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arXiv · 2604.21414

SemanticAgent: A Semantics-Aware Framework for Text-to-SQL Data Synthesis

Qiang Gao·Zhenping Li·Anqi Zhuo·Yingxiao Zhao·Weibo Geng·Xiaosong Li
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Abstract

Existing text-to-SQL synthesis pipelines still conflate executability with semantic validity: syntactic checks and execution-based validation can retain queries that execute successfully while violating database semantics. To address these limitations, we propose SemanticAgent, a semantic-aware synthesis framework. SemanticAgent organizes synthesis around three specialized modules: an analyzer, a synthesizer, and a verifier. Through a three-stage protocol of semantic analysis, stepwise synthesis, and diagnostic refinement, SemanticAgent transforms execution-based validation alone into a traceable reasoning process. Our framework generates synthetic data that consistently outperforms prior synthesis methods under semantic-quality evaluation, leading to stronger downstream fine-tuning performance, especially on semantically demanding benchmarks.

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Qiang Gao, Zhenping Li, Anqi Zhuo, Yingxiao Zhao, Weibo Geng, Xiaosong Li. 2026-04-23. SemanticAgent: A Semantics-Aware Framework for Text-to-SQL Data Synthesis. https://arxiv.org/abs/2604.21414

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