Papers by Peiru Yang
Knowledge Poisoning Attacks on Medical Multi-Modal Retrieval-Augmented Generation (2026.acl-long)
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Peiru Yang, Haoran Zheng, Tong Ju, Shiting Wang, Wanchun Ni, Jiajun Liu, Shangguang Wang, Yongfeng Huang, Tao Qi
| Challenge: | Existing studies have investigated knowledge poisoning attacks in medical RAG systems . knowledge poison attacks can disrupt model outputs and undermine system reliability . |
| Approach: | They propose a knowledge poisoning framework that injects misinformation into textual data . they propose to use paired visual data as a query-agnostic trigger to promote retrieval . |
| Outcome: | The proposed framework produces clinically plausible but incorrect generations on five LLMs and datasets. |
HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation (2021.acl-long)
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| Challenge: | Existing news recommendation methods learn a single user embedding for each user from their previous behaviors to represent their overall interest. Existing methods only learn 'one' embeddable representation vectors to model user interest. |
| Approach: | They propose a news recommendation method with hierarchical user interest modeling that captures user interest in news rather than a single user embedding. |
| Outcome: | The proposed method can better capture multi-grained user interest in news. |