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base_model:
- Qwen/Qwen2.5-VL-3B-Instruct
datasets:
- yushaohan/ProGuard-data
language:
- en
tags:
- vlm
- safety
- guard
library_name: transformers
pipeline_tag: image-text-to-text
---
# ProGuard-3B
ProGuard is a proactive multimodal safeguard model. It is designed to identify and reason about unknown risks across both text and visual modalities, moving beyond rigid predefined classification systems.
- **Arxiv Paper:** [ProGuard: Towards Proactive Multimodal Safeguard](https://arxiv.org/abs/2512.23573)
- **Project Page:** [ProGuard Homepage](https://yushaohan.github.io/ProGuard/)
- **GitHub Repository:** [ProGuard Implementation](https://github.com/yushaohan/ProGuard), [DeepSafe Implementation](https://github.com/AI45Lab/DeepSafe)
This model is the official open-source implementation of **ProGuard**. For deployment instructions, please refer to **[this link](https://github.com/yushaohan/ProGuard/tree/master/deploy)**.
## Citation
If you find this model helpful, please cite our research:
```bibtex
@article{yu2025proguard,
title={ProGuard: Towards Proactive Multimodal Safeguard},
author={Yu, Shaohan and Li, Lijun and Si, Chenyang and Sheng, Lu and Shao, Jing},
journal={arXiv preprint arXiv:2512.23573},
year={2025},
url={https://yushaohan.github.io/ProGuard/}
}
@article{zhang2026deepsight,
title={DeepSight: An All-in-One LM Safety Toolkit},
author={Zhang, Bo and Guo, Jiaxuan and Li, Lijun and Liu, Dongrui and Chen, Sujin and Chen, Guanxu and Zheng, Zhijie and Lin, Qihao and Yan, Lewen and Qian, Chen and others},
journal={arXiv preprint arXiv:2602.12092},
year={2026}
}
``` |