CITATION.cff

cff-version: 1.2.0
message: "If you use snapvec in your research, please cite it as below."
title: "snapvec: fast compressed approximate nearest-neighbor search"
authors:
  - family-names: "Steffens"
    given-names: "Jayson"
    email: "stffens@gmail.com"
type: software
version: "0.11.0"
date-released: "2026-04-21"
license: MIT
repository-code: "https://github.com/stffns/snapvec"
url: "https://stffns.github.io/snapvec/"
keywords:
  - "approximate nearest neighbor"
  - "vector search"
  - "quantization"
  - "product quantization"
  - "randomized Hadamard transform"
  - "TurboQuant"
  - "embeddings"
  - "retrieval"
abstract: >-
  snapvec is a Python library for fast, compressed approximate
  nearest-neighbor search over embedding vectors.  It implements
  randomized Hadamard transform plus Lloyd-Max scalar quantization
  (TurboQuant), product quantization, and IVF-PQ with optional
  float16 rerank.  Runtime dependencies are limited to NumPy; hot
  paths are compiled via Cython and OpenMP.
references:
  - type: article
    authors:
      - family-names: "Zandieh"
        given-names: "Amir"
      - family-names: "Daliri"
        given-names: "Mahdi"
      - family-names: "Hadian"
        given-names: "Amirhossein"
      - family-names: "Mirrokni"
        given-names: "Vahab"
    title: "TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate"
    year: 2025
    identifiers:
      - type: other
        value: "arXiv:2504.19874"
  - type: article
    authors:
      - family-names: "Jégou"
        given-names: "Hervé"
      - family-names: "Douze"
        given-names: "Matthijs"
      - family-names: "Schmid"
        given-names: "Cordelia"
    title: "Product Quantization for Nearest Neighbor Search"
    journal: "IEEE Transactions on Pattern Analysis and Machine Intelligence"
    year: 2011
    volume: 33
    number: 1
    start: 117
    end: 128