ParSEval: Interactive Counterexample-driven Evaluation for Text-to-SQL
Summary: ParSEval interactively generates databases under configurable constraints to counterexample-test Text-to-SQL predictions beyond single-instance execution accuracy. It exposes witness instances and disagreement patterns across NULLs, duplicates, set/bag semantics, and key-foreign-key assumptions. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Chunyu Chen (Simon Fraser University)
- 2. Zhengjie Miao (Simon Fraser University)
- 3. Yong Zhang (Huawei)
- 4. Jiannan Wang (Tsinghua University)
BibTeX Citation
@article{chen_vldb26,
title = {{ParSEval: Interactive Counterexample-driven Evaluation for Text-to-SQL}},
author = {Chen, Chunyu and Miao, Zhengjie and Zhang, Yong and Wang, Jiannan},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4846--4849},
doi = {10.14778/3827998.3828137},
url = {https://doi.org/10.14778/3827998.3828137},
year = {2026}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,129 | ParSEval: Plan-aware Test Database Generation for SQL Equivalence Evaluation | 2025 | VLDB | 5.0751052e-05 |
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