Learning to Erase Private Knowledge from Multi-Documents for Retrieval-Augmented Large Language Models
Retrieval-Augmented Generation (RAG) is a promising technique for applying LLMs to proprietary domains. However, retrieved documents may contain sensitive knowledge, posing risks of privacy leakage in generative results. Thus, effectively erasing private information from retrieved documents is a key challenge for RAG....
Yujing Wang, Jinwen Chen, Hainan Zhang et al.
· ACM International Conference... · 1 citation