Calibrating constraint-aware reranking for text-to-SQL execution under 11% schema drift: a factor ablation
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Keywords

text-to-SQL execution
constraint-aware reranking
schema drift
paired simulation
reproducibility

Abstract

We evaluated constraint-aware reranking for text-to-SQL execution under 11% schema drift. A deterministic paired simulation generated 56 cases and preserved a boundary-condition stratum. Mean execution accuracy changed from 0.543 to 0.580; the paired difference was +0.036 (95% interval +0.034 to +0.039). The result is limited to the stated simulation and is reported with a reproducible result artifact.

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References

Xie, H., Zhou, X., Yang, J., Shen, S., Wang, Z., Zheng, Y., Xu, T., Shi, Y., Zong, Z., Li, Y., Chen, P., Jiang, J., He, D., Yan, X., & Jiang, J. (2026). SiriusDeliver: Automating Data Warehouse Delivery at Tencent. arXiv. https://doi.org/10.48550/arXiv.2608.09185

Mellah, Y., Kocaman, V., Ul Haq, H., & Talby, D. (2024). Efficient schema-less text-to-SQL conversion using large language models. Artificial Intelligence in Health, 1(2), 96. https://doi.org/10.36922/aih.2661

Jain, K. (2024). Experimental Evaluation: Is NoSQL better than SQL Database?. https://doi.org/10.22541/au.172498858.84181818/v1

Rapolu, N. K. (2023). MIGRATION OF LEGACY DATABASE ORACLE/MS SQL TO HANA DATABASE TO IMPROVE REAL-TIME ONLINE ANALYTICAL PROCESSING AND ONLINE TRANSACTION PROCESSING FROM ONE DATA MODEL. International Scientific Journal of Engineering and Management, 02(03), 1-7. https://doi.org/10.55041/isjem00215

Reichenpfader, D., Müller, H., & Denecke, K. (2023). Large language model-based information extraction from free-text radiology reports: a scoping review protocol. https://doi.org/10.1101/2023.07.28.23292031

Cinquin, O. (2024). ChIP-GPT: a managed large language model for robust data extraction from biomedical database records. Briefings in Bioinformatics, 25(2), bbad535. https://doi.org/10.1093/bib/bbad535

Amel Abdyssalam A Alhaag (2025). Comparison between Database Search Algorithms (SQL and no SQL). مجلة العلوم الشاملة, 9(ملحق 36), 1810-1830. https://doi.org/10.65405/bc8atc11

Shi, L., Tang, Z., Zhang, N., Zhang, X., & Yang, Z. (2026). A Survey on Employing Large Language Models for Text-to-SQL Tasks. ACM Computing Surveys, 58(2), 1-37. https://doi.org/10.1145/3737873

Putra, C., Arlis, S., & Nurcahyo, G. W. (2025). Large Language Model Method as a Translator Indonesian Into SQL Language. Jurnal KomtekInfo, 124-130. https://doi.org/10.35134/komtekinfo.v12i3.658

ŞAHİNASLAN, E., & ŞAHİNASLAN, Ö. (2022). Microsoft SQL Sunucusunda Veritabanı Kurtarma Teknikleri. International Journal of Innovative Engineering Applications, 6(1), 158-169. https://doi.org/10.46460/ijiea.1070325