LLM-Powered Interactive Graph Search: A Scalable and Practical Approach
Summary: LLM oracles replace noisy reachability queries in interactive graph search, addressing ambiguous/overlapping nodes in real hierarchies. SuS: similarity-based upward search with layer-wise refinement and fast init, outperforming four baselines on real datasets. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Han Linghu (Hong Kong University of Science and Technology)
- 2. Qianhao Cong (Butterfly Effect Private Limited)
- 3. Yuming Huang (National University of Singapore)
- 4. Shangqi Lu (Hong Kong University of Science and Technology)
- 5. Liang Feng (Chongqing University)
- 6. Jing Tang (Hong Kong University of Science and Technology)
BibTeX Citation
@inproceedings{linghu_sigmod26,
title = {{LLM-Powered Interactive Graph Search: A Scalable and Practical Approach}},
author = {Linghu, Han and Cong, Qianhao and Huang, Yuming and Lu, Shangqi and Feng, Liang and Tang, Jing},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3769804},
url = {https://dl.acm.org/doi/10.1145/3769804},
year = {2026}
}
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