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arXiv — cs.AI preprintsInternational5 October 2026

MRVQ: One Resident Index for Dimension- and Rate-Elastic Vector Search

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arXiv:2610.03651v1 Announce Type: new Abstract: Dense-retrieval services must switch among embedding-prefix dimensions and index bit rates as latency, quality, and memory budgets change. Tuning a quantizer separately for each rate gives the best quality, but the retrieval tier then holds several code streams and quantizer states at once. We introduce Matryoshka Residual Vector Quantization (MRVQ), a post-hoc residual quantizer for frozen embeddings. Its maximum-rate code can be truncated two ways: dropping residual stages lowers the rate, and dropping embedding coordinates lowers the dimension
— arXiv — cs.AI preprints

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