Robust U1
Robust-U1 is a unified Multimodal Large Language Model (MLLM) that can self-recover corrupted visual content and perform multimodal reasoning over it. This enables robust visual understanding even under real-world...
Source du modèle
- Type
- Text model
- Taille du fichier
- 320 MB–27,2 GB
- Version
- vRevision 4388f4f
- Mis à jour
- 1 nov. 2026
- Téléchargements
- 42
- Source
- Hugging Face
Description de la source
Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?
Robust-U1 is a unified Multimodal Large Language Model (MLLM) that can self-recover corrupted visual content and perform multimodal reasoning over it. This enables robust visual understanding even under real-world image degradations.
- Paper: Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?
- Repository: jqtangust/Robust-U1
- Demo: Hugging Face Space
🏰 Pretrained Checkpoints
| 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 the paper:
@inproceedings{tang2026robustu1,
title={Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?},
author={Tang, Jiaqi and Chen, Jianmin and Zhai, Youyang and Wei, Wei and Liu, Runtao and Zhao, Mengjie and Wu, Xiangyu and Xiao, Qingfa and Chen, Qifeng},
booktitle={Proceedings of the 43rd International Conference on Machine Learning (ICML)},
year={2026},
}
Exigences
Modèles
1- Trouvé
VAE · 320 MB · SAFETENSORS · FP32 (tensor header) · Hugging Face · Jiaqi-hkust/Robust-U1
Sources
1 source
Sources
1 sourceVérifié 1 nov.
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Artefacts du modèle
2 artefacts
Artefacts du modèle
2 artefactsae.safetensors
safetensors · FP32 (tensor header) · 320 MB · SHA-256 afc8e28272cd…9e38 · Hugging Face
Download filemodel.safetensors
safetensors · BF16 (unverified) · 27,2 GB · SHA-256 bedcdcfa1be2…90e3 · Hugging Face
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3 extraits
Extraits de sources
3 extraits--- license: mit library_name: transformers pipeline_tag: any-to-any --- # Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding? [Robust-U1](https://arxiv.org/abs/2606.08063) is a unified Multimodal Large Language Model (MLLM) that can self-recover corrupted visual content and perform multimodal reasoning over it. This enables robust visual understanding even under real-world image degradations. - **Paper:** [Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?](https://arxiv.org/abs/2606.08063) - **Repository:** [jqtangust/Robust-U1](https://github.com/jqtangust/Robust-U1) - **Demo:** [Hugging Face Space](https://huggingface.co/spaces/Jiaqi-hkust/Robust-U1) ### 🏰 **Pretrained Checkpoints** | Checkpoint | Link | Note | |:----------:|:----:|:----:| | BAGEL-7B-MoT | [ByteDance-Seed/BAGEL-7B-MoT](https://huggingface.co/ByteDance-Seed/BAGEL-7B-MoT) | Used as initial weights for training. | | **Robust-U1** | [Jiaqi-hkust/Robust-U1](https://huggingface.co/Jiaqi-hkust/Robust-U1) | Final model for visual self-recovery and multimodal reasoning. | | **Robust-U1-RL** | [Jiaqi-hkust/Robust-U1-RL](https://huggingface.co/Jiaqi-hkust/Robust-U1-RL) | Fine-tuned with reinforcement learning. | | **Robust-U1-SFT** | [Jiaqi-hkust/Robust-U1-SFT](https://huggingface.co/Jiaqi-hkust/Robust-U1-SFT) | Fine-tuned with supervised learning. | ## ⭐️ **Citation** If you find this repository useful, please cite the paper: ```bibtex @inproceedings{tang2026robustu1, title={Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?}, author={Tang, Jiaqi and Chen, Jianmin and Zhai, Youyang and Wei, Wei and Liu, Runtao and Zhao, Mengjie and Wu, Xiangyu and Xiao, Qingfa and Chen, Qifeng}, booktitle={Proceedings of the 43rd International Conference on Machine Learning (ICML)}, year={2026}, } ```
Source context: 42 downloads · 2 likes · Pipeline any-to-any · Library transformers · Repo Jiaqi-hkust/Robust-U1
Source context: 8 downloads · 1 likes · Pipeline any-to-any · Library transformers · Repo Jiaqi-hkust/Robust-U1
