DTS-SQL: Decomposed Text-to-SQL with Small Large Language Models

• URL: http://arxiv.org/abs/2402.01117v1
• Date: Fri, 2 Feb 2024 03:21:00 GMT
• Title: DTS-SQL: Decomposed Text-to-SQL with Small Large Language Models
• Authors: Mohammadreza Pourreza and Davood Rafiei
• Abstract summary: We introduce a novel two-stage fine-tuning approach that decomposes the task into two simpler tasks. We show that this approach improves execution accuracy by 3 to 7 percent.
• Score: 7.388002745070808
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Leading models for the text-to-SQL task heavily rely on proprietary Large Language Models (LLMs), posing concerns over data privacy. Closing the performance gap between small open-source models and large proprietary models is crucial to mitigate this reliance. To this end, we introduce a novel two-stage fine-tuning approach that decomposes the task into two simpler tasks. Through comprehensive evaluation on two large cross-domain datasets and two small LLMs, we show that this approach improves execution accuracy by 3 to 7 percent, effectively aligning the performance of open-source models with their proprietary counterparts.

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