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cs.DC2025
On The Reproducibility Limitations of RAG Systems
Baiqiang Wang, Dongfang Zhao, Nathan R Tallent +1
Retrieval-Augmented Generation (RAG) is increasingly employed in generative AI-driven scientific workflows to integrate rapidly evolving scientific knowledge bases, yet its reliabi…
cs.IR2025
PIR-RAG: A System for Private Information Retrieval in Retrieval-Augmented Generation
Baiqiang Wang, Qian Lou, Mengxin Zheng +1
Retrieval-Augmented Generation (RAG) has become a foundational component of modern AI systems, yet it introduces significant privacy risks by exposing user queries to service provi…