EvoSQL: Memory-Augmented Critic-Generator Co-Evolution for Text-to-SQL
Text-to-SQL has advanced rapidly with large language models, but complex database queries still require reasoning beyond one-shot generation, including multi-step decomposition, execution-based diagnosis, and targeted correction. We present EvoSQL, a co-evolution framework that formulates SQL synthesis as an iterative interaction between a generator and a critic. EvoSQL maintains a contextualized candidate memory, verifies SQL candidates with both execution signals and LLM-based critique, and updates its memory through utility-guided aggregation. To strengthen the underlying generator-critic pair, we further introduce a Self-Distillation Policy Optimization (SDPO) fine-tuning stage that i...
| Authors | Jiawei Zhou, Jianwei Wang, Chenyu Zhou et al. |
|---|---|
| Primary category | cs.AI |
| Published | 4 June 2026 |
| Last updated at source | 29 August 2026 |
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