Paper#Text-to-SQL, Semantic Validation, Natural Language Processing, AI🔬 ResearchAnalyzed: Jan 3, 2026 19:39
Hierarchical Representation for Semantic Validation in Text-to-SQL
Published:Dec 28, 2025 02:25
•1 min read
•ArXiv
Analysis
This paper addresses the critical problem of semantic validation in Text-to-SQL systems, which is crucial for ensuring the reliability and executability of generated SQL queries. The authors propose a novel hierarchical representation approach, HEROSQL, that integrates global user intent (Logical Plans) and local SQL structural details (Abstract Syntax Trees). The use of a Nested Message Passing Neural Network and an AST-driven sub-SQL augmentation strategy are key innovations. The paper's significance lies in its potential to improve the accuracy and interpretability of Text-to-SQL systems, leading to more reliable data querying platforms.
Key Takeaways
- •Proposes HEROSQL, a hierarchical approach for semantic validation in Text-to-SQL.
- •Integrates global intent (Logical Plans) and local details (Abstract Syntax Trees).
- •Employs a Nested Message Passing Neural Network for information propagation.
- •Uses an AST-driven sub-SQL augmentation strategy for robust optimization.
- •Achieves state-of-the-art performance on Text-to-SQL validation benchmarks.
Reference
“HEROSQL achieves an average 9.40% improvement of AUPRC and 12.35% of AUROC in identifying semantic inconsistencies.”