Proposes local-first IR framework with experiments showing dense retrieval maintains over 91% nDCG@10 up to 100K documents on consumer hardware and 7B local models reach within 4 points of cloud baselines.
Fedrag: A framework for fine-tuning retrieval-augmented generation systems.arXiv preprint arXiv:2506.09200, 2025
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A survey of architectures, threats, defenses, and future directions for security and privacy in RAG systems.
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Proposes local-first IR framework with experiments showing dense retrieval maintains over 91% nDCG@10 up to 100K documents on consumer hardware and 7B local models reach within 4 points of cloud baselines.
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Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems
A survey of architectures, threats, defenses, and future directions for security and privacy in RAG systems.