3 papers
cs.CL2026
Learning to Erase Private Knowledge from Multi-Documents for Retrieval-Augmented Large Language Models
Yujing Wang, Jinwen Chen, Hainan Zhang +5
Retrieval-Augmented Generation (RAG) is a promising technique for applying LLMs to proprietary domains. However, retrieved documents may contain sensitive knowledge, posing risks o…
cs.CL2024
MaFeRw: Query Rewriting with Multi-Aspect Feedbacks for Retrieval-Augmented Large Language Models
Yujing Wang, Hainan Zhang, Liang Pang +3
In a real-world RAG system, the current query often involves spoken ellipses and ambiguous references from dialogue contexts, necessitating query rewriting to better describe user'…
cs.LG2024
Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning
Yujing Wang, Hainan Zhang, Sijia Wen +2
Federated learning is highly susceptible to model poisoning attacks, especially those meticulously crafted for servers. Traditional defense methods mainly focus on updating assessm…