{
 "id": "failo0711/ATG-MoE_TrainingSet",
 "owner": "failo0711",
 "name": "ATG-MoE_TrainingSet",
 "downloads": 2073,
 "likes": 0,
 "last_modified": "2026-03-20T03:37:56.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "robotics"
 ],
 "citation": "If you find this dataset or our work helpful, please cite:\n\n```bibtex\n@misc{huang2026atgmoeautoregressivetrajectorygeneration,\n  title={ATG-MoE: Autoregressive trajectory generation with mixture-of-experts for assembly skill learning},\n  author={Weihang Huang and Chaoran Zhang and Xiaoxin Deng and Hao Zhou and Zhaobo Xu and Shubo Cui and Long Zeng},\n  year={2026},\n  eprint={2603.19029},\n  archivePrefix={arXiv},\n  primaryClass={cs.RO},\n  url={https://arxiv.org/abs/2603.19029},\n}",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "68b141bb10592d1e572db6c695541a23b1f4d040",
 "stated_evidence": "https://huggingface.co/datasets/failo0711/ATG-MoE_TrainingSet/blob/68b141bb10592d1e572db6c695541a23b1f4d040/README.md",
 "file_evidence": "https://huggingface.co/datasets/failo0711/ATG-MoE_TrainingSet/tree/68b141bb10592d1e572db6c695541a23b1f4d040",
 "card_nc": false
}