Jiangsu Second Normal University

GuardRAG: A Post-Retrieval Defense against Poisoning Attacks in Retrieval-Augmented Generation

Retrieval-Augmented Generation (RAG) enhances the factual grounding of Large Language Models (LLMs) by incorporating external evidence, but also exposes them to corpus poisoning attacks. In particular, coordinated attacks can introduce multiple mutually reinforcing poisoned documents into retrieved contexts, making rel...