APEX-SQL: Talking to the data via Agentic Exploration for Text-to-SQL
Text-to-SQL systems powered by Large Language Models have excelled on academic benchmarks but struggle in complex enterprise environments. The primary limitation lies in their reliance on static schema representations, which fails to resolve semantic ambiguity and scale effectively to large, complex databases. To address this, we propose APEX-SQL, an Agentic Text-to-SQL Framework that shifts the paradigm from passive translation to agentic exploration. Our framework employs a hypothesis-verification loop to ground model reasoning in real data. In the schema linking phase, we use logical planning to verbalize hypotheses, dual-pathway pruning to reduce the search space, and parallel data pr...
| Authors | Bowen Cao, Weibin Liao, Yushi Sun et al. |
|---|---|
| Primary category | cs.DB |
| Published | 11 February 2026 |
| Last updated at source | 31 May 2026 |
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