[2604.07041] AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views

Computer Science > Databases arXiv:2604.07041 (cs) [Submitted on 8 Apr 2026] Title:AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views Authors:Minh Tam Pham, Trinh Pham, Tong Chen, Hongzhi Yin, Quoc Viet Hung Nguyen, Thanh Tam Nguyen View a PDF of the paper titled AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views, by Minh Tam Pham and 5 other authors View PDF HTML (experimental) Abstract:Text-to-SQL is the task of translating natural language queries into executable SQL for a given database, enabling non-expert users to access structured data without writing SQL manually. Despite rapid advances driven by large language models (LLMs), existing approaches still struggle with complex queries in real-world settings, where database schemas are large and questions require multi-step reasoning over many interrelated tables. In such cases, providing the full schema often exceeds the context window, while one-shot generation frequently produces non-executable SQL due to syntax errors and incorrect schema linking. To address these challenges, we introduce AV-SQL, a framework that decomposes complex Text-to-SQL into a pipeline of specialized LLM agents. Central to AV-SQL is the concept of agentic views: agent-generated Common Table Expressions (CTEs) that encapsulate intermediate query logic and filter relevant schema elements from large schemas. AV-SQL operates in three stages: (1) a rewriter agent compresses and clarifies the input query; (2) a view ...