Papers with ANN index

1 papers
Drift-Adapter: A Practical Approach to Near Zero-Downtime Embedding Model Upgrades in Vector Databases (2025.emnlp-main)

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Challenge: Upgrading embedding models in production environments requires re-encoding the entire corpus and rebuilding the Approximate Nearest Neighbor (ANN) index.
Approach: They propose a lightweight, learnable transformation layer designed to bridge embedding spaces between models by mapping new queries into the legacy embeddable space.
Outcome: The proposed transformation layer recovers 95–99% of the retrieval recall of a full re-embedding, adding less than 10,s query latency.

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