GoldenRetriever replaces ranking with threshold selection for encrypted RAG
Researchers propose a non-interactive homomorphic encryption framework that selects documents by similarity threshold rather than ranking, reducing latency in privacy-preserving retrieval-augmented generation systems.
Researchers have published a new approach to privacy-preserving retrieval-augmented generation that replaces computationally expensive ranking with threshold-based document selection. The framework, called GoldenRetriever, uses homomorphic encryption to evaluate document similarity without exposing ...
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- Source type
- Primary publication (lab/vendor blog) — our analysis + implication
- Source link
- r/arxiv-compression
- Published
- UTC
- Byline
- By the gotcontext.ai team (editorial standards)
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