Papers by Taiki Miyagawa

1 papers
Differentially Private Synthetic Text Generation for Retrieval-Augmented Generation (RAG) (2026.findings-acl)

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Challenge: Existing private RAG methods rely on query-time differential privacy (DP) Existing studies have identified significant privacy risks when their databases contain sensitive information.
Approach: They propose a framework that generates differentially private RAG databases using LLMs . Unlike prior methods, the synthetic text can be reused once created .
Outcome: Experiments show that DP-SynRAG achieves superior performance to state-of-the-art RAG systems while maintaining a fixed privacy budget.

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