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English(EN) Private Retrieval Augmented Generation via Random Projection

随机投影方法增强RAG系统的隐私性

研究人员开发了一种新颖的随机投影方法,以增强检索增强生成(RAG)系统的隐私性。该技术旨在降低在使用大型语言模型(LLM)时,敏感信息从检索数据存储中泄露的风险。所提出的方法将相同的投影应用于数据存储和查询嵌入,可证明地保持语义相似性,同时提供针对数据提取攻击的显著保护。实证结果表明,这种轻量级方法在检索和生成性能方面均优于先前的方法。 AI

影响 这项研究为保护AI检索系统中敏感数据提供了一种更实用、更有效的方法,有望加速RAG在注重隐私的应用中的普及。

排序理由 关于AI系统隐私新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

随机投影方法增强RAG系统的隐私性

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关于AI系统隐私新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Dixi Yao, Tahseen Rabbani, Tian Li ·

    通过随机投影实现的私有检索增强生成

    arXiv:2610.22297v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) enhances the capabilities of large language models (LLMs) by querying external structured knowledge. However, it can also introduce privacy risks by leaking sensitive information from the retriev…