RobotWin 2.0 (Preprocessed LeRobot v2.1 Release)

This repository releases our preprocessed RoboTwin / RobotWin 2.0 dataset in LeRobot v2.1 format for the open-source release of Fast-WAM: Do World Action Models Need Test-time Future Imagination?

This is not the official upstream RoboTwin release. It is our paper-specific processed version prepared to support training, evaluation, and reproducibility for our project.

This Hugging Face repository distributes the dataset as split .tar.gz archives to make large-scale download and release management easier. After extraction, the recovered dataset keeps the original LeRobot v2.1 directory structure.

The uploaded repository is expected to contain:

README.md
dataset_stats.json
robotwin2.0.tar.gz.part-00
robotwin2.0.tar.gz.part-01
...
robotwin2.0.tar.gz.part-07

Summary

• Provenance: preprocessed from RoboTwin 2.0 for the Fast-WAM open-source release
• Format: LeRobot v2.1
• Robot type: aloha
• FPS: 50
• Episodes: 27,500
• Frames: 6,075,103
• Number of archive parts: 8

Project

• Project page: https://yuantianyuan01.github.io/FastWAM/
• Paper: https://arxiv.org/abs/2603.16666
• Code repository: https://github.com/yuantianyuan01/FastWAM

Download and Extract

Download all archive parts from this repository, then reconstruct and extract the dataset with:

cat robotwin2.0.tar.gz.part-* | tar -xzf -

After extraction, you will get:

robotwin2.0/
  data/
  meta/
  videos/

After extraction, the dataset can be loaded as a standard LeRobot v2.1 dataset.

Notes

• dataset_stats.json is provided at the repository root as an additional statistics file from the original local dataset directory.
• The release is distributed as split archives. Users need to reconstruct and extract the dataset locally before loading it with LeRobot-compatible tooling.

License

This release is a preprocessed derivative of RoboTwin 2.0 for Fast-WAM.

It is released under the MIT license, consistent with the upstream RoboTwin 2.0 release. Please also refer to the original RoboTwin project and dataset for upstream attribution and terms.

Citation

If you use this release, please cite the Fast-WAM paper.

@misc{yuan2026fastwam,
  title={Fast-WAM: Do World Action Models Need Test-time Future Imagination?},
  author={Tianyuan Yuan and Zibin Dong and Yicheng Liu and Hang Zhao},
  year={2026},
  note={arXiv preprint arXiv:2603.16666}
}

If you use the underlying RoboTwin 2.0 data source, please also cite the original RoboTwin 2.0 paper:

@article{chen2025robotwin,
  title={Robotwin 2.0: A scalable data generator and benchmark with strong domain randomization for robust bimanual robotic manipulation},
  author={Chen, Tianxing and Chen, Zanxin and Chen, Baijun and Cai, Zijian and Liu, Yibin and Li, Zixuan and Liang, Qiwei and Lin, Xianliang and Ge, Yiheng and Gu, Zhenyu and others},
  journal={arXiv preprint arXiv:2506.18088},
  year={2025}
}

Official RoboTwin links:

• RoboTwin repository: https://github.com/RoboTwin-Platform/RoboTwin
• RoboTwin website: https://robotwin-platform.github.io/
• RoboTwin 2.0 paper: https://arxiv.org/abs/2506.18088