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Bridging the Gap: Cardinality Estimation for Semantic Queries on Unstructured Data
Summary: SemStats estimates cardinalities for LLM-driven semantic queries over unstructured data using a semantic catalog/index and lightweight learned judges. Stratified importance sampling yields up to 25× lower error and 31× lower latency than prior methods.
(summarized by gpt-5.6-luna on Jul 26 2026)
Paper ID
h6fab0ea6b2b0b228
Venue
SIGMOD
Year
2026
Pagerank
4.9793485e-05
Overall Rank
10,422 | 29.93%
DOI
10.1145/3802024
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BibTeX Citation
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@inproceedings{xu_sigmod26,
title = {{Bridging the Gap: Cardinality Estimation for Semantic Queries on Unstructured Data}},
author = {Xu, Shihui and Wang, Jiayi and Li, Guoliang},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802024},
url = {https://dl.acm.org/doi/10.1145/3802024},
year = {2026}
}
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Showing 23 of 23 cited papers.
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1
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DeepDB: Learn from Data, not from Queries!
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795
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2018
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