>
             </tr>
           </tbody>
         </table>
+        <table class="line-table" aria-label="Two-line method-block architecture">
+          <thead>
+            <tr>
+              <th>Evidence line</th>
+              <th>Method block</th>
+              <th>Methods</th>
+              <th>Score statement</th>
+              <th>Read as</th>
+            </tr>
+          </thead>
+          <tbody>
+            <tr>
+              <td>1 sample episode</td>
+              <td>Task-head baselines</td>
+              <td>Minimal; Neural MLP</td>
+              <td>40/40 direct scores.</td>
+              <td>Task-lab reproducibility and simple-vs-neural behavior.</td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Aligned baseline heads</td>
+              <td>Metadata simple/NN; raw-feature simple/NN</td>
+              <td>80/80 scores: 74 direct + 6 compact-proxy.</td>
+              <td>Same-split metadata/raw-feature baseline comparison.</td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Qwen3-Omni series</td>
+              <td>Qwen3-Omni v6 LoRA</td>
+              <td>20/20 direct scores from verified selected-128 Qwen3-Omni LoRA and task-specific probes.</td>
+              <td>Trainable Qwen3-Omni diagnostic baseline on the selected-128 surface.</td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Cosmos3 series</td>
+              <td>Cosmos3-Super Reasoner; Cosmos3-Nano Future Window</td>
+              <td>40/40 direct scores from verified public-safe reasoner and future-window artifacts.</td>
+              <td>Cosmos3 reasoner and future-window diagnostics on the selected-128 surface.</td>
+            </tr>
+          </tbody>
+        </table>
+        <p class="table-note">Cosmos3-Super Forward-Dynamics LoRA is published as a separate fine-tuned adapter with weights/results; it is not counted as a 20-task matrix method row.</p>
+        <table class="line-table" aria-label="Qwen3-Omni run version ladder">
+          <thead>
+            <tr>
+              <th>Qwen run</th>
+              <th>What changed</th>
+              <th>Eval samples</th>
+              <th>JSON validity</th>
+              <th>Contact acc.</th>
+              <th>Public role</th>
+            </tr>
+          </thead>
+          <tbody>
+            <tr>
+              <td>v1</td>
+              <td>Selected-128 validation-aware LoRA baseline.</td>
+              <td>448</td>
+              <td>0.8750</td>
+              <td>0.6451</td>
+              <td>Superseded lineage evidence.</td>
+            </tr>
+            <tr>
+              <td>v2</td>
+              <td>Structured-JSON reuse full-8-GPU LoRA.</td>
+              <td>448</td>
+              <td>0.9978</td>
+              <td>0.7188</td>
+              <td>Superseded lineage evidence.</td>
+            </tr>
+            <tr>
+              <td>v3</td>
+              <td>Strict-label prompt/eval over the v2 adapter.</td>
+              <td>448</td>
+              <td>1.0000</td>
+              <td>0.7210</td>
+              <td>Prompt/eval lineage evidence.</td>
+            </tr>
+            <tr>
+              <td>v4</td>
+              <td>Four-epoch structured-JSON LoRA.</td>
+              <td>448</td>
+              <td>1.0000</td>
+              <td>0.7299</td>
+              <td>Superseded metric-tradeoff run.</td>
+            </tr>
+            <tr>
+              <td>v5</td>
+              <td>Multiscale cap96 LoRA.</td>
+              <td>4,032</td>
+              <td>1.0000</td>
+              <td>0.7865</td>
+              <td>Pinned prior release and comparison baseline.</td>
+            </tr>
+            <tr>
+              <td>v6</td>
+              <td>Rank64/lr5e-5 multiscale LoRA plus task-specific probes.</td>
+              <td>4,032</td>
+              <td>0.9990</td>
+              <td>0.8177</td>
+              <td>Current public 20-task Qwen3-Omni row.</td>
+            </tr>
+          </tbody>
+        </table>
+        <p class="table-note">Qwen v1-v6 are run-lineage labels, not the project-level result layers. The public matrix row is Qwen3-Omni v6 LoRA; v5 stays pinned as the prior release. Full details: <a href="data/qwen3_omni_run_lineage.json">qwen3_omni_run_lineage.json</a> and <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/QWEN3_OMNI_RUN_LINEAGE.md">QWEN3_OMNI_RUN_LINEAGE.md</a>.</p>
         <div class="reader-journey" aria-label="Recommended reader journeys">
           <article class="reader-step">
             <small>01 understand</small>
@@ -4023,7 +4206,7 @@
           <article class="reader-step">
             <small>04 extend</small>
             <strong>Choose the next model branch</strong>
-            <p>Use directions and scale-up resources for spatial, world-model, VLA, Qwen3, and Cosmos follow-up work.</p>
+            <p>Use directions and scale-up resources for spatial, world-model, VLA, Qwen3-Omni, and Cosmos3 follow-up work.</p>
             <a href="#directions">Open directions</a>
           </article>
         </div>
@@ -4068,7 +4251,7 @@
             <article class="brief-card">
               <small>results</small>
               <strong>Compare methods cleanly</strong>
-              <p>Single-episode baselines, 128-episode aligned baselines, Qwen3, and Cosmos branches stay separated by evidence type.</p>
+              <p>Single-episode baselines, 128-episode aligned baselines, Qwen3-Omni v6 LoRA, and Cosmos3-Super/Nano branches stay separated by evidence type.</p>
               <div class="reading-links">
                 <a href="#takeaways">takeaways</a>
                 <a href="data/unified_task_model_radar.json">radar data</a>
@@ -4812,7 +4995,7 @@
         <div class="figure-brief">
           <article class="figure-brief-card">
             <h3>Unified plus split radars</h3>
-            <p>The unified radar keeps all 9 methods in one view. The split radars separate the 1-episode Minimal/NN baseline comparison from the 128-episode metadata/raw/Qwen/Cosmos comparison.</p>
+            <p>The unified radar keeps all 9 methods in one view. The split radars separate the 1-episode Minimal/NN baseline comparison from the 128-episode metadata/raw, Qwen3-Omni v6 LoRA, and Cosmos3-Super/Nano comparison.</p>
           </article>
           <article class="figure-brief-card">
             <h3>Metric normalization</h3>
@@ -4972,7 +5155,7 @@
           <article class="suite-line-card">
             <small>128 episode results</small>
             <h3>Scale-up evidence</h3>
-            <p>Metadata/raw baselines and Qwen/Cosmos branches use the aligned 128-episode surface. It has 134 direct scores plus 6 compact-proxy scores.</p>
+            <p>Metadata/raw baselines, Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, and Cosmos3-Nano Future Window use the aligned 128-episode surface. It has 134 direct scores plus 6 compact-proxy scores.</p>
             <div class="line-claim">
               <div><span>best read as</span><p>A same-split comparison table with explicit source and proxy status.</p></div>
             </div>
@@ -5026,6 +5209,52 @@
             </tr>
           </tbody>
         </table>
+        <table class="line-table" aria-label="Method ownership inside each evidence line">
+          <thead>
+            <tr>
+              <th>Line</th>
+              <th>Block</th>
+              <th>Methods</th>
+              <th>Records</th>
+              <th>Evidence type</th>
+              <th>Primary artifact</th>
+            </tr>
+          </thead>
+          <tbody>
+            <tr>
+              <td>1 sample episode</td>
+              <td>Task-head baselines</td>
+              <td>Minimal; Neural MLP</td>
+              <td>40 direct</td>
+              <td>Direct target metrics on the public sample windows.</td>
+              <td><a href="data/single_episode_task_model_radar.json">single-episode radar JSON</a></td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Aligned baseline heads</td>
+              <td>Metadata simple/NN; raw-feature simple/NN</td>
+              <td>74 direct + 6 compact-proxy</td>
+              <td>Processed-target metrics where available; proxy cells remain source-linked.</td>
+              <td><a href="data/task_method_20_gap_audit.json">score/proxy audit</a></td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Qwen3-Omni series</td>
+              <td>Qwen3-Omni v6 LoRA</td>
+              <td>20 direct</td>
+              <td>Verified selected-128 LoRA and task-specific probe artifacts.</td>
+              <td><a href="data/omni_model_comparison.json">model comparison JSON</a></td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Cosmos3 series</td>
+              <td>Cosmos3-Super Reasoner; Cosmos3-Nano Future Window</td>
+              <td>40 direct</td>
+              <td>Verified reasoner and future-window public-safe artifacts; forward-dynamics LoRA is a separate adapter artifact outside the 20-task method rows.</td>
+              <td><a href="data/omni_model_comparison.json">model comparison JSON</a></td>
+            </tr>
+          </tbody>
+        </table>
         <div class="artifact-grid">
           <article class="artifact primary-artifact">
             <div>
@@ -5399,7 +5628,7 @@
           <article class="resource-mode">
             <small>scale</small>
             <strong>Continue model work</strong>
-            <p>Use Qwen3/Cosmos packages, 128-episode feature index, and foundation-model plans for the next runs.</p>
+            <p>Use Qwen3-Omni v6, Cosmos3-Super/Nano packages, the 128-episode feature index, and foundation-model plans for the next runs.</p>
             <a href="#omni-scale-up">Open scale-up</a>
           </article>
         </div>
@@ -5454,8 +5683,8 @@
               <article class="artifact"><h3>GitHub Package</h3><p>Static dashboard container published to GitHub Container Registry for local browsing with Docker, without raw data or model weights.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/pkgs/container/ropedia-xperience-10m-task-suite">GHCR package</a></article>
               <article class="artifact"><h3>Derived HF artifacts</h3><p>Metrics, predictions, docs, and lightweight derived files without raw data redistribution.</p><a href="https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts">artifact collection</a></article>
               <article class="artifact"><h3>HF baseline models</h3><p>Minimal NumPy softmax, ridge baselines, and neural task-head model files.</p><a href="https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines">model repo</a></article>
-              <article class="artifact"><h3>HF weights + results</h3><p>Consolidated public-safe baseline weights, Qwen3/Cosmos adapters, verified results, analysis files, and manifest.</p><a href="https://huggingface.co/cy0307/ropedia-xperience-10m-weights-results">weights/results repo</a></article>
-              <article class="artifact"><h3>HF collection</h3><p>Space, artifacts, baseline models, and verified Qwen3/Cosmos3 adapter repos grouped into one public project collection.</p><a href="https://huggingface.co/collections/cy0307/ropedia-xperience-10m-task-suite">collection</a></article>
+              <article class="artifact"><h3>HF weights + results</h3><p>Consolidated public-safe baseline weights, Qwen3-Omni and Cosmos3 adapters/packages, verified results, analysis files, and manifest.</p><a href="https://huggingface.co/cy0307/ropedia-xperience-10m-weights-results">weights/results repo</a></article>
+              <article class="artifact"><h3>HF collection</h3><p>Space, artifacts, baseline models, Qwen3-Omni v6 LoRA, Cosmos3-Super, and Cosmos3-Nano repos grouped into one public project collection.</p><a href="https://huggingface.co/collections/cy0307/ropedia-xperience-10m-task-suite">collection</a></article>
               <article class="artifact"><h3>Current all-feature action model</h3><p>Classifier metrics, predictions, confusion matrix, and model weights.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/results/min_all_modalities_action_model/metrics.json">model metrics</a></article>
               <article class="artifact"><h3>Project packet</h3><p>Compact route through the project for readers who want the shortest path from scope to results after choosing a surface.</p><a href="data/project_packet.json">project packet</a></article>
             </div>
@@ -5472,7 +5701,7 @@
               <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>
               <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>
               <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>
-              <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>
+              <article class="artifact"><h3>Qwen3-Omni LoRA group</h3><p>Separates the 1-episode sensor-adapter smoke test from Qwen run v1-v6. v6 is the current 20-task matrix row, while v5 remains the pinned prior release.</p><a href="data/qwen3_omni_run_lineage.json">Qwen v1-v6 lineage</a><a href="data/omni_model_comparison.json">Qwen group</a></article>
               <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>
               <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>
               <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>
@@ -5868,7 +6097,7 @@ python scripts/validate_publication_package.py</code></pre>
       diagnostics: "Best for charts and error-analysis evidence.",
       artifacts: "Best for finding files, mirrors, weights, scripts, and checks.",
       evidence: "Best for current experiment status and milestones.",
-      "omni-scale-up": "Best for Qwen3/Cosmos model-branch status.",
+      "omni-scale-up": "Best for Qwen3-Omni and Cosmos3 model-branch status.",
       run: "Best for reproduction commands."
     };
     const sectionTabMap = Object.fromEntries(tabSections.map((section) => [section.id, section.dataset.projectTab]));
@@ -6394,6 +6623,19 @@ python scripts/validate_publication_package.py</code></pre>
       playerTimer = window.setInterval(advancePlayer, 2600);
     }
 
+    function labelResponsiveTables() {
+      document.querySelectorAll(".line-table").forEach((table) => {
+        const headers = Array.from(table.querySelectorAll("thead th")).map((header) => header.textContent.trim());
+        table.querySelectorAll("tbody tr").forEach((row) => {
+          Array.from(row.children).forEach((cell, index) => {
+            if (headers[index] && !cell.dataset.label) {
+              cell.dataset.label = headers[index];
+            }
+          });
+        });
+      });
+    }
+
     async function initTaskSurface() {
       try {
         const response = await fetch("data/task_walkthroughs.json", { cache: "no-cache" });
@@ -6424,6 +6666,7 @@ python scripts/validate_publication_package.py</code></pre>
         setActiveStage(Number(button.dataset.stage));
       });
     });
+    labelResponsiveTables();
     initTaskSurface();
 
     document.querySelectorAll("[data-copy]").forEach((button) => {

index.html

@@ -4,7 +4,7 @@
   <meta charset="utf-8">
   <meta name="viewport" content="width=device-width, initial-scale=1">
   <title>Ropedia Xperience-10M Task Suite</title>
-  <meta name="description" content="Ropedia Xperience-10M Task Suite organized into two evidence lines: one public sample episode for reproducible task construction and 128 selected episodes for aligned baselines plus Qwen3/Cosmos comparison.">
+  <meta name="description" content="Ropedia Xperience-10M Task Suite organized into two evidence lines: one public sample episode for reproducible task construction and 128 selected episodes for aligned baselines, Qwen3-Omni v6 LoRA, and Cosmos3 series comparison.">
   <meta name="theme-color" content="#020502">
   <meta name="robots" content="index, follow">
   <link rel="canonical" href="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/">
@@ -12,7 +12,7 @@
   <link rel="apple-touch-icon" href="apple-touch-icon.png">
   <link rel="manifest" href="site.webmanifest">
   <meta property="og:title" content="Ropedia Xperience-10M Task Suite">
-  <meta property="og:description" content="A two-line Ropedia Xperience-10M public suite: 1 sample episode for task construction, 128 selected episodes for same-split baselines and Qwen3/Cosmos comparison.">
+  <meta property="og:description" content="A two-line Ropedia Xperience-10M public suite: 1 sample episode for task construction, 128 selected episodes for same-split baselines, Qwen3-Omni v6 LoRA, and Cosmos3 series comparison.">
   <meta property="og:type" content="website">
   <meta property="og:url" content="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/">
   <meta property="og:image" content="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/assets/brand/xperience10m-logo-social-card.png?v=xperience10m-logo-v4">
@@ -1153,6 +1153,16 @@
       text-decoration: none;
     }
     .line-table a:hover { color: var(--green); }
+    .line-table td[data-label]::before {
+      display: none;
+    }
+    .table-note {
+      margin: -14px 0 28px;
+      color: var(--muted);
+      font-size: 13px;
+      line-height: 1.45;
+      max-width: 900px;
+    }
     .task-suite-image {
       display: block;
       margin-top: 30px;
@@ -3432,10 +3442,11 @@
       .site-nav {
         min-height: var(--nav-height);
       }
-      .wrap { width: min(100% - 28px, var(--max)); }
+      .wrap { width: calc(100vw - 28px); max-width: calc(100vw - 28px); }
       .site-nav .wrap,
       .project-tabs-shell .wrap {
-        width: min(100% - 28px, var(--max));
+        width: calc(100vw - 28px);
+        max-width: calc(100vw - 28px);
       }
       .nav-inner {
         position: relative;
@@ -3598,6 +3609,61 @@
         min-height: 52px;
       }
       main > section { scroll-margin-top: 112px; }
+      html,
+      body {
+        max-width: 100%;
+        overflow-x: hidden;
+      }
+      .hero-inner,
+      .hero-inner > *,
+      .hero-radar-panel,
+      .hero-radar-layout,
+      .hero-radar-copy {
+        min-width: 0;
+        max-width: 100%;
+      }
+      .hero-inner {
+        display: block;
+        width: 100%;
+      }
+      .hero,
+      main,
+      .site-nav {
+        max-width: 100vw;
+        overflow-x: hidden;
+      }
+      .hero .wrap {
+        width: min(360px, calc(100% - 28px));
+        max-width: 360px;
+        margin-inline: auto;
+        padding-inline: 0;
+      }
+      h1 {
+        max-width: 100%;
+        font-size: 34px;
+        line-height: 1.04;
+        text-wrap: balance;
+        overflow-wrap: normal;
+      }
+      .eyebrow {
+        display: flex;
+        flex-wrap: wrap;
+        justify-content: center;
+        max-width: 100%;
+        font-size: 11px;
+        line-height: 1.25;
+        text-align: center;
+      }
+      .eyebrow::before {
+        display: none;
+      }
+      .hero-copy {
+        max-width: 100%;
+        font-size: 16px;
+        line-height: 1.56;
+        white-space: normal;
+        overflow-wrap: break-word;
+      }
       .hero-actions {
         display: grid;
         grid-template-columns: 1fr;
@@ -3628,6 +3694,17 @@
         border-bottom: 0;
         padding: 10px 12px;
       }
+      .line-table td[data-label]::before {
+        content: attr(data-label);
+        display: block;
+        margin-bottom: 4px;
+        color: var(--green);
+        font-family: var(--font-mono);
+        font-size: 10px;
+        font-weight: 800;
+        letter-spacing: 0.07em;
+        text-transform: uppercase;
+      }
       .line-table td:first-child {
         width: auto;
         padding-top: 14px;
@@ -3807,8 +3884,8 @@
         <p class="hero-copy">
           The public suite has two result lines. Line 1 uses one public sample
           episode to make the 20-task lab inspectable and reproducible. Line 2
-          uses 128 selected episodes to compare aligned baselines, Qwen3-Omni,
-          and Cosmos branches. The public matrix is complete at 180/180 scored
+          uses 128 selected episodes to compare aligned baselines, Qwen3-Omni
+          v6 LoRA, Cosmos3-Super Reasoner, and Cosmos3-Nano Future Window. The public matrix is complete at 180/180 scored
           method-task records, with six compact-proxy cells explicitly marked.
         </p>
         <div class="hero-actions">
@@ -3899,7 +3976,8 @@
             <div class="hero-method-list" aria-label="Method families shown in the radar">
               <div class="hero-method" style="--method-color:#67e8d1"><strong>Line 1: Minimal + Neural MLP</strong><span>Single public-sample episode; 40/40 direct task scores.</span></div>
               <div class="hero-method" style="--method-color:#f59e0b"><strong>Line 2: metadata + raw baselines</strong><span>Same selected-128 split; all four baseline rows have 20 records, with proxy notes where direct raw targets are absent.</span></div>
-              <div class="hero-method" style="--method-color:#9bb8ff"><strong>Line 2: Qwen3-Omni + Cosmos</strong><span>Qwen3, Cosmos3-Super, and Cosmos3-Nano are represented as selected-128 method rows with source notes in the matrix.</span></div>
+              <div class="hero-method" style="--method-color:#9bb8ff"><strong>Line 2: Qwen3-Omni v6 LoRA</strong><span>One trainable selected-128 model row; 20/20 direct scores from verified LoRA and task-specific probe artifacts.</span></div>
+              <div class="hero-method" style="--method-color:#d8f4a5"><strong>Line 2: Cosmos3 series</strong><span>Cosmos3-Super Reasoner and Cosmos3-Nano Future Window are separate selected-128 method rows; 40/40 direct scores.</span></div>
             </div>
             <div class="hero-task-strip" aria-label="Radar task axis examples">
               <span>01 Action Recognition</span>
@@ -3995,12 +4073,117 @@
               <td>128 selected episodes</td>
               <td>Selected held-out 96/16/16 split; 34,269 exported windows; public-safe metadata/raw-feature artifacts linked to official gated episode paths.</td>
               <td>140/140 selected-128 scores: 134 direct + 6 compact-proxy.</td>
-              <td>Same-split comparison, model-branch diagnostics, Qwen/Cosmos evidence, and scale-up decisions.</td>
+              <td>Same-split comparison, Qwen3-Omni v6 LoRA diagnostics, Cosmos3-Super/Cosmos3-Nano diagnostics, and scale-up decisions.</td>
               <td>Reading compact-proxy cells as direct raw-target measurements.</td>
               <td><a href="data/episode128_task_model_radar.json">128-episode radar JSON</a><br><a href="data/xperience10m_128_episode_feature_index.json">feature index JSON</a><br><a href="data/two_evidence_line_result_summary.json">result summary JSON</a><br><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/TWO_EVIDENCE_LINES.md">line doc</a></td>
             </tr>
           </tbody>
         </table>
+        <table class="line-table" aria-label="Two-line method-block architecture">
+          <thead>
+            <tr>
+              <th>Evidence line</th>
+              <th>Method block</th>
+              <th>Methods</th>
+              <th>Score statement</th>
+              <th>Read as</th>
+            </tr>
+          </thead>
+          <tbody>
+            <tr>
+              <td>1 sample episode</td>
+              <td>Task-head baselines</td>
+              <td>Minimal; Neural MLP</td>
+              <td>40/40 direct scores.</td>
+              <td>Task-lab reproducibility and simple-vs-neural behavior.</td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Aligned baseline heads</td>
+              <td>Metadata simple/NN; raw-feature simple/NN</td>
+              <td>80/80 scores: 74 direct + 6 compact-proxy.</td>
+              <td>Same-split metadata/raw-feature baseline comparison.</td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Qwen3-Omni series</td>
+              <td>Qwen3-Omni v6 LoRA</td>
+              <td>20/20 direct scores from verified selected-128 Qwen3-Omni LoRA and task-specific probes.</td>
+              <td>Trainable Qwen3-Omni diagnostic baseline on the selected-128 surface.</td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Cosmos3 series</td>
+              <td>Cosmos3-Super Reasoner; Cosmos3-Nano Future Window</td>
+              <td>40/40 direct scores from verified public-safe reasoner and future-window artifacts.</td>
+              <td>Cosmos3 reasoner and future-window diagnostics on the selected-128 surface.</td>
+            </tr>
+          </tbody>
+        </table>
+        <p class="table-note">Cosmos3-Super Forward-Dynamics LoRA is published as a separate fine-tuned adapter with weights/results; it is not counted as a 20-task matrix method row.</p>
+        <table class="line-table" aria-label="Qwen3-Omni run version ladder">
+          <thead>
+            <tr>
+              <th>Qwen run</th>
+              <th>What changed</th>
+              <th>Eval samples</th>
+              <th>JSON validity</th>
+              <th>Contact acc.</th>
+              <th>Public role</th>
+            </tr>
+          </thead>
+          <tbody>
+            <tr>
+              <td>v1</td>
+              <td>Selected-128 validation-aware LoRA baseline.</td>
+              <td>448</td>
+              <td>0.8750</td>
+              <td>0.6451</td>
+              <td>Superseded lineage evidence.</td>
+            </tr>
+            <tr>
+              <td>v2</td>
+              <td>Structured-JSON reuse full-8-GPU LoRA.</td>
+              <td>448</td>
+              <td>0.9978</td>
+              <td>0.7188</td>
+              <td>Superseded lineage evidence.</td>
+            </tr>
+            <tr>
+              <td>v3</td>
+              <td>Strict-label prompt/eval over the v2 adapter.</td>
+              <td>448</td>
+              <td>1.0000</td>
+              <td>0.7210</td>
+              <td>Prompt/eval lineage evidence.</td>
+            </tr>
+            <tr>
+              <td>v4</td>
+              <td>Four-epoch structured-JSON LoRA.</td>
+              <td>448</td>
+              <td>1.0000</td>
+              <td>0.7299</td>
+              <td>Superseded metric-tradeoff run.</td>
+            </tr>
+            <tr>
+              <td>v5</td>
+              <td>Multiscale cap96 LoRA.</td>
+              <td>4,032</td>
+              <td>1.0000</td>
+              <td>0.7865</td>
+              <td>Pinned prior release and comparison baseline.</td>
+            </tr>
+            <tr>
+              <td>v6</td>
+              <td>Rank64/lr5e-5 multiscale LoRA plus task-specific probes.</td>
+              <td>4,032</td>
+              <td>0.9990</td>
+              <td>0.8177</td>
+              <td>Current public 20-task Qwen3-Omni row.</td>
+            </tr>
+          </tbody>
+        </table>
+        <p class="table-note">Qwen v1-v6 are run-lineage labels, not the project-level result layers. The public matrix row is Qwen3-Omni v6 LoRA; v5 stays pinned as the prior release. Full details: <a href="data/qwen3_omni_run_lineage.json">qwen3_omni_run_lineage.json</a> and <a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/QWEN3_OMNI_RUN_LINEAGE.md">QWEN3_OMNI_RUN_LINEAGE.md</a>.</p>
         <div class="reader-journey" aria-label="Recommended reader journeys">
           <article class="reader-step">
             <small>01 understand</small>
@@ -4023,7 +4206,7 @@
           <article class="reader-step">
             <small>04 extend</small>
             <strong>Choose the next model branch</strong>
-            <p>Use directions and scale-up resources for spatial, world-model, VLA, Qwen3, and Cosmos follow-up work.</p>
+            <p>Use directions and scale-up resources for spatial, world-model, VLA, Qwen3-Omni, and Cosmos3 follow-up work.</p>
             <a href="#directions">Open directions</a>
           </article>
         </div>
@@ -4068,7 +4251,7 @@
             <article class="brief-card">
               <small>results</small>
               <strong>Compare methods cleanly</strong>
-              <p>Single-episode baselines, 128-episode aligned baselines, Qwen3, and Cosmos branches stay separated by evidence type.</p>
+              <p>Single-episode baselines, 128-episode aligned baselines, Qwen3-Omni v6 LoRA, and Cosmos3-Super/Nano branches stay separated by evidence type.</p>
               <div class="reading-links">
                 <a href="#takeaways">takeaways</a>
                 <a href="data/unified_task_model_radar.json">radar data</a>
@@ -4812,7 +4995,7 @@
         <div class="figure-brief">
           <article class="figure-brief-card">
             <h3>Unified plus split radars</h3>
-            <p>The unified radar keeps all 9 methods in one view. The split radars separate the 1-episode Minimal/NN baseline comparison from the 128-episode metadata/raw/Qwen/Cosmos comparison.</p>
+            <p>The unified radar keeps all 9 methods in one view. The split radars separate the 1-episode Minimal/NN baseline comparison from the 128-episode metadata/raw, Qwen3-Omni v6 LoRA, and Cosmos3-Super/Nano comparison.</p>
           </article>
           <article class="figure-brief-card">
             <h3>Metric normalization</h3>
@@ -4972,7 +5155,7 @@
           <article class="suite-line-card">
             <small>128 episode results</small>
             <h3>Scale-up evidence</h3>
-            <p>Metadata/raw baselines and Qwen/Cosmos branches use the aligned 128-episode surface. It has 134 direct scores plus 6 compact-proxy scores.</p>
+            <p>Metadata/raw baselines, Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, and Cosmos3-Nano Future Window use the aligned 128-episode surface. It has 134 direct scores plus 6 compact-proxy scores.</p>
             <div class="line-claim">
               <div><span>best read as</span><p>A same-split comparison table with explicit source and proxy status.</p></div>
             </div>
@@ -5026,6 +5209,52 @@
             </tr>
           </tbody>
         </table>
+        <table class="line-table" aria-label="Method ownership inside each evidence line">
+          <thead>
+            <tr>
+              <th>Line</th>
+              <th>Block</th>
+              <th>Methods</th>
+              <th>Records</th>
+              <th>Evidence type</th>
+              <th>Primary artifact</th>
+            </tr>
+          </thead>
+          <tbody>
+            <tr>
+              <td>1 sample episode</td>
+              <td>Task-head baselines</td>
+              <td>Minimal; Neural MLP</td>
+              <td>40 direct</td>
+              <td>Direct target metrics on the public sample windows.</td>
+              <td><a href="data/single_episode_task_model_radar.json">single-episode radar JSON</a></td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Aligned baseline heads</td>
+              <td>Metadata simple/NN; raw-feature simple/NN</td>
+              <td>74 direct + 6 compact-proxy</td>
+              <td>Processed-target metrics where available; proxy cells remain source-linked.</td>
+              <td><a href="data/task_method_20_gap_audit.json">score/proxy audit</a></td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Qwen3-Omni series</td>
+              <td>Qwen3-Omni v6 LoRA</td>
+              <td>20 direct</td>
+              <td>Verified selected-128 LoRA and task-specific probe artifacts.</td>
+              <td><a href="data/omni_model_comparison.json">model comparison JSON</a></td>
+            </tr>
+            <tr>
+              <td>128 selected episodes</td>
+              <td>Cosmos3 series</td>
+              <td>Cosmos3-Super Reasoner; Cosmos3-Nano Future Window</td>
+              <td>40 direct</td>
+              <td>Verified reasoner and future-window public-safe artifacts; forward-dynamics LoRA is a separate adapter artifact outside the 20-task method rows.</td>
+              <td><a href="data/omni_model_comparison.json">model comparison JSON</a></td>
+            </tr>
+          </tbody>
+        </table>
         <div class="artifact-grid">
           <article class="artifact primary-artifact">
             <div>
@@ -5399,7 +5628,7 @@
           <article class="resource-mode">
             <small>scale</small>
             <strong>Continue model work</strong>
-            <p>Use Qwen3/Cosmos packages, 128-episode feature index, and foundation-model plans for the next runs.</p>
+            <p>Use Qwen3-Omni v6, Cosmos3-Super/Nano packages, the 128-episode feature index, and foundation-model plans for the next runs.</p>
             <a href="#omni-scale-up">Open scale-up</a>
           </article>
         </div>
@@ -5454,8 +5683,8 @@
               <article class="artifact"><h3>GitHub Package</h3><p>Static dashboard container published to GitHub Container Registry for local browsing with Docker, without raw data or model weights.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/pkgs/container/ropedia-xperience-10m-task-suite">GHCR package</a></article>
               <article class="artifact"><h3>Derived HF artifacts</h3><p>Metrics, predictions, docs, and lightweight derived files without raw data redistribution.</p><a href="https://huggingface.co/datasets/cy0307/ropedia-xperience-10m-task-suite-artifacts">artifact collection</a></article>
               <article class="artifact"><h3>HF baseline models</h3><p>Minimal NumPy softmax, ridge baselines, and neural task-head model files.</p><a href="https://huggingface.co/cy0307/ropedia-xperience-10m-task-baselines">model repo</a></article>
-              <article class="artifact"><h3>HF weights + results</h3><p>Consolidated public-safe baseline weights, Qwen3/Cosmos adapters, verified results, analysis files, and manifest.</p><a href="https://huggingface.co/cy0307/ropedia-xperience-10m-weights-results">weights/results repo</a></article>
-              <article class="artifact"><h3>HF collection</h3><p>Space, artifacts, baseline models, and verified Qwen3/Cosmos3 adapter repos grouped into one public project collection.</p><a href="https://huggingface.co/collections/cy0307/ropedia-xperience-10m-task-suite">collection</a></article>
+              <article class="artifact"><h3>HF weights + results</h3><p>Consolidated public-safe baseline weights, Qwen3-Omni and Cosmos3 adapters/packages, verified results, analysis files, and manifest.</p><a href="https://huggingface.co/cy0307/ropedia-xperience-10m-weights-results">weights/results repo</a></article>
+              <article class="artifact"><h3>HF collection</h3><p>Space, artifacts, baseline models, Qwen3-Omni v6 LoRA, Cosmos3-Super, and Cosmos3-Nano repos grouped into one public project collection.</p><a href="https://huggingface.co/collections/cy0307/ropedia-xperience-10m-task-suite">collection</a></article>
               <article class="artifact"><h3>Current all-feature action model</h3><p>Classifier metrics, predictions, confusion matrix, and model weights.</p><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/results/min_all_modalities_action_model/metrics.json">model metrics</a></article>
               <article class="artifact"><h3>Project packet</h3><p>Compact route through the project for readers who want the shortest path from scope to results after choosing a surface.</p><a href="data/project_packet.json">project packet</a></article>
             </div>
@@ -5472,7 +5701,7 @@
               <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>
               <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>
               <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>
-              <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>
+              <article class="artifact"><h3>Qwen3-Omni LoRA group</h3><p>Separates the 1-episode sensor-adapter smoke test from Qwen run v1-v6. v6 is the current 20-task matrix row, while v5 remains the pinned prior release.</p><a href="data/qwen3_omni_run_lineage.json">Qwen v1-v6 lineage</a><a href="data/omni_model_comparison.json">Qwen group</a></article>
               <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>
               <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>
               <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>
@@ -5868,7 +6097,7 @@ python scripts/validate_publication_package.py</code></pre>
       diagnostics: "Best for charts and error-analysis evidence.",
       artifacts: "Best for finding files, mirrors, weights, scripts, and checks.",
       evidence: "Best for current experiment status and milestones.",
-      "omni-scale-up": "Best for Qwen3/Cosmos model-branch status.",
+      "omni-scale-up": "Best for Qwen3-Omni and Cosmos3 model-branch status.",
       run: "Best for reproduction commands."
     };
     const sectionTabMap = Object.fromEntries(tabSections.map((section) => [section.id, section.dataset.projectTab]));
@@ -6394,6 +6623,19 @@ python scripts/validate_publication_package.py</code></pre>
       playerTimer = window.setInterval(advancePlayer, 2600);
     }
 
+    function labelResponsiveTables() {
+      document.querySelectorAll(".line-table").forEach((table) => {
+        const headers = Array.from(table.querySelectorAll("thead th")).map((header) => header.textContent.trim());
+        table.querySelectorAll("tbody tr").forEach((row) => {
+          Array.from(row.children).forEach((cell, index) => {
+            if (headers[index] && !cell.dataset.label) {
+              cell.dataset.label = headers[index];
+            }
+          });
+        });
+      });
+    }
+
     async function initTaskSurface() {
       try {
         const response = await fetch("data/task_walkthroughs.json", { cache: "no-cache" });
@@ -6424,6 +6666,7 @@ python scripts/validate_publication_package.py</code></pre>
         setActiveStage(Number(button.dataset.stage));
       });
     });
+    labelResponsiveTables();
     initTaskSurface();
 
     document.querySelectorAll("[data-copy]").forEach((button) => {

scripts/build_multilingual_public_readmes.py

@@ -63,11 +63,11 @@ def hero(title: str, tagline: str, active: str) -> str:
 
 ENGLISH_TOP = f"""{hero(
     "Ropedia Xperience-10M Task Suite",
-    "A multilingual public research surface for Xperience-10M: sample data, 20 embodied-AI tasks, baselines, Qwen3/Cosmos diagnostics, and foundation-model training directions.",
+    "A multilingual public research surface for Xperience-10M: sample data, 20 embodied-AI tasks, baselines, Qwen3-Omni and Cosmos3 diagnostics, and foundation-model training directions.",
     "en",
 )}
 
-**Ropedia Xperience-10M Task Suite** is organized as two public result lines, not one blended benchmark. The 1-sample line is a fully inspectable task lab. The selected-128 line is the comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Every score points back to a source artifact and keeps direct-vs-proxy status visible.
+**Ropedia Xperience-10M Task Suite** is organized as two public result lines, not one blended benchmark. The 1-sample line is a fully inspectable task lab. The selected-128 line is the comparison surface for aligned baselines, the Qwen3-Omni series, and the Cosmos3 series. Every score points back to a source artifact and keeps direct-vs-proxy status visible.
 
 **Updated:** {UPDATED}.
 
@@ -121,7 +121,7 @@ The multilingual README files are reader guides. The canonical technical evidenc
     </tr>
     <tr>
       <td><strong>Line 2 methods</strong></td>
-      <td>Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano cover all 20 selected-128 task axes: 140/140 scores.</td>
+      <td>Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, and Cosmos3-Nano Future Window cover all 20 selected-128 task axes: 140/140 scores.</td>
     </tr>
     <tr>
       <td><strong>Foundation directions</strong></td>
@@ -129,7 +129,7 @@ The multilingual README files are reader guides. The canonical technical evidenc
     </tr>
     <tr>
       <td><strong>Public mirrors</strong></td>
-      <td>GitHub, GitHub Pages, HF Space, HF artifact dataset, HF baseline model repo, Qwen3/Cosmos model repos, and HF collection.</td>
+      <td>GitHub, GitHub Pages, HF Space, HF artifact dataset, HF baseline model repo, Qwen3-Omni and Cosmos3 model repos, and HF collection.</td>
     </tr>
   </tbody>
 </table>
@@ -211,11 +211,88 @@ The public suite is organized around two result lines. Keep them separate when r
   </tbody>
 </table>
 
+### Method Blocks
+
+<table>
+  <thead>
+    <tr>
+      <th width="20%">Evidence line</th>
+      <th width="20%">Method block</th>
+      <th width="24%">Methods</th>
+      <th width="18%">Score statement</th>
+      <th>Read as</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td><strong>1 sample episode</strong></td>
+      <td>Task-head baselines</td>
+      <td>Minimal; Neural MLP</td>
+      <td>40/40 direct scores.</td>
+      <td>Task-lab reproducibility and simple-vs-neural behavior.</td>
+    </tr>
+    <tr>
+      <td><strong>128 selected episodes</strong></td>
+      <td>Aligned baseline heads</td>
+      <td>Metadata simple/NN; raw-feature simple/NN</td>
+      <td>80/80 scores: 74 direct + 6 compact-proxy.</td>
+      <td>Same-split metadata/raw-feature baseline comparison.</td>
+    </tr>
+    <tr>
+      <td><strong>128 selected episodes</strong></td>
+      <td>Qwen3-Omni series</td>
+      <td>Qwen3-Omni v6 LoRA</td>
+      <td>20/20 direct scores from verified selected-128 Qwen3-Omni LoRA and task-specific probes.</td>
+      <td>Trainable Qwen3-Omni diagnostic baseline on the selected-128 surface.</td>
+    </tr>
+    <tr>
+      <td><strong>128 selected episodes</strong></td>
+      <td>Cosmos3 series</td>
+      <td>Cosmos3-Super Reasoner; Cosmos3-Nano Future Window</td>
+      <td>40/40 direct scores from verified public-safe reasoner and future-window artifacts.</td>
+      <td>Cosmos3 reasoner and future-window diagnostics on the selected-128 surface.</td>
+    </tr>
+  </tbody>
+</table>
+
+Cosmos3-Super Forward-Dynamics LoRA is published as a separate fine-tuned adapter artifact with weights/results; it is not counted as a 20-task matrix method row.
+
+### Qwen3-Omni Run Versions
+
+These are Qwen3-Omni run versions, not the three project-level public result layers. The 20-task matrix uses **Qwen3-Omni v6 LoRA**. v5 remains the pinned prior release. v1-v4 are lineage/ablation evidence.
+
+<table>
+  <thead>
+    <tr>
+      <th width="10%">Run</th>
+      <th width="26%">What changed</th>
+      <th width="12%">Eval samples</th>
+      <th width="12%">JSON validity</th>
+      <th width="12%">Contact acc.</th>
+      <th>Public role</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr><td><strong>v1</strong></td><td>Selected-128 validation-aware LoRA baseline.</td><td>448</td><td>0.8750</td><td>0.6451</td><td>Superseded lineage evidence.</td></tr>
+    <tr><td><strong>v2</strong></td><td>Structured-JSON reuse full-8-GPU LoRA.</td><td>448</td><td>0.9978</td><td>0.7188</td><td>Superseded lineage evidence.</td></tr>
+    <tr><td><strong>v3</strong></td><td>Strict-label prompt/eval over the v2 adapter.</td><td>448</td><td>1.0000</td><td>0.7210</td><td>Prompt/eval lineage evidence.</td></tr>
+    <tr><td><strong>v4</strong></td><td>Four-epoch structured-JSON LoRA.</td><td>448</td><td>1.0000</td><td>0.7299</td><td>Superseded metric tradeoff run.</td></tr>
+    <tr><td><strong>v5</strong></td><td>Multiscale cap96 LoRA.</td><td>4,032</td><td>1.0000</td><td>0.7865</td><td>Pinned prior release and comparison baseline.</td></tr>
+    <tr><td><strong>v6</strong></td><td>Rank64/lr5e-5 multiscale LoRA.</td><td>4,032</td><td>0.9990</td><td>0.8177</td><td>Current public 20-task Qwen row.</td></tr>
+  </tbody>
+</table>
+
+Detailed lineage:
+[`QWEN3_OMNI_RUN_LINEAGE.md`](QWEN3_OMNI_RUN_LINEAGE.md) and
+[`qwen3_omni_run_lineage.json`](docs/data/qwen3_omni_run_lineage.json).
+
 Result entry points:
 [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md),
 [`two_evidence_lines.json`](docs/data/two_evidence_lines.json),
 [`TWO_EVIDENCE_LINE_RESULT_SUMMARY.md`](TWO_EVIDENCE_LINE_RESULT_SUMMARY.md),
 [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json),
+[`QWEN3_OMNI_RUN_LINEAGE.md`](QWEN3_OMNI_RUN_LINEAGE.md),
+[`qwen3_omni_run_lineage.json`](docs/data/qwen3_omni_run_lineage.json),
 [`single_episode_task_model_radar.json`](docs/data/single_episode_task_model_radar.json),
 [`episode128_task_model_radar.json`](docs/data/episode128_task_model_radar.json),
 [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), and
@@ -275,7 +352,7 @@ Result entry points:
 LANGUAGE_GUIDES = {
     "zh": {
         "title": "Ropedia Xperience-10M 任务套件",
-        "tagline": "面向 Xperience-10M 的多语言公开研究入口：样本数据、20 个具身智能任务、基线、Qwen3/Cosmos 诊断结果，以及基础模型训练方向。",
+        "tagline": "面向 Xperience-10M 的多语言公开研究入口：样本数据、20 个具身智能任务、基线、Qwen3-Omni 与 Cosmos3 诊断结果，以及基础模型训练方向。",
         "body": f"""## 如何阅读这个项目
 
 这个仓库把 Ropedia 公开的 Xperience-10M sample episode 变成一个可检查的具身智能任务实验室。请先看仪表盘和项目状态，再进入 20 个任务、结果矩阵和 Hugging Face 镜像。
@@ -293,6 +370,8 @@ LANGUAGE_GUIDES = {
 
 公式：2 个单 episode 方法 x 20 个任务 = 40；7 个 128-episode 方法 x 20 个任务 = 140；公开矩阵总计 180/180 scored records。
 
+方法块：Line 1 是 task-head baselines（Minimal、Neural MLP）。Line 2 分成 aligned baseline heads（metadata simple/NN、raw-feature simple/NN）、Qwen3-Omni series（Qwen3-Omni v6 LoRA）和 Cosmos3 series（Cosmos3-Super Reasoner、Cosmos3-Nano Future Window）。Qwen3 run v1-v6 是 LoRA/评估演进线，不是项目级三层版本；20-task matrix 使用 v6，v5 是 pinned prior release。Cosmos3-Super Forward-Dynamics LoRA 是单独发布的 adapter 权重/结果，不计入 20-task matrix method row。
+
 入口：[`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md)、[`two_evidence_lines.json`](docs/data/two_evidence_lines.json)、[`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)、[`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json)。
 
 ## 快速入口
@@ -311,7 +390,7 @@ LANGUAGE_GUIDES = {
 
 - 数据层：公开 sample episode 被切成 20-frame 窗口，并连接视频、音频、深度、pose/SLAM、mocap、IMU、calibration 和语言标注。
 - 任务层：20 个统一任务覆盖识别、预测、检索、重建、同步、长时预测、action-object 关系和 sensor bridge。
-- 结果层：单 episode minimal/NN 覆盖 20/20；128-episode metadata/raw/Qwen3/Cosmos 分开标注；当前公开矩阵为 180/180 scored records，其中 174 direct、6 compact proxy，proxy target 显式保留。
+- 结果层：单 episode minimal/NN 覆盖 20/20；128-episode metadata/raw、Qwen3-Omni v6 LoRA、Cosmos3-Super Reasoner、Cosmos3-Nano Future Window 分开标注；当前公开矩阵为 180/180 scored records，其中 174 direct、6 compact proxy，proxy target 显式保留。
 - 训练方向：spatial intelligence、human-video world model、vision-language-action 三条 pipeline 已经有任务映射和需要的证据清单。
 
 ## 公开边界
@@ -321,7 +400,7 @@ LANGUAGE_GUIDES = {
     },
     "es": {
         "title": "Ropedia Xperience-10M Task Suite",
-        "tagline": "Superficie pública multilingüe para Xperience-10M: datos de muestra, 20 tareas embodied-AI, baselines, diagnósticos Qwen3/Cosmos y direcciones de entrenamiento.",
+        "tagline": "Superficie pública multilingüe para Xperience-10M: datos de muestra, 20 tareas embodied-AI, baselines, diagnósticos Qwen3-Omni y Cosmos3, y direcciones de entrenamiento.",
         "body": f"""## Cómo Leer Este Proyecto
 
 Este repositorio convierte el episodio público de muestra de Xperience-10M en un laboratorio verificable de tareas para embodied AI. Empieza por el panel visual y el estado del proyecto; después entra en las tareas, matrices de resultados y espejos de Hugging Face.
@@ -339,6 +418,8 @@ Este repositorio convierte el episodio público de muestra de Xperience-10M en u
 
 Fórmula: 2 métodos de un episodio x 20 tareas = 40; 7 métodos de 128 episodios x 20 tareas = 140; matriz pública total = 180/180 registros con score.
 
+Bloques de métodos: la línea 1 contiene task-head baselines (Minimal, Neural MLP). La línea 2 separa aligned baseline heads (metadata simple/NN, raw-feature simple/NN), la serie Qwen3-Omni (Qwen3-Omni v6 LoRA) y la serie Cosmos3 (Cosmos3-Super Reasoner, Cosmos3-Nano Future Window). Qwen3 v1-v6 es una línea de evolución LoRA/evaluación, no las tres capas públicas del proyecto; la matriz de 20 tareas usa v6 y v5 queda como pinned prior release. Cosmos3-Super Forward-Dynamics LoRA se publica como adapter/pesos/resultados aparte y no cuenta como fila de método en la matriz de 20 tareas.
+
 Entradas: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Ruta Rápida
@@ -367,7 +448,7 @@ El proyecto publica solo artifacts derivados, métricas, figuras, tarjetas y res
     },
     "fr": {
         "title": "Ropedia Xperience-10M Task Suite",
-        "tagline": "Surface publique multilingue pour Xperience-10M : échantillon, 20 tâches embodied-AI, baselines, diagnostics Qwen3/Cosmos et pistes d'entraînement.",
+        "tagline": "Surface publique multilingue pour Xperience-10M : échantillon, 20 tâches embodied-AI, baselines, diagnostics Qwen3-Omni et Cosmos3, et pistes d'entraînement.",
         "body": f"""## Comment Lire Ce Projet
 
 Ce dépôt transforme l'épisode public d'exemple Xperience-10M en laboratoire de tâches vérifiable pour l'IA incarnée. Commencez par le tableau de bord et le statut du projet, puis ouvrez les contrats de tâches, les matrices de résultats et les miroirs Hugging Face.
@@ -385,6 +466,8 @@ Ce dépôt transforme l'épisode public d'exemple Xperience-10M en laboratoire d
 
 Formule : 2 méthodes sur 1 épisode x 20 tâches = 40; 7 méthodes sur 128 épisodes x 20 tâches = 140; matrice publique totale = 180/180 enregistrements scorés.
 
+Blocs de méthodes : la ligne 1 contient les task-head baselines (Minimal, Neural MLP). La ligne 2 sépare les aligned baseline heads (metadata simple/NN, raw-feature simple/NN), la série Qwen3-Omni (Qwen3-Omni v6 LoRA) et la série Cosmos3 (Cosmos3-Super Reasoner, Cosmos3-Nano Future Window). Qwen3 v1-v6 est une lignée LoRA/évaluation, pas les trois couches publiques du projet; la matrice 20 tâches utilise v6 et v5 reste le pinned prior release. Cosmos3-Super Forward-Dynamics LoRA est publié comme adapter/poids/résultats séparé et ne compte pas comme ligne de méthode dans la matrice 20 tâches.
+
 Entrées : [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Parcours Rapide
@@ -413,7 +496,7 @@ Le projet publie des artifacts dérivés, métriques, figures et cartes public-s
     },
     "de": {
         "title": "Ropedia Xperience-10M Task Suite",
-        "tagline": "Mehrsprachige öffentliche Forschungsoberfläche für Xperience-10M: Sample-Daten, 20 Embodied-AI-Aufgaben, Baselines, Qwen3/Cosmos-Diagnostik und Trainingsrichtungen.",
+        "tagline": "Mehrsprachige öffentliche Forschungsoberfläche für Xperience-10M: Sample-Daten, 20 Embodied-AI-Aufgaben, Baselines, Qwen3-Omni- und Cosmos3-Diagnostik und Trainingsrichtungen.",
         "body": f"""## So Liest Man Dieses Projekt
 
 Dieses Repository macht aus dem öffentlichen Xperience-10M-Sample eine prüfbare Aufgabenoberfläche für Embodied AI. Beginnen Sie mit Dashboard und Projektstatus, danach mit Aufgabenverträgen, Ergebnismatrizen und Hugging-Face-Spiegeln.
@@ -431,6 +514,8 @@ Dieses Repository macht aus dem öffentlichen Xperience-10M-Sample eine prüfbar
 
 Formel: 2 Single-Episode-Methoden x 20 Aufgaben = 40; 7 128-Episode-Methoden x 20 Aufgaben = 140; öffentliche Gesamtmatrix = 180/180 gescorte Einträge.
 
+Methodenblöcke: Linie 1 enthält task-head baselines (Minimal, Neural MLP). Linie 2 trennt aligned baseline heads (metadata simple/NN, raw-feature simple/NN), die Qwen3-Omni series (Qwen3-Omni v6 LoRA) und die Cosmos3 series (Cosmos3-Super Reasoner, Cosmos3-Nano Future Window). Qwen3 v1-v6 ist eine LoRA-/Evaluationslinie, nicht die drei öffentlichen Projektebenen; die 20-Task-Matrix nutzt v6 und v5 bleibt der pinned prior release. Cosmos3-Super Forward-Dynamics LoRA ist ein separat veröffentlichter Adapter/Gewichts-/Ergebnis-Artefakt und zählt nicht als Methodenreihe der 20-Task-Matrix.
+
 Einstieg: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Schneller Einstieg
@@ -459,7 +544,7 @@ Dieses Projekt veröffentlicht nur abgeleitete Artefakte, Metriken, Figuren, Kar
     },
     "ja": {
         "title": "Ropedia Xperience-10M Task Suite",
-        "tagline": "Xperience-10M の多言語公開研究面: サンプルデータ、20 個の embodied-AI タスク、ベースライン、Qwen3/Cosmos 診断、基盤モデル訓練方向。",
+        "tagline": "Xperience-10M の多言語公開研究面: サンプルデータ、20 個の embodied-AI タスク、ベースライン、Qwen3-Omni と Cosmos3 診断、基盤モデル訓練方向。",
         "body": f"""## このプロジェクトの読み方
 
 このリポジトリは、公開 Xperience-10M サンプル episode を、検証可能な embodied AI タスク実験面に変換します。まずダッシュボードとプロジェクト状態を見て、その後 20 タスク、結果行列、Hugging Face ミラーを確認してください。
@@ -477,6 +562,8 @@ Dieses Projekt veröffentlicht nur abgeleitete Artefakte, Metriken, Figuren, Kar
 
 式: 1-episode methods 2 個 x 20 tasks = 40、128-episode methods 7 個 x 20 tasks = 140、公開 matrix 合計は 180/180 scored records。
 
+Method blocks: Line 1 は task-head baselines（Minimal、Neural MLP）。Line 2 は aligned baseline heads（metadata simple/NN、raw-feature simple/NN）、Qwen3-Omni series（Qwen3-Omni v6 LoRA）、Cosmos3 series（Cosmos3-Super Reasoner、Cosmos3-Nano Future Window）に分かれます。Qwen3 v1-v6 は LoRA/eval の lineage で、project-level の 3 version とは別です。20-task matrix は v6 を使い、v5 は pinned prior release です。Cosmos3-Super Forward-Dynamics LoRA は別の adapter/weights/results artifact として公開され、20-task matrix の method row には含めません。
+
 入口: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md)、[`two_evidence_lines.json`](docs/data/two_evidence_lines.json)、[`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)、[`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json)。
 
 ## クイックルート
@@ -505,7 +592,7 @@ Dieses Projekt veröffentlicht nur abgeleitete Artefakte, Metriken, Figuren, Kar
     },
     "ko": {
         "title": "Ropedia Xperience-10M Task Suite",
-        "tagline": "Xperience-10M을 위한 다국어 공개 연구 표면: 샘플 데이터, 20개 embodied-AI 과제, 베이스라인, Qwen3/Cosmos 진단, foundation 모델 학습 방향.",
+        "tagline": "Xperience-10M을 위한 다국어 공개 연구 표면: 샘플 데이터, 20개 embodied-AI 과제, 베이스라인, Qwen3-Omni 및 Cosmos3 진단, foundation 모델 학습 방향.",
         "body": f"""## 이 프로젝트를 읽는 방법
 
 이 저장소는 공개 Xperience-10M sample episode를 검증 가능한 embodied AI 과제 실험 표면으로 정리합니다. 먼저 대시보드와 프로젝트 상태를 보고, 이후 20개 과제, 결과 행렬, Hugging Face 미러를 확인하세요.
@@ -523,6 +610,8 @@ Dieses Projekt veröffentlicht nur abgeleitete Artefakte, Metriken, Figuren, Kar
 
 공식: single-episode 방법 2개 x 20 tasks = 40; 128-episode 방법 7개 x 20 tasks = 140; 전체 공개 matrix = 180/180 scored records.
 
+방법 블록: Line 1은 task-head baselines(Minimal, Neural MLP)입니다. Line 2는 aligned baseline heads(metadata simple/NN, raw-feature simple/NN), Qwen3-Omni series(Qwen3-Omni v6 LoRA), Cosmos3 series(Cosmos3-Super Reasoner, Cosmos3-Nano Future Window)로 분리됩니다. Qwen3 v1-v6은 LoRA/eval lineage이며 project-level 3개 버전과 다릅니다. 20-task matrix는 v6을 사용하고 v5는 pinned prior release입니다. Cosmos3-Super Forward-Dynamics LoRA는 별도의 adapter/weights/results artifact로 공개되며 20-task matrix method row에는 포함되지 않습니다.
+
 입구: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## 빠른 경로
@@ -551,7 +640,7 @@ Dieses Projekt veröffentlicht nur abgeleitete Artefakte, Metriken, Figuren, Kar
     },
     "pt": {
         "title": "Ropedia Xperience-10M Task Suite",
-        "tagline": "Superfície pública multilíngue para Xperience-10M: dados de amostra, 20 tarefas embodied-AI, baselines, diagnósticos Qwen3/Cosmos e direções de treino.",
+        "tagline": "Superfície pública multilíngue para Xperience-10M: dados de amostra, 20 tarefas embodied-AI, baselines, diagnósticos Qwen3-Omni e Cosmos3 e direções de treino.",
         "body": f"""## Como Ler Este Projeto
 
 Este repositório transforma o episódio público de amostra do Xperience-10M em um laboratório verificável de tarefas para embodied AI. Comece pelo painel visual e pelo status do projeto; depois abra os contratos de tarefas, matrizes de resultados e espelhos no Hugging Face.
@@ -569,6 +658,8 @@ Este repositório transforma o episódio público de amostra do Xperience-10M em
 
 Fórmula: 2 métodos de um episódio x 20 tarefas = 40; 7 métodos de 128 episódios x 20 tarefas = 140; matriz pública total = 180/180 registros com score.
 
+Blocos de métodos: a linha 1 contém task-head baselines (Minimal, Neural MLP). A linha 2 separa aligned baseline heads (metadata simple/NN, raw-feature simple/NN), a série Qwen3-Omni (Qwen3-Omni v6 LoRA) e a série Cosmos3 (Cosmos3-Super Reasoner, Cosmos3-Nano Future Window). Qwen3 v1-v6 é uma linhagem LoRA/eval, não as três camadas públicas do projeto; a matriz de 20 tarefas usa v6 e v5 fica como pinned prior release. Cosmos3-Super Forward-Dynamics LoRA é publicado como adapter/pesos/resultados separado e não conta como linha de método na matriz de 20 tarefas.
+
 Entradas: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Rota Rápida