metadata
base_model:
- Qwen/Qwen2.5-VL-7B-Instruct
datasets:
- yushaohan/ProGuard-data
language:
- en
tags:
- vlm
- safety
- guard
library_name: transformers
pipeline_tag: image-text-to-text
ProGuard-7B
ProGuard is a proactive multimodal safeguard model introduced as part of the DeepSight toolkit. It is designed to identify and reason about unknown risks across both text and visual modalities, moving beyond rigid predefined classification systems.
- ProGuard Paper: ProGuard: Towards Proactive Multimodal Safeguard
- DeepSight Paper: DeepSight: An All-in-One LM Safety Toolkit
- Project Page: DeepSight Homepage
- GitHub Repository: DeepSafe (Safety Evaluation ToolKit)
This model is the official open-source implementation of ProGuard. For deployment instructions, please refer to this link.
Citation
If you find this model helpful, please cite our research:
@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}
}