DexterSQL: A New Prompting-Based System for Text-to-SQL Generation
Researchers have developed DexterSQL, a prompting-based Text-to-SQL system that addresses three key problems in non-fine-tuning methods: reliance on coarse-grained schema information, failure to capture recurring SQL-generation errors, and issues with condition omission, hallucination, or misplacement in complex queries. The system introduces a deep schema explorator that identifies ambiguous columns and analyzes their individual and joint data distributions to understand relationships and distinct roles. Additionally, it includes a database-agnostic rule creator that mines mismatches between generated and gold SQL queries. The paper, available on arXiv (2608.11889), presents these components as novel contributions to improve SQL generation accuracy without altering underlying large language model parameters.
Key facts
- DexterSQL is a prompting-based Text-to-SQL system.
- It addresses three problems: coarse-grained schema, recurring failures, and condition issues.
- The deep schema explorator identifies ambiguous columns and analyzes data distributions.
- The database-agnostic rule creator mines mismatches between generated and gold SQL.
- The system does not fine-tune large language models.
- The paper is available on arXiv with ID 2608.11889.
- The system aims to improve SQL generation for complex questions.
- It is a non-fine-tuning method.
Entities
Institutions
- arXiv