Yysrc/LIBERO-Spatial

Mantis

This is the official checkpoint of Mantis: A Versatile Vision-Language-Action Model with Disentangled Visual Foresight

• Paper: https://arxiv.org/pdf/2511.16175
• Code: https://github.com/zhijie-group/Mantis

🔥 Highlights

• Disentangled Visual Foresight augments action learning without overburdening the backbone.
• Progressive Training preserves the understanding capabilities of the backbone.
• Adaptive Temporal Ensemble reduces inference cost while maintaining stable control.

How to use

This is the Mantis model trained on the LIBERO spatial dataset. For detailed usage please refer to our repository.

📝 Citation

If you find our code or models useful in your work, please cite our paper:

@article{yang2025mantis,
  title={Mantis: A Versatile Vision-Language-Action Model with Disentangled Visual Foresight},
  author={Yang, Yi and Li, Xueqi and Chen, Yiyang and Song, Jin and Wang, Yihan and Xiao, Zipeng and Su, Jiadi and Qiaoben, You and Liu, Pengfei and Deng, Zhijie},
  journal={arXiv preprint arXiv:2511.16175},
  year={2025}
}