Papers by Jiawen Shi
SafeAgent: Safeguarding LLM Agents via an Automated Risk Simulator (2026.acl-long)
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Xueyang Zhou, Weidong Wang, Lin Lu, Jiawen Shi, Guiyao Tie, Xu Yongtian, Lixing Chen, Pan Zhou, Neil Zhenqiang Gong, Lichao Sun
| Challenge: | SafeAgent improves agent safety through fully automated synthetic data generation. |
| Approach: | They propose a framework that improves agent safety through fully automated synthetic data generation. |
| Outcome: | The proposed framework outperforms closed-source models on two safety benchmarks and one real-world task. |
PersLEARN: Research Training through the Lens of Perspective Cultivation (2023.acl-demo)
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Yu-Zhe Shi, Shiqian Li, Xinyi Niu, Qiao Xu, Jiawen Liu, Yifan Xu, Shiyu Gu, Bingru He, Xinyang Li, Xinyu Zhao, Zijian Zhao, Yidong Lyu, Zhen Li, Sijia Liu, Lin Qiu, Jinhao Ji, Lecheng Ruan, Yuxi Ma, Wenjuan Han, Yixin Zhu
| Challenge: | PersLEARN is a tool designed to facilitate the cultivation of scientific perspectives . junior researchers struggle to identify the perspectives reflected in the literature and struggle to develop their own viewpoints. |
| Approach: | They propose a tool to facilitate the cultivation of scientific perspectives by interacting with a prompt-based model and allowing students to develop their own perspectives explicitly. |
| Outcome: | The proposed tool outperforms baseline approaches across multiple domains of literature from different perspectives. |
Merge Hijacking: Backdoor Attacks to Model Merging of Large Language Models (2025.acl-long)
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| Challenge: | Existing research on model merging focuses on optimizing model performance and minimizing backdoors. |
| Approach: | They propose a backdoor attack targeting model merging in Large Language Models that creates a unified model for multi-domain tasks. |
| Outcome: | The proposed attack is effective across models, merging algorithms, and tasks while maintaining utility across tasks. |