Paper introducing FANNG, a fast algorithm for constructing approximate nearest neighbor graphs. The method builds graphs that enable efficient nearest neighbor queries while maintaining high quality approximations.

Foundational paper introducing the navigable small world (NSW) graph algorithm for approximate nearest neighbor search, which became the basis for widely-used graph-based ANN methods including HNSW.

Research paper by Chen et al. examining the meaningfulness of nearest neighbor search in high-dimensional spaces. Analyzes limitations and implications for vector similarity search. Key for understanding ANN effectiveness.

FusionANNS architecture by Bing Tian et al. for billion-scale ANN search using CPU/GPU cooperation.

Paper by Tepper et al. proposing GleanVec, a method to accelerate vector search using minimalist nonlinear dimensionality reduction. Improves efficiency for high-dimensional vector queries.

iDEC by Gong et al. for approximate nearest neighbor search using indexable distance estimating codes. VLDB Endowment 13.9 (2020).