Dialect-Agnostic SQL Parsing via LLM-Based Segmentation
Summary: SQLFlex combines grammar parsing with LLM-based clause- and expression-level segmentation, avoiding LLMs’ weaknesses on hierarchical SQL and hallucination. It robustly parses eight dialects (91.55–100%), improving linting and test-case reduction over existing tools.
(summarized by gpt-5.6-luna on Jul 26 2026)
@inproceedings{an_sigmod26,
title = {{Dialect-Agnostic SQL Parsing via LLM-Based Segmentation}},
author = {An, Junwen and Mahathevan, Kabilan and Rigger, Manuel},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802038},
url = {https://dl.acm.org/doi/10.1145/3802038},
year = {2026}
}
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