DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation
Prompting-based (i.e., non-fine-tuning) Text-to-SQL methods, where underlying large language model parameters are not changed for the task, face three problems: (i) relying on coarse-grained schema information that may not reveal the fine-grained relationships needed to distinguish ambiguous columns, (ii) failing to capture recurring SQL-generation failures, and (iii) suffering from omission or hallucination of components in complex questions. This paper develops DexterSQL, a prompting/non-fine-tuning-based Text-to-SQL system that improves SQL generation with three novel components: (i) deep schema explorator that identifies ambiguous columns, analyzes their individual and joint data dist...
| Authors | Anik Pramanik, Murat Kantarcioglu, Vincent Oria et al. |
|---|---|
| Primary category | cs.DB |
| Published | 12 August 2026 |
| Last updated at source | 8 September 2026 |
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