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EvoSQL framework enhances Text-to-SQL with critic-generator co-evolution

By PulseAugur Editorial · [1 sources] ·

Researchers have developed EvoSQL, a novel framework designed to enhance Text-to-SQL capabilities by treating SQL synthesis as an iterative process between a generator and a critic. This system incorporates a memory component to store and verify SQL candidates, utilizing both execution signals and LLM-based critique for refinement. EvoSQL also includes a Self-Distillation Policy Optimization (SDPO) stage to fine-tune coding LLMs with execution-aware supervision, demonstrating significant improvements on benchmark datasets like Spider and BIRD, particularly for open-source models such as Qwen3-4B and Qwen2.5-Coder-3B. AI

IMPACT This research could lead to more reliable and generalizable Text-to-SQL systems, improving how users interact with databases through natural language.

RANK_REASON The cluster describes a new research paper detailing a novel framework for Text-to-SQL systems. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

EvoSQL framework enhances Text-to-SQL with critic-generator co-evolution

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The cluster describes a new research paper detailing a novel framework for Text-to-SQL systems. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jiawei Zhou, Jianwei Wang, Chenyu Zhou, Chaojian Shi, Ming Dong, Kai Wang ·

    EvoSQL: Memory-Augmented Critic-Generator Co-Evolution for Text-to-SQL

    arXiv:2607.20489v1 Announce Type: new Abstract: 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…

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