Query and Conquer: Execution-Guided SQL Generation
We propose a novel approach for generating complex outputs that significantly
improves accuracy in text-to-SQL tasks. Our method leverages execution results
to select the most semantically consistent query from multiple candidates,
enabling smaller, cost-effective models to surpass computationally intensive
reasoning methods such as o1, o3-mini, and DeepSeek R1 while reducing inference
cost by as much as 30 times. It integrates effortlessly with existing models,
offering a practical and scalable pathway to state-of-the-art SQL generation.
67eb6e6088a08fae617860f3
Łukasz Borchmann
extracted_confirmed
2025-04-01T05:01:23.216Z
600b381d3cc3b87db94bc0ce
https://cdn-avatars.huggingface.co/v1/production/uploads/600b381d3cc3b87db94bc0ce/I3xpr4gzcG1uXawXBpWpD.jpeg
Łukasz Borchmann
user
Borchmann
67eb6e6088a08fae617860f4
Marek Wydmuch
admin_assigned
2025-04-01T08:01:57.075Z
66c5e93e8f14c260be9d9f63
/avatars/f4bf15e23923ef3256d3f01a3278d8bc.svg
Marek Wydmuch
user
sfc-mwydmuch
Query and Conquer: Execution-Guided SQL Generation
We propose a novel approach for generating complex outputs that significantly
improves accuracy in text-to-SQL tasks. Our method leverages execution results
to select the most semantically consistent query from multiple candidates,
enabling smaller, cost-effective models to surpass computationally intensive
reasoning methods such as o1, o3-mini, and DeepSeek R1 while reducing inference
cost by as much as 30 times. It integrates effortlessly with existing models,
offering a practical and scalable pathway to state-of-the-art SQL generation.
A novel approach selects semantically consistent SQL queries using execution results, outperforming complex reasoning methods with reduced computational cost.
text-to-SQL semantically consistent query DeepSeek inference cost