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About this paper
Fernando Granado, Roberto Lotufo, Jayr Pereira
Researchers at Universidade Estadual de Campinas (UNICAMP) developed RAISE, a unified LLM agent that interactively explores databases using thought-based planning and tool use to generate SQL queries. This framework achieved 81.8% Best-of-N execution accuracy on the challenging BIRD dataset, matching state-of-the-art multi-stage pipelines with a simplified architecture.
Key insights
- A unified LLM agent with reasoning capabilities and tool use can effectively handle complex Text-to-SQL tasks, challenging the necessity of traditional multi-stage pipelines.
- Dynamic database exploration by the LLM provides substantially more value (an 11.7 percentage point improvement) than static query refinement alone, leading to improved accuracy.
- Scaling test-time computation through deeper interactive exploration (depth) rather than broader candidate generation (breadth) is a valuable strategy for resolving ambiguous or underspecified queries.
Summary by alphaXiv.
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