2025
EcoSafeRAG: Efficient Security through Context Analysis in Retrieval-Augmented Generation
EMNLP 2025
Retrieval-Augmented Generation (RAG) compensates for the static knowledge limitations of Large Language Models (LLMs) by integrating external knowledge, producing responses with enhanced factual correctness and query-specific contextualization. However, it also introduces new attack surfaces such as