Update dataset card: Add paper, project page, code, sample usage, citation, and tags

README.md

@@ -4,19 +4,27 @@ task_categories:
 - robotics
 tags:
 - LeRobot
+- manipulation
+- vision-to-action
+- flow-matching
+- av-aloha
+- robomimic
+language:
+- en
 configs:
 - config_name: default
   data_files: data/*/*.parquet
 ---
 
-This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
+This dataset was created using [LeRobot](https://github.com/huggingface/lerobot) and contains demonstrations related to the paper [VITA: Vision-to-Action Flow Matching Policy](https://huggingface.co/papers/2507.13231).
 
 ## Dataset Description
 
+This dataset is part of the VITA project, a noise-free and conditioning-free policy learning framework that directly maps visual representations to latent actions using flow matching. It provides data for robotic manipulation tasks from benchmarks like ALOHA and Robomimic.
 
-
-- **Homepage:** [More Information Needed]
-- **Paper:** [More Information Needed]
+- **Homepage:** [https://ucd-dare.github.io/VITA/](https://ucd-dare.github.io/VITA/)
+- **Paper:** [VITA: Vision-to-Action Flow Matching Policy](https://huggingface.co/papers/2507.13231)
+- **Code:** [https://github.com/ucd-dare/VITA](https://github.com/ucd-dare/VITA)
 - **License:** apache-2.0
 
 ## Dataset Structure
@@ -182,11 +190,30 @@ This dataset was created using [LeRobot](https://github.com/huggingface/lerobot)
 }
 ```
 
+## Sample Usage
+
+This dataset is designed to be used with the [VITA framework](https://github.com/ucd-dare/VITA), which utilizes [LeRobot](https://github.com/huggingface/lerobot) for data handling. The VITA GitHub repository provides a `convert.py` script to preprocess Hugging Face datasets into an optimized offline Zarr format for faster training.
+
+To preprocess this dataset for use with VITA, first set up the VITA environment as described in its [GitHub README's Getting Started section](https://github.com/ucd-dare/VITA#getting-started).
+
+Once the environment is set up, you can convert this Hugging Face dataset (e.g., `iantc104/av_aloha_sim_hook_package` as an example repository ID from the VITA project) to the offline Zarr format by running the `convert.py` script:
+
+```bash
+cd VITA/gym-av-aloha/scripts
+python convert.py -r iantc104/av_aloha_sim_hook_package
+```
+
+The processed dataset will be stored in `./VITA/gym-av-aloha/outputs`, ready for training with VITA's scripts.
 
 ## Citation
 
 **BibTeX:**
 
 ```bibtex
-[More Information Needed]
+@article{gao2025vita,
+  title={VITA: Vision-to-Action Flow Matching Policy},
+  author={Gao, Dechen and Zhao, Boqi and Lee, Andrew and Chuang, Ian and Zhou, Hanchu and Wang, Hang and Zhao, Zhe and Zhang, Junshan and Soltani, Iman},
+  journal={arXiv preprint arXiv:2507.13231},
+  year={2025}
+}
 ```