Add dataset card

README.md

@@ -1,3 +1,102 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+  - en
+tags:
+  - robotics
+  - vision-language-action
+  - neuro-symbolic
+  - manipulation
+  - primitive-annotations
+task_categories:
+  - robotics
+size_categories:
+  - 1K<n<10K
+---
+
+# NS-VLA Dataset: Primitive-Annotated Robotic Manipulation Data
+
+<div align="center">
+
+[![arXiv](https://img.shields.io/badge/arXiv-XXXX.XXXXX-b31b1b.svg)](https://arxiv.org/abs/XXXX.XXXXX)
+[![GitHub](https://img.shields.io/badge/GitHub-Code-black)](https://github.com/Zuzuzzy/NS-VLA)
+[![Project Page](https://img.shields.io/badge/Project-Page-blue)](https://zuzuzzy.github.io/NS-VLA/)
+
+</div>
+
+## Dataset Description
+
+This dataset provides **primitive annotations** for robotic manipulation demonstrations used to train and evaluate the NS-VLA framework. Each demonstration trajectory is segmented and labeled with structured manipulation primitives.
+
+## Primitive Vocabulary
+
+| Primitive | Description | Frequency |
+|:---|:---|:---:|
+| `pick` | Grasp a target object | 44.4% |
+| `place_in` | Place object inside a container | 25.0% |
+| `place_on` | Place object on a surface | 16.7% |
+| `close` | Close an appliance (e.g., microwave) | 5.6% |
+| `place_rel` | Place relative to another object | — |
+| `turn_on` | Activate an appliance (e.g., stove) | — |
+| `open` | Open an appliance door | — |
+
+## Dataset Structure
+
+```
+NS-VLA-Dataset/
+├── libero/
+│   ├── spatial/          # LIBERO-Spatial task annotations
+│   ├── object/           # LIBERO-Object task annotations
+│   ├── goal/             # LIBERO-Goal task annotations
+│   └── long/             # LIBERO-Long task annotations
+├── calvin/
+│   └── ABC_D/            # CALVIN ABC→D split annotations
+└── metadata.json         # Dataset statistics and splits
+```
+
+## Annotation Format
+
+Each annotation file is a JSON with the following structure:
+
+```json
+{
+  "task_id": "libero_spatial_01",
+  "instruction": "put the white mug on the left plate",
+  "primitives": [
+    {"op": "pick", "args": {"object": "white_mug"}, "start": 0, "end": 45},
+    {"op": "place_on", "args": {"object": "white_mug", "support": "left_plate"}, "start": 46, "end": 102}
+  ],
+  "total_steps": 102
+}
+```
+
+## Usage
+
+> ⚠️ **Note**: Dataset files will be released upon paper acceptance. Please check back soon.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Zuzuzzy/NS-VLA-Dataset")
+```
+
+## Associated Benchmarks
+
+- [LIBERO](https://github.com/Lifelong-Robot-Learning/LIBERO) — Language-conditioned robotic manipulation
+- [LIBERO-Plus](https://arxiv.org/abs/2510.13626) — Robustness evaluation with perturbations
+- [CALVIN](https://github.com/mees/calvin) — Long-horizon language-conditioned manipulation
+
+## Citation
+
+```bibtex
+@article{zhu2026nsvla,
+  title={NS-VLA: Towards Neuro-Symbolic Vision-Language-Action Models},
+  author={Zhu, Ziyue and Wu, Shangyang and Zhao, Shuai and Zhao, Zhiqiu and Li, Shengjie and Wang, Yi and Li, Fang and Luo, Haoran},
+  journal={arXiv preprint arXiv:XXXX.XXXXX},
+  year={2026}
+}
+```
+
+## License
+
+This dataset is released under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0).