Jiaqi-hkust/Robust-U1-SFT

Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?

Robust-U1 is a unified MLLM that self-recovers corrupted visual content and reasons over it, enabling robust visual understanding under real-world image degradations.

• Paper: Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?
• Repository: jqtangust/Robust-U1
• Project Page: Hugging Face Space

🏰 Pretrained checkpoints (reference)

Checkpoint	Link	Note
BAGEL-7B-MoT	ByteDance-Seed/BAGEL-7B-MoT	Used as initial weights for training.
Robust-U1	Jiaqi-hkust/Robust-U1	Final model for visual self-recovery and multimodal reasoning.
Robust-U1-RL	Jiaqi-hkust/Robust-U1-RL	Fine-tuned with reinforcement learning.
Robust-U1-SFT	Jiaqi-hkust/Robust-U1-SFT	Fine-tuned with supervised learning.

⭐️ Citation

If you find this repository useful, please cite our paper:

@inproceedings{
2026robustu,
title={Robust-U1: Can {MLLM}s Self-Recover Corrupted Visual Content for Robust Understanding?},
author={Jiaqi Tang, Jianmin Chen, Youyang Zhai, Wei Wei, Runtao Liu, Mengjie Zhao, Xiangyu Wu, Qingfa Xiao, Qifeng Chen},
booktitle={Forty-third International Conference on Machine Learning},
year={2026},
url={https://openreview.net/forum?id=I6W6cxVVts}
}