DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries
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We study the problem of vector set search with vector set queries. This task is analogous to traditional near-neighbor search, with the exception that both the query and each element in the collection are sets of vectors. We identify this problem as a core subroutine for many web applications and find that existing solutions are unacceptably slow. Towards this end, we present a new approximate search algorithm, DESSERT (DESSERT Effeciently Searches Sets of Embeddings via Retrieval Tables). DESSERT is a general tool with strong theoretical guarantees and excellent empirical performance. When we integrate DESSERT into ColBERT, a highly optimized state-of-the-art semantic search method, we find a 2-5x speedup on the MSMarco passage ranking task with minimal loss in recall, underscoring the effectiveness and practical applicability of our proposal.
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