Clarify RoboValue training and small-scale evaluation data organization

Rename the training root to training-data while preserving native LeRobot structure, maintain both diagnostic test sets, and document the paper/task annotation audit.

README.md

@@ -1,5 +1,5 @@
 ---
-pretty_name: RoboValue Training and Evaluation Data
+pretty_name: RoboValue Training and Small-Scale Evaluation Data
 language:
 - en
 - zh
@@ -29,7 +29,7 @@ configs:
 
 <div align="center">
   <img src="https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/resolve/main/assets/robovalue-logo.png" alt="RoboValue" width="420" />
-  <h1>RoboValue Training and Evaluation Data</h1>
+  <h1>RoboValue Training and Small-Scale Evaluation Data</h1>
   <p><strong>Training Demonstrations · Small-Scale Real-World &amp; Simulation Public Test Sets</strong></p>
   <p>
     <a href="https://arxiv.org/abs/2610.26663"><img src="https://img.shields.io/badge/arXiv-Paper-red?logo=arxiv" alt="RoboValue paper on arXiv" /></a>
@@ -71,7 +71,7 @@ Training demonstrations and public test trajectories have separate directories a
 
 | Collection | Location | Scale | Purpose |
 | --- | --- | --- | --- |
-| Simulation / real-world training | `data/<domain>/{full-shot,one-shot}` | Four training subsets listed above | Expert demonstrations for training or reference conditioning |
+| Simulation / real-world training | `training-data/<domain>/{full-shot,one-shot}` | Four training subsets listed above | Expert demonstrations for training or reference conditioning |
 | [Real-world public test set](evaluation/real-world/test-30/README.md) | `evaluation/real-world/test-30` | **4 tasks / 30 trajectories / 27,498 time steps / 90 videos** | Small-scale In-Domain diagnostic evaluation |
 | [Simulation public test set](evaluation/simulation/test-30/README.md) | `evaluation/simulation/test-30` | **4 tasks / 30 trajectories / 17,149 time steps / 90 videos** | Small-scale In-Domain diagnostic evaluation |
 
@@ -130,7 +130,7 @@ The simulation dataset covers the following 15 tasks.
 | 13 | Swap Blocks |
 | 14 | Sweep Blocks |
 
-[Full-Shot task metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/full-shot/meta/tasks.parquet) · [One-Shot task metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/meta/tasks.parquet)
+[Full-Shot task metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/full-shot/meta/tasks.parquet) · [One-Shot task metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/meta/tasks.parquet)
 
 </details>
 
@@ -146,7 +146,7 @@ The first seven entries are left-side fields; the last seven are right-side fiel
 | 0–6 | `left_joint_0` … `left_joint_6` |
 | 7–13 | `right_joint_0` … `right_joint_6` |
 
-[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/meta/info.json)
+[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/meta/info.json)
 
 </details>
 
@@ -162,7 +162,7 @@ The first seven entries are left-side fields; the last seven are right-side fiel
 | 0–6 | `left_joint_0` … `left_joint_6` |
 | 7–13 | `right_joint_0` … `right_joint_6` |
 
-[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/meta/info.json)
+[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/meta/info.json)
 
 </details>
 
@@ -177,7 +177,7 @@ Loaded images use **CHW (channels, height, width)** order.
 | `observation.images.cam_left_wrist` | `[3, 480, 640]` |
 | `observation.images.cam_right_wrist` | `[3, 480, 640]` |
 
-[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/meta/info.json)
+[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/meta/info.json)
 
 </details>
 
@@ -189,7 +189,7 @@ Loaded images use **CHW (channels, height, width)** order.
 | ---: | --- | ---: | ---: | --- |
 | **789,612** | **4,500 · AV1 / H.264** | **≈45.47 GB** | ≈8.77 hours | `train: 0:1500` |
 
-[**Browse files →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/data/simulation/full-shot) · [Download and read](#download-and-reading)
+[**Browse files →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/training-data/simulation/full-shot) · [Download and read](#download-and-reading)
 
 ### ◉ 2.3 One-Shot
 
@@ -199,9 +199,9 @@ Loaded images use **CHW (channels, height, width)** order.
 | ---: | --- | ---: | ---: | --- |
 | **8,080** | **45 · AV1** | **≈0.50 GB** | ≈5.39 minutes | `train: 0:15` |
 
-[**Browse files →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/data/simulation/one-shot) · [Task–episode–row mapping](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/provenance/episode_mapping.json) · [Download and read](#download-and-reading)
+[**Browse files →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/training-data/simulation/one-shot) · [Task–episode–row mapping](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/provenance/episode_mapping.json) · [Download and read](#download-and-reading)
 
-**Subtask annotations:** [58 paper-defined segments](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/annotations/subtasks/README.md) label all **8,080 frames**, with one subtask per frame. These annotations accompany the training demonstrations and are separate from benchmark test-set labels. [`dataset_labeler`-compatible JSON](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145/data/simulation/one-shot/annotations/subtasks/dataset_labeler) uses the same subtasks and boundaries as the frame labels.
+**Subtask annotations:** [58 paper-defined segments](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/annotations/subtasks/README.md) label all **8,080 frames**, with one subtask per frame. These annotations accompany the training demonstrations and are separate from benchmark test-set labels. [`dataset_labeler`-compatible JSON](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/MIGRATED_TRAINING_REVISION/training-data/simulation/one-shot/annotations/subtasks/dataset_labeler) uses the same subtasks and boundaries as the frame labels.
 
 ## 🟧 3. Real-World Training <a name="real-world"></a>
 
@@ -249,7 +249,7 @@ The real-world dataset covers the following 20 tasks.
 | 18 | Arrange Flowers and Reed Diffuser |
 | 19 | Prepare Breakfast |
 
-[Full-Shot task metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/full-shot/meta/tasks.parquet) · [One-Shot task metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/one-shot/meta/tasks.parquet)
+[Full-Shot task metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/full-shot/meta/tasks.parquet) · [One-Shot task metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/one-shot/meta/tasks.parquet)
 
 </details>
 
@@ -274,7 +274,7 @@ The real-world dataset covers the following 20 tasks.
 
 The table lists key fields; the full 290-dimensional definition is in the metadata below.
 
-[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/one-shot/meta/info.json)
+[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/one-shot/meta/info.json)
 
 </details>
 
@@ -299,7 +299,7 @@ The table lists key fields; the full 290-dimensional definition is in the metada
 
 The last two reference orientations are distinct from the end-effector target orientations. Full field definitions are in the metadata below.
 
-[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/one-shot/meta/info.json)
+[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/one-shot/meta/info.json)
 
 </details>
 
@@ -314,7 +314,7 @@ Loaded images use **CHW (channels, height, width)** order.
 | `observation.images.cam_left_wrist` | `[3, 528, 640]` |
 | `observation.images.cam_right_wrist` | `[3, 528, 640]` |
 
-[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/one-shot/meta/info.json)
+[Full-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/full-shot/meta/info.json) · [One-Shot metadata](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/one-shot/meta/info.json)
 
 </details>
 
@@ -326,7 +326,7 @@ Loaded images use **CHW (channels, height, width)** order.
 | ---: | --- | ---: | ---: | --- |
 | **1,534,321** | **6,000 · HEVC** | **≈23.13 GB** | ≈14.21 hours | `train: 0:2000` |
 
-[**Browse files →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/data/real-world/full-shot) · [Download and read](#download-and-reading)
+[**Browse files →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/training-data/real-world/full-shot) · [Download and read](#download-and-reading)
 
 ### ◉ 3.3 One-Shot
 
@@ -338,7 +338,7 @@ For 19 tasks, the selected trajectory has the **smallest original `episode_id` a
 | ---: | --- | ---: | ---: | --- |
 | **16,362** | **60 · HEVC** | **≈0.22 GB** | ≈9.09 minutes | `train: 0:20` |
 
-[**Browse files →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/data/real-world/one-shot) · [Task–episode–row mapping](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/one-shot/provenance/episode_mapping.json) · [Download and read](#download-and-reading)
+[**Browse files →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/training-data/real-world/one-shot) · [Task–episode–row mapping](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/one-shot/provenance/episode_mapping.json) · [Download and read](#download-and-reading)
 
 ## 🗂️ 4. Repository Layout <a name="repository-layout"></a>
 
@@ -346,7 +346,7 @@ For 19 tasks, the selected trajectory has the **smallest original `episode_id` a
 README.md                         English dataset card
 README_zh.md                      Chinese dataset card
 subset_catalog.json               Subset index
-data/
+training-data/
 ├── simulation/
 │   ├── full-shot/                1,500 episodes · 15 tasks
 │   └── one-shot/                 15 episodes · 1 per task
@@ -396,10 +396,10 @@ Select one `prefix` to download only that subset. Sizes use decimal GB.
 
 | 🗂️ Subset | ↓ `prefix` | ▦ Episodes / time steps | ▣ Size |
 | --- | --- | ---: | ---: |
-| 🟦 **Simulation Full-Shot** | `data/simulation/full-shot` | 1,500 / 789,612 | ≈45.47 GB |
-| 🟦 **Simulation One-Shot** | `data/simulation/one-shot` | 15 / 8,080 | ≈0.50 GB |
-| 🟧 **Real-World Full-Shot** | `data/real-world/full-shot` | 2,000 / 1,534,321 | ≈23.13 GB |
-| 🟧 **Real-World One-Shot** | `data/real-world/one-shot` | 20 / 16,362 | ≈0.22 GB |
+| 🟦 **Simulation Full-Shot** | `training-data/simulation/full-shot` | 1,500 / 789,612 | ≈45.47 GB |
+| 🟦 **Simulation One-Shot** | `training-data/simulation/one-shot` | 15 / 8,080 | ≈0.50 GB |
+| 🟧 **Real-World Full-Shot** | `training-data/real-world/full-shot` | 2,000 / 1,534,321 | ≈23.13 GB |
+| 🟧 **Real-World One-Shot** | `training-data/real-world/one-shot` | 20 / 16,362 | ≈0.22 GB |
 | **Real-World Public Test** | `evaluation/real-world/test-30` | 30 / 27,498 | ≈0.38 GB |
 | **Simulation Public Test** | `evaluation/simulation/test-30` | 30 / 17,149 | ≈0.595 GB |
 
@@ -421,8 +421,8 @@ from huggingface_hub import snapshot_download
 from lerobot.datasets.lerobot_dataset import LeRobotDataset
 
 repo_id = "wzlllong/value-model-benchmark-training-data"
-prefix = "data/simulation/one-shot"
-revision = "7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145"
+prefix = "training-data/simulation/one-shot"
+revision = "MIGRATED_TRAINING_REVISION"
 local_dir = Path(os.environ.get("ROBOVALUE_LOCAL_DIR", "./robovalue-data"))
 
 snapshot = snapshot_download(
@@ -466,11 +466,11 @@ After the Simulation One-Shot example above, join the frame labels on `episode_i
 ```python
 import pyarrow.parquet as pq
 
-annotation_prefix = "data/simulation/one-shot/annotations/subtasks"
+annotation_prefix = "training-data/simulation/one-shot/annotations/subtasks"
 annotation_snapshot = snapshot_download(
     repo_id=repo_id,
     repo_type="dataset",
-    revision="7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145",
+    revision="MIGRATED_TRAINING_REVISION",
     allow_patterns=[f"{annotation_prefix}/**"],
     local_dir=local_dir,
 )

README_zh.md

@@ -1,6 +1,6 @@
 <div align="center">
   <img src="https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/resolve/main/assets/robovalue-logo.png" alt="RoboValue" width="420" />
-  <h1>RoboValue 训练与公开测试数据</h1>
+  <h1>RoboValue 训练与小规模评测数据</h1>
   <p><strong>训练示例 · 小规模真机与仿真公开测试集</strong></p>
   <p>
     <a href="https://arxiv.org/abs/2610.26663"><img src="https://img.shields.io/badge/arXiv-Paper-red?logo=arxiv" alt="RoboValue paper on arXiv" /></a>
@@ -42,7 +42,7 @@ RoboValue 提供面向**机器人价值模型**的专家示例，覆盖 **15 个
 
 | 数据集合 | 目录 | 规模 | 用途 |
 | --- | --- | --- | --- |
-| 仿真／真机训练数据 | `data/<domain>/{full-shot,one-shot}` | 上述四个训练子集 | 用于训练或示例参考输入的专家示范 |
+| 仿真／真机训练数据 | `training-data/<domain>/{full-shot,one-shot}` | 上述四个训练子集 | 用于训练或示例参考输入的专家示范 |
 | [真机公开测试集](evaluation/real-world/test-30/README_zh.md) | `evaluation/real-world/test-30` | **4任务／30轨迹／27,498时间步／90视频** | 小规模 In-Domain 诊断评测 |
 | [仿真公开测试集](evaluation/simulation/test-30/README_zh.md) | `evaluation/simulation/test-30` | **4任务／30轨迹／17,149时间步／90视频** | 小规模 In-Domain 诊断评测 |
 
@@ -101,7 +101,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 | 13 | 交换积木位置<br><sub>Swap Blocks</sub> |
 | 14 | 清扫积木<br><sub>Sweep Blocks</sub> |
 
-[Full-Shot 任务元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/full-shot/meta/tasks.parquet) · [One-Shot 任务元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/meta/tasks.parquet)
+[Full-Shot 任务元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/full-shot/meta/tasks.parquet) · [One-Shot 任务元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/meta/tasks.parquet)
 
 </details>
 
@@ -117,7 +117,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 | 0–6 | `left_joint_0` … `left_joint_6` |
 | 7–13 | `right_joint_0` … `right_joint_6` |
 
-[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/meta/info.json)
+[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/meta/info.json)
 
 </details>
 
@@ -133,7 +133,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 | 0–6 | `left_joint_0` … `left_joint_6` |
 | 7–13 | `right_joint_0` … `right_joint_6` |
 
-[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/meta/info.json)
+[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/meta/info.json)
 
 </details>
 
@@ -148,7 +148,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 | `observation.images.cam_left_wrist` | `[3, 480, 640]` |
 | `observation.images.cam_right_wrist` | `[3, 480, 640]` |
 
-[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/meta/info.json)
+[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/meta/info.json)
 
 </details>
 
@@ -160,7 +160,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 | ---: | --- | ---: | ---: | --- |
 | **789,612** | **4,500 个 · AV1 / H.264** | **≈45.47 GB** | ≈8.77 小时 | `train: 0:1500` |
 
-[**浏览文件 →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/data/simulation/full-shot) · [下载与读取](#download-and-reading)
+[**浏览文件 →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/training-data/simulation/full-shot) · [下载与读取](#download-and-reading)
 
 ### ◉ 2.3 One-Shot
 
@@ -170,9 +170,9 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 | ---: | --- | ---: | ---: | --- |
 | **8,080** | **45 个 · AV1** | **≈0.50 GB** | ≈5.39 分钟 | `train: 0:15` |
 
-[**浏览文件 →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/data/simulation/one-shot) · [任务—轨迹—行范围映射](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/provenance/episode_mapping.json) · [下载与读取](#download-and-reading)
+[**浏览文件 →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/training-data/simulation/one-shot) · [任务—轨迹—行范围映射](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/provenance/episode_mapping.json) · [下载与读取](#download-and-reading)
 
-**子任务标注：**[58 个论文子任务区间](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/simulation/one-shot/annotations/subtasks/README.md)覆盖全部 **8,080 帧**，每帧对应一个子任务。标注用于这些训练示例，与评测集标签分开。 另提供 [`dataset_labeler` 兼容 JSON](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145/data/simulation/one-shot/annotations/subtasks/dataset_labeler)，与逐帧标签使用相同的子任务和边界。
+**子任务标注：**[58 个论文子任务区间](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/simulation/one-shot/annotations/subtasks/README.md)覆盖全部 **8,080 帧**，每帧对应一个子任务。标注用于这些训练示例，与评测集标签分开。 另提供 [`dataset_labeler` 兼容 JSON](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/MIGRATED_TRAINING_REVISION/training-data/simulation/one-shot/annotations/subtasks/dataset_labeler)，与逐帧标签使用相同的子任务和边界。
 
 ## 🟧 3. 真实世界训练数据 <a name="real-world"></a>
 
@@ -220,7 +220,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 | 18 | 插花与摆放藤条香薰<br><sub>Arrange Flowers and Reed Diffuser</sub> |
 | 19 | 准备早餐<br><sub>Prepare Breakfast</sub> |
 
-[Full-Shot 任务元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/full-shot/meta/tasks.parquet) · [One-Shot 任务元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/one-shot/meta/tasks.parquet)
+[Full-Shot 任务元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/full-shot/meta/tasks.parquet) · [One-Shot 任务元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/one-shot/meta/tasks.parquet)
 
 </details>
 
@@ -245,7 +245,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 
 上表列出主要字段；完整 290 维定义见以下元数据。
 
-[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/one-shot/meta/info.json)
+[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/one-shot/meta/info.json)
 
 </details>
 
@@ -270,7 +270,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 
 最后两项参考朝向不同于末端目标朝向。完整字段定义见以下元数据。
 
-[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/one-shot/meta/info.json)
+[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/one-shot/meta/info.json)
 
 </details>
 
@@ -285,7 +285,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 | `observation.images.cam_left_wrist` | `[3, 528, 640]` |
 | `observation.images.cam_right_wrist` | `[3, 528, 640]` |
 
-[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/one-shot/meta/info.json)
+[Full-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/full-shot/meta/info.json) · [One-Shot 元数据](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/one-shot/meta/info.json)
 
 </details>
 
@@ -297,7 +297,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 | ---: | --- | ---: | ---: | --- |
 | **1,534,321** | **6,000 个 · HEVC** | **≈23.13 GB** | ≈14.21 小时 | `train: 0:2000` |
 
-[**浏览文件 →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/data/real-world/full-shot) · [下载与读取](#download-and-reading)
+[**浏览文件 →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/training-data/real-world/full-shot) · [下载与读取](#download-and-reading)
 
 ### ◉ 3.3 One-Shot
 
@@ -309,7 +309,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 | ---: | --- | ---: | ---: | --- |
 | **16,362** | **60 个 · HEVC** | **≈0.22 GB** | ≈9.09 分钟 | `train: 0:20` |
 
-[**浏览文件 →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/data/real-world/one-shot) · [任务—轨迹—行范围映射](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/data/real-world/one-shot/provenance/episode_mapping.json) · [下载与读取](#download-and-reading)
+[**浏览文件 →**](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/tree/main/training-data/real-world/one-shot) · [任务—轨迹—行范围映射](https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/blob/main/training-data/real-world/one-shot/provenance/episode_mapping.json) · [下载与读取](#download-and-reading)
 
 ## 🗂️ 4. 仓库目录 <a name="repository-layout"></a>
 
@@ -317,7 +317,7 @@ Full-Shot 与 One-Shot 中，每条 **episode** 都是一条完整的任务示
 README.md                         英文数据集卡片
 README_zh.md                      中文数据集卡片
 subset_catalog.json               子集索引
-data/
+training-data/
 ├── simulation/
 │   ├── full-shot/                1,500 条 · 15 个任务
 │   └── one-shot/                 15 条 · 每任务 1 条
@@ -367,10 +367,10 @@ evaluation/
 
 | 🗂️ 子集 | ↓ `prefix` | ▦ 轨迹 / 时间步 | ▣ 大小 |
 | --- | --- | ---: | ---: |
-| 🟦 **仿真 Full-Shot** | `data/simulation/full-shot` | 1,500 / 789,612 | ≈45.47 GB |
-| 🟦 **仿真 One-Shot** | `data/simulation/one-shot` | 15 / 8,080 | ≈0.50 GB |
-| 🟧 **真机 Full-Shot** | `data/real-world/full-shot` | 2,000 / 1,534,321 | ≈23.13 GB |
-| 🟧 **真机 One-Shot** | `data/real-world/one-shot` | 20 / 16,362 | ≈0.22 GB |
+| 🟦 **仿真 Full-Shot** | `training-data/simulation/full-shot` | 1,500 / 789,612 | ≈45.47 GB |
+| 🟦 **仿真 One-Shot** | `training-data/simulation/one-shot` | 15 / 8,080 | ≈0.50 GB |
+| 🟧 **真机 Full-Shot** | `training-data/real-world/full-shot` | 2,000 / 1,534,321 | ≈23.13 GB |
+| 🟧 **真机 One-Shot** | `training-data/real-world/one-shot` | 20 / 16,362 | ≈0.22 GB |
 | **真机公开测试集** | `evaluation/real-world/test-30` | 30 / 27,498 | ≈0.38 GB |
 | **仿真公开测试集** | `evaluation/simulation/test-30` | 30 / 17,149 | ≈0.595 GB |
 
@@ -392,8 +392,8 @@ from huggingface_hub import snapshot_download
 from lerobot.datasets.lerobot_dataset import LeRobotDataset
 
 repo_id = "wzlllong/value-model-benchmark-training-data"
-prefix = "data/simulation/one-shot"
-revision = "7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145"
+prefix = "training-data/simulation/one-shot"
+revision = "MIGRATED_TRAINING_REVISION"
 local_dir = Path(os.environ.get("ROBOVALUE_LOCAL_DIR", "./robovalue-data"))
 
 snapshot = snapshot_download(
@@ -437,11 +437,11 @@ observation.images.cam_right_wrist (3, 480, 640)
 ```python
 import pyarrow.parquet as pq
 
-annotation_prefix = "data/simulation/one-shot/annotations/subtasks"
+annotation_prefix = "training-data/simulation/one-shot/annotations/subtasks"
 annotation_snapshot = snapshot_download(
     repo_id=repo_id,
     repo_type="dataset",
-    revision="7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145",
+    revision="MIGRATED_TRAINING_REVISION",
     allow_patterns=[f"{annotation_prefix}/**"],
     local_dir=local_dir,
 )

subset_catalog.json

@@ -39,7 +39,7 @@
       "tasks": 15,
       "episodes_per_task": 100,
       "episodes": 1500,
-      "path_in_repo": "data/simulation/full-shot",
+      "path_in_repo": "training-data/simulation/full-shot",
       "name_en": "Simulation Full-Shot Training Data",
       "name_zh": "仿真 Full-Shot 训练集",
       "format": "LeRobot v3.0",
@@ -115,7 +115,8 @@
         "收纳笔记本电脑与耳机",
         "交换积木位置",
         "清扫积木"
-      ]
+      ],
+      "role": "training"
     },
     {
       "subset_id": "simulation-one-shot-data",
@@ -125,7 +126,7 @@
       "tasks": 15,
       "episodes_per_task": 1,
       "episodes": 15,
-      "path_in_repo": "data/simulation/one-shot",
+      "path_in_repo": "training-data/simulation/one-shot",
       "name_en": "Simulation One-Shot Training Data",
       "name_zh": "仿真 One-Shot 训练集",
       "format": "LeRobot v3.0",
@@ -141,7 +142,7 @@
       "video_codecs": [
         "av1"
       ],
-      "episode_mapping": "data/simulation/one-shot/provenance/episode_mapping.json",
+      "episode_mapping": "training-data/simulation/one-shot/provenance/episode_mapping.json",
       "videos": 45,
       "platform": "ARX",
       "source_description_en": "Based on open-source RoboDojo data reviewed by our team, with selected demonstrations recorded again.",
@@ -199,8 +200,8 @@
       ],
       "annotations": {
         "subtasks": {
-          "path_in_repo": "data/simulation/one-shot/annotations/subtasks",
-          "revision": "7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145",
+          "path_in_repo": "training-data/simulation/one-shot/annotations/subtasks",
+          "revision": "MIGRATED_TRAINING_REVISION",
           "status": "user_confirmed_release",
           "target": "active_semantic_subtask",
           "scope": "training_demonstrations",
@@ -216,35 +217,35 @@
             "frame_index"
           ],
           "global_index_matches": "index",
-          "frame_labels": "data/simulation/one-shot/annotations/subtasks/frame_labels.parquet",
-          "taxonomy": "data/simulation/one-shot/annotations/subtasks/taxonomy.json",
+          "frame_labels": "training-data/simulation/one-shot/annotations/subtasks/frame_labels.parquet",
+          "taxonomy": "training-data/simulation/one-shot/annotations/subtasks/taxonomy.json",
           "size_bytes": 146350,
           "payload_size_bytes": 146350,
-          "documentation": "data/simulation/one-shot/annotations/subtasks/README.md",
+          "documentation": "training-data/simulation/one-shot/annotations/subtasks/README.md",
           "interval_convention": "[start_frame,end_frame)",
           "boundary_mask": "boundary_uncertain",
           "payload_files": 24,
           "dataset_labeler": {
-            "path_in_repo": "data/simulation/one-shot/annotations/subtasks/dataset_labeler",
+            "path_in_repo": "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler",
             "format": "dataset_labeler_sia_cspc",
             "task_files": [
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/arrange_largest_number_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/fill_pen_holder_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/fold_clothes_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/hang_mugs_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/insert_tubes_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/make_toast_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/organize_table_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/pack_objects_into_box_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/play_stacking_toy_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/press_by_number_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/put_bottles_into_dustbin_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/stack_blocks_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/store_laptop_and_headphones_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/swap_blocks_sia_cspc_annotations.json",
-              "data/simulation/one-shot/annotations/subtasks/dataset_labeler/sweep_blocks_sia_cspc_annotations.json"
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/arrange_largest_number_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/fill_pen_holder_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/fold_clothes_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/hang_mugs_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/insert_tubes_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/make_toast_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/organize_table_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/pack_objects_into_box_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/play_stacking_toy_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/press_by_number_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/put_bottles_into_dustbin_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/stack_blocks_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/store_laptop_and_headphones_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/swap_blocks_sia_cspc_annotations.json",
+              "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/sweep_blocks_sia_cspc_annotations.json"
             ],
-            "exceptional_intervals": "data/simulation/one-shot/annotations/subtasks/dataset_labeler/exceptional_intervals.json",
+            "exceptional_intervals": "training-data/simulation/one-shot/annotations/subtasks/dataset_labeler/exceptional_intervals.json",
             "transfer_export_records": 15,
             "transfer_export_boundary_points": 73,
             "record_fields": [
@@ -271,9 +272,11 @@
             "metric": "SIA+CSPC",
             "group": "one-shot",
             "gap": 20
-          }
+          },
+          "source_revision": "7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145"
         }
-      }
+      },
+      "role": "training"
     },
     {
       "subset_id": "real-world-full-shot-data",
@@ -282,7 +285,7 @@
       "name_en": "Real-World Full-Shot Training Data",
       "name_zh": "真机 Full-Shot 训练集",
       "availability": "available",
-      "path_in_repo": "data/real-world/full-shot",
+      "path_in_repo": "training-data/real-world/full-shot",
       "format": "LeRobot v3.0",
       "robot_type": "G2A",
       "tasks": 20,
@@ -348,7 +351,8 @@
         "准备早餐"
       ],
       "size_bytes": 23125415964,
-      "duration_seconds": 51144.03333333333
+      "duration_seconds": 51144.03333333333,
+      "role": "training"
     },
     {
       "subset_id": "real-world-one-shot-data",
@@ -358,7 +362,7 @@
       "tasks": 20,
       "episodes_per_task": 1,
       "episodes": 20,
-      "path_in_repo": "data/real-world/one-shot",
+      "path_in_repo": "training-data/real-world/one-shot",
       "name_en": "Real-World One-Shot Training Data",
       "name_zh": "真机 One-Shot 训练集",
       "format": "LeRobot v3.0",
@@ -374,7 +378,7 @@
       "video_codecs": [
         "hevc"
       ],
-      "episode_mapping": "data/real-world/one-shot/provenance/episode_mapping.json",
+      "episode_mapping": "training-data/real-world/one-shot/provenance/episode_mapping.json",
       "source_episode_selection": "minimum original episode_id among the 100 source episodes for 19 tasks; tea uses the minimum original episode_id from the 27-episode tea refresh batch",
       "videos": 60,
       "platform": "AgiBot Genie02",
@@ -434,7 +438,8 @@
           "source_episode_id": 52375079,
           "selection": "minimum original episode_id in the 27-episode tea refresh batch"
         }
-      ]
+      ],
+      "role": "training"
     },
     {
       "subset_id": "real-world-test-30",
@@ -606,10 +611,11 @@
     }
   ],
   "planned_subsets": [],
-  "data_revision": "7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145",
+  "data_revision": "MIGRATED_TRAINING_REVISION",
   "publication_authorization": "All data were authorized before public release.",
-  "pretty_name": "RoboValue Training and Evaluation Data",
-  "training_data_revision": "7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145",
-  "revision_note": "data_revision and training_data_revision refer to existing training payloads; use the commit containing both public test subsets for evaluation/real-world/test-30 and evaluation/simulation/test-30.",
-  "evaluation_data_revision": "578593ef28ee7a2d861ebf38162c928291b0d4a9"
+  "pretty_name": "RoboValue Training and Small-Scale Evaluation Data",
+  "training_data_revision": "MIGRATED_TRAINING_REVISION",
+  "revision_note": "training_data_revision identifies the unchanged training payloads under training-data/. source_training_data_revision records the original release under data/. evaluation_data_revision identifies the separate public test payloads.",
+  "evaluation_data_revision": "578593ef28ee7a2d861ebf38162c928291b0d4a9",
+  "source_training_data_revision": "7fd21cb2519b4d59cbe9fe8b23cfdf477e3ad145"
 }