ReToolSQL: Agentic Reinforcement Learning for Robust Text-to-SQL
ReToolSQL is presented, a two-stage training framework for text-to-SQL that combines a supervised warm-start on rejection-sampled reasoning traces with agentic reinforcement fine-tuning (RFT) over multi-turn tool-use trajectories and shows that a properly designed SFT$\to-RFT pipeline over tool-use trajectories is a practical path toward robust enterprise-grade text-to-SQL.
Pratik Kakkar, Chandra Dhir, Ravi Shankar et al.
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