Fast-Convergent Proximity Graphs for Approximate Nearest Neighbor Search
Summary: Introduces alpha-convergent graphs for ANN, a proximity-graph index with a pruning rule that yields polylog-time exact NN when the true NN lies within fixed radius tau, otherwise ANN under bounded intrinsic dimensionality. Practical alpha-CNG localizes pruning for scalable build/search and outperforms prior PG indexes in distance evals and steps. (summarized by gpt-5-mini on Apr 11 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Binhong Li (Hong Kong University of Science and Technology)
- 2. Xiao Yan (Wuhan University)
- 3. Shangqi Lu (Hong Kong University of Science and Technology)
BibTeX Citation
@inproceedings{li_sigmod26,
title = {{Fast-Convergent Proximity Graphs for Approximate Nearest Neighbor Search}},
author = {Li, Binhong and Yan, Xiao and Lu, Shangqi},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786650},
url = {https://dl.acm.org/doi/10.1145/3786650},
year = {2026}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,028 | Advances of Query Processing in Vector Databases | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 26 of 26 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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