AI RESEARCH
HaS: Accelerating RAG through Homology-Aware Speculative Retrieval
arXiv CS.CL
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ArXi:2604.20452v1 Announce Type: cross Retrieval-Augmented Generation (RAG) expands the knowledge boundary of large language models (LLMs) at inference by retrieving external documents as context. However, retrieval becomes increasingly time-consuming as the knowledge databases grow in size. Existing acceleration strategies either compromise accuracy through approximate retrieval, or achieve marginal gains by reusing results of strictly identical queries.