Optimizing Large Language Models for Robust Domain-Specific Text-to-SQL: From Prompting to Preference Alignment

Noah Hampp, Katya Mirylenka, Michael Glass


Anthology ID:
2026.swisstext-1.5
Volume:
Proceedings of the 11th Edition of the Swiss Text Analytics Conference
Month:
June
Year:
2026
Address:
Zurich, Switzerland
Editors:
Rico Sennrich, Gerold Schneider, Tilia Ellendorff, Yingqiang Gao, Jannis Vamvas, Mark Cieliebak
Venue:
SwissText
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Publisher:
Association for Computational Linguistics
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Pages:
63–74
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URL:
https://preview.aclanthology.org/ingest-swisstext/2026.swisstext-1.5/
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Cite (ACL):
Noah Hampp, Katya Mirylenka, and Michael Glass. 2026. Optimizing Large Language Models for Robust Domain-Specific Text-to-SQL: From Prompting to Preference Alignment. In Proceedings of the 11th Edition of the Swiss Text Analytics Conference, pages 63–74, Zurich, Switzerland. Association for Computational Linguistics.
Cite (Informal):
Optimizing Large Language Models for Robust Domain-Specific Text-to-SQL: From Prompting to Preference Alignment (Hampp et al., SwissText 2026)
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https://preview.aclanthology.org/ingest-swisstext/2026.swisstext-1.5.pdf