SIGKDD 2025 paper proposing adaptive awareness capabilities for graph-based approximate nearest neighbor search, enabling the search algorithm to dynamically adjust its strategy based on local graph characteristics and query properties.

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.

ICML 2019 paper introducing a learned routing approach for similarity graphs, using machine learning to guide greedy search traversal in graph-based approximate nearest neighbor search.

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.

Paper from 2024 proposing a probabilistic routing approach for graph-based approximate nearest neighbor search, introducing probability models to guide search traversal on proximity graphs.

VLDB 2024 paper proposing RoarGraph, a projected bipartite graph structure for efficient cross-modal approximate nearest neighbor search. The method addresses the challenges of searching across different modalities (e.g., text, image) using graph-based indexing.