Improve dataset card: Add task categories, project/code links, and sample usage

This PR significantly improves the dataset card for the `A2_Dataset` by:
- Adding `task_categories: ['robotics']` and relevant `tags` (`pick-and-place`, `manipulation`, `reinforcement-learning`) to the metadata for better discoverability.
- Including direct links to the project page (https://xukechun.github.io/papers/A2) and the GitHub repository (https://github.com/xukechun/Action-Prior-Alignment).
- Expanding the initial description with a brief summary of the paper's contribution to provide more context.
- Incorporating a "Sample Usage" section with `bash` commands for data collection, training, and evaluation, directly extracted from the project's GitHub README.
- Adding the BibTeX citation for proper attribution.

README.md

@@ -1,5 +1,71 @@
 ---
 license: mit
+task_categories:
+- robotics
+tags:
+- pick-and-place
+- manipulation
+- reinforcement-learning
 ---
 
-This is the official repository for the training dataset of the paper: [Efficient Alignment of Unconditioned Action Prior for Language-conditioned Pick and Place in Clutter](https://huggingface.co/papers/2503.09423). Please download the file and unzip it in the `data` folder.
+This is the official repository for the training dataset of the paper: [Efficient Alignment of Unconditioned Action Prior for Language-conditioned Pick and Place in Clutter](https://huggingface.co/papers/2503.09423).
+
+We study the task of language-conditioned pick and place in clutter, where a robot should grasp a target object in open clutter and move it to a specified place. This dataset supports the A$^2$ action prior alignment method, which integrates foundation priors from vision, language, and action to enable effective policies.
+
+Project Page: https://xukechun.github.io/papers/A2
+Code: https://github.com/xukechun/Action-Prior-Alignment
+
+Please download the file and unzip it in the `data` folder.
+
+### Sample Usage
+
+The following snippets from the [GitHub repository](https://github.com/xukechun/Action-Prior-Alignment) demonstrate how to use this dataset for data collection, training, and evaluation.
+
+#### Data Collection
+- For pick data
+```bash
+bash scripts/data_collection/collect_data_grasp.sh
+```
+- For place data
+```bash
+bash scripts/data_collection/collect_data_place.sh
+```
+
+#### Training
+- Unified training for pick and place
+```bash
+bash scripts/train/train_clutter_gp_unified.sh
+```
+- Adaptation for place
+```bash
+bash scripts/train/train_clutter_gp_adaptive.sh
+```
+
+#### Evaluation
+To test the pre-trained model, simply change the location of `--model_path`:
+
+- Pick
+```bash
+bash scripts/test/test_grasp.sh
+```
+- Place
+```bash
+bash scripts/test/test_place.sh
+```
+- Pick and place
+```bash
+bash scripts/test/test_pickplace.sh
+```
+
+### Citation
+
+If you find this work useful, please consider citing:
+
+```bibtex
+@article{xu2025efficient,
+  title={Efficient Alignment of Unconditioned Action Prior for Language-conditioned Pick and Place in Clutter},
+  author={Xu, Kechun and Xia, Xunlong and Wang, Kaixuan and Yang, Yifei and Mao, Yunxuan and Deng, Bing and Xiong, Rong and Wang, Yue},
+  journal={arXiv preprint arXiv:2503.09423},
+  year={2025}
+}
+```