LeanVec: Searching vectors faster by making them fit

arXiv:2312.16335v2 Announce Type: replace
Abstract: Modern deep learning models have the ability to generate high-dimensional vectors whose similarity reflects semantic resemblance. Thus, similarity search, i.e., the operation of retrieving those vectors in a large collection that are similar to a given query, has become a critical component of a wide range of applications that demand highly accurate and timely answers. In this setting, the high vector dimensionality puts similarity search systems under compute and memory pressure, leading to subpar performance. …

abstract arxiv become collection cs.db cs.lg deep learning faster generate making modern query search searching semantic them type vectors