8 papers · 1 filter
E2E: Efficient Filtered AKNN Search via Adaptive Termination
Wenxuan Xia, Mingyu Yang, Wentao Li +1
Approximate k-Nearest Neighbor (AKNN) search is widely used in vector databases. When vectors carry additional attributes (e.g., labels or numerical values), filtered AKNN search r…
Multiple Index Merge for Approximate Nearest Neighbor Search
Liuchang Jing, Mingyu Yang, Lei Li +2
Approximate nearest neighbor (AKNN) search in high-dimensional space is a foundational problem in vector databases with widespread applications. Among the numerous AKNN indexes…
Quantization Meets Projection: A Happy Marriage for Approximate k-Nearest Neighbor Search
Mingyu Yang, Liuchang Jing, Wentao Li +1
Approximate -nearest neighbor (AKNN) search is a fundamental problem with wide applications. To reduce memory and accelerate search, vector quantization is widely adopted. Howev…
Elastic Index Selection for Label-Hybrid AKNN Search
Mingyu Yang, Wenxuan Xia, Wentao Li +2
Real-world vector embeddings are usually associated with extra labels, such as attributes and keywords. Many applications require the nearest neighbor search that contains specific…
VSAG: An Optimized Search Framework for Graph-based Approximate Nearest Neighbor Search
Xiaoyao Zhong, Haotian Li, Jiabao Jin +11
Approximate nearest neighbor search (ANNS) is a fundamental problem in vector databases and AI infrastructures. Recent graph-based ANNS algorithms have achieved high search accurac…
EnhanceGraph: A Continuously Enhanced Graph-based Index for High-dimensional Approximate Nearest Neighbor Search
Xiaoyao Zhong, Jiabao Jin, Peng Cheng +5
Recently, Approximate Nearest Neighbor Search in high-dimensional vector spaces has garnered considerable attention due to the rapid advancement of deep learning techniques. We obs…