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Distribution-Aware Exploration for Adaptive HNSW Search
Summary: Query-adaptive HNSW exploration factor (Ada-ef) for ANNS: statistically model query–data similarity to set per-query ef under a declarative target recall. Distribution-aware, update-friendly, avoids over/under-searching; 4x latency, 50x compute, 100x memory gains.
(summarized by gpt-5.4-mini on Apr 11 2026)
Paper ID
h1bd16fe7d0ba040e
Venue
SIGMOD
Year
2026
Pagerank
5.1376962e-05
Overall Rank
9,593 | 35.70%
DOI
10.1145/3786639
PDF
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(CC BY 4.0)
Incoming Non-self Citations Over Time
BibTeX Citation
@inproceedings{zhang_sigmod26,
title = {{Distribution-Aware Exploration for Adaptive HNSW Search}},
author = {Zhang, Chao and Miller, Renée J.},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786639},
url = {https://dl.acm.org/doi/10.1145/3786639},
year = {2026}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 22 of 22 cited papers.
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A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search 2021
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HD-Index: Pushing the Scalability-Accuracy Boundary for Approximate kNN Search in High-Dimensional Spaces 2018
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1,610
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Kuzu* Graph Database Management System 2023
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1,881
iDEC: Indexable Distance Estimating Codes for Approximate Nearest Neighbor Search 2020
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2,268
ELPIS: Graph-Based Similarity Search for Scalable Data Science 2023
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2,885
Graph-Based Vector Search: An Experimental Evaluation of the State-of-the-Art 2025
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Steiner-Hardness: A Query Hardness Measure for Graph-Based ANN Indexes 2024
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FARGO: Fast Maximum Inner Product Search via Global Multi-Probing 2023
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TigerVector: Supporting Vector Search in Graph Databases for Advanced RAGs 2025
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DARTH: Declarative Recall Through Early Termination for Approximate Nearest Neighbor Search 2026
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