This content originally appeared on DEV Community and was authored by Mike Young
This is a Plain English Papers summary of a research paper called SQL Query Generation Gets 10.6% More Accurate with New Execution-Guided Approach. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
Overview
- SQL generation for natural language queries remains challenging
- New execution-guided approach helps models learn from query feedback
- Uses generated query execution results to refine SQL output
- Introduces minimum Bayes risk (MBR) decoding for SQL
- Improves accuracy on Spider benchmark by up to 10.6%
- Provides valuable feedback to models on SQL correctness
- Compatible with both closed and open-source LLMs
Plain English Explanation
Imagine trying to teach someone a language by only showing them the final result of what they're trying to say. That's essentially how most text-to-SQL generation models learn - they need to figure out the r...
Click here to read the full summary of this paper
This content originally appeared on DEV Community and was authored by Mike Young
Mike Young | Sciencx (2025-04-01T14:17:48+00:00) SQL Query Generation Gets 10.6% More Accurate with New Execution-Guided Approach. Retrieved from https://www.scien.cx/2025/04/01/sql-query-generation-gets-10-6-more-accurate-with-new-execution-guided-approach/
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