Cluster with Auctions: Jointly Optimizing Database Partitioning and Query Probing for Vector Search

Jul 16, 2026

Researchers present CwA (Cluster with Auctions), a method that jointly learns balanced database partitions and a neural probing function for approximate nearest neighbor search. Unlike traditional approaches that use the same assignment function for both queries and database vectors, CwA decouples these processes and directly optimizes search performance for the query distribution. The method employs a parallelizable auction algorithm for combinatorial optimization and demonstrates up to 4.7× throughput improvement over state-of-the-art methods when query and database distributions differ.

Why it matters: This work offers a significant advance in vector search efficiency, particularly in scenarios where query and database distributions are not aligned, by optimizing both partitioning and probing functions jointly.

Full story at: arXiv Information Retrieval ↗