3 papers
cs.IR2026
Matryoshka Hash Representations for Model-Aware Compact Semantic Retrieval
Peichun Hua, Yunming Xiao
Retrieval-augmented generation (RAG) depends on dense retrieval: each document is stored as a learned vector, and a query is answered by finding its nearest neighbors in that vecto…
cs.CR2026
Spruce: Scalable Private Outsourced Retrieval Using Compact Embeddings
Peichun Hua, Yunming Xiao
Retrieval-Augmented Generation (RAG) has made dense retrieval over large document collections a standard building block. Organizations increasingly outsource vector indexes to untr…
cs.CR2026
Pointing the Way, Hiding the Destination: Practical Private Dense Retrieval at Scale
Peichun Hua, Danyang Chen, Junan Zhang +5
Hosted retrieval-augmented generation (RAG) and semantic search allow users to query valuable provider-held corpora, raising two competing demands: to hide each query and chosen re…