SOURCE-LINKED INTELLIGENCE
Spruce: Scalable Private Outsourced Retrieval Using Compact Embeddings
Retrieval-Augmented Generation (RAG) has made dense retrieval over large document collections a standard building block. Organizations increasingly outsource vector indexes to untrusted clouds, exposing proprietary corpora and user queries. Cryptographic protection is challenging because each query searches corpus-scale state, causing computation, correlated randomness, and communication to grow with the corpus. At million-document scale, a naive secure implementation takes minutes and about 90 GB of communication per query. Even recent optimized systems require 10--22 seconds. We propose Spru
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-03T05:19:03.000Z
First collected: 2026-09-21T05:11:56.580Z. This is not the publication date.