Projection and Quantisation: A Unifying View of Learning to Hash, from Random Projections to the RAG Era

arXiv:2510.04127v2 Announce Type: replace-cross Abstract: Approximate nearest neighbour (ANN) search underpins large-scale retrieval, increasingly within the retrieval-augmented generation pipelines that ground large language models, yet the methods that address it have multiplied across communities until they are seldom read as a single field. We argue they form one field with three design choices, and develop the projection-quantisation-organisation (PQO) lens, under which locality-sensitive hashing, learned binary hashing, deep end-to-end hashing, product quantisation, graph-based indexes,

Source: arXiv cs.LG — read the full report at the original publisher.

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