Meet AdANNS: A Novel Framework that Leverages Adaptive Representations for Different Phases of ANNS Pipelines to Improve the Accuracy-Compute Tradeoff

To obtain information comparable to a given query, large-scale web search engines train an encoder to contain the query and then connect the encoder to an approximate nearest neighbor search (ANNS) pipeline. Learned representations are often stiff, high-dimensional vectors generally employed as-is throughout the ANNS pipeline. They can result in computationally expensive retrieval because of […]

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