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

arXiv 2604.21414 ↗First posted 23 Apr 2026cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 43 of its 52 references that are in the map. First posted on arXiv 23 Apr 2026.

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31 more

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