作者位次 #2/4ACL 2026Findings· Findings of ACL
Differentially Private Synthetic Text Generation for Retrieval-Augmented Generation ( RAG )
Junki Mori · Kazuya Kakizaki · Taiki Miyagawa · Jun Sakuma
摘要
Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by grounding them in external knowledge. However, its application in sensitive domains is limited by privacy risks. Existing private RAG methods typically rely on query-time differential privacy (DP), which requires repeat...