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PLForge: Enhancing Language Models for Natural Language to Procedural Extensions of SQL

Summary: Defines NL-to-PL/SQL to target procedural, multi-statement PL/SQL generation that Text-to-SQL models neglect. Introduces PLForge (3/7/15B) via PL/SQL-centric incremental pretraining, custom prompting and synthetic NL–PL/SQL data, improving execution- and exact-match vs. baselines. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
7599
Venue
SIGMOD
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,389 | 28.73%
DOI
10.1145/3769813

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BibTeX Citation

@inproceedings{zhang_sigmod26,
        title = {{PLForge: Enhancing Language Models for Natural Language to Procedural Extensions of SQL}},
        author = {Zhang, Hang and Wang, Chaokun and Li, Hongwei and Wu, Cheng and Wang, Songyao and Liu, Yabin and Shi, Gengyuan and Liu, Ziyang},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3769813},
        url = {https://dl.acm.org/doi/10.1145/3769813},
        year = {2026}
}

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