SOURCE-LINKED INTELLIGENCE

RSLM: Training-Free Vector Quantization for Approximate Nearest Neighbor Search

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

By introducing RSLM (Rotated Scaled Lloyd-Max), a family of training-free vector quantization codecs compressing embeddings to 1--4 bits per dimension, we reduce memory cost and memory bandwidth of a typical large-scale Approximate Nearest Neighbor (ANN) search system, while reducing its complexity and keeping or improving recall across multiple benchmark datasets. State-of-the-art systems filter candidates using coarse partitions, approximately score them to narrow the set, and then rescore the best with higher precision representations (often >=8 bits per dimension). Our relativized codecs c

Read original source ↗ Open in workspace

recordType

paper

region

Global