mlsanityData to 7 Oct 2026

Foundations of Vector Retrieval

arXiv 2401.09350 ↗First posted 17 Jan 2024cs.DS cs.IRcited by 5

Not on the map. Why?

Abstract (arXiv)

Vectors are universal mathematical objects that can represent text, images, speech, or a mix of these data modalities. That happens regardless of whether data is represented by hand-crafted features or learnt embeddings. Collect a large enough quantity of such vectors and the question of retrieval becomes urgently relevant: Finding vectors that are more similar to a query vector. This monograph is concerned with the question above and covers fundamental concepts along with advanced data structures and algorithms for vector retrieval. In doing so, it recaps this fascinating topic and lowers barriers of entry into this rich area of research.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Jan 2024.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 3.

5 papers.