3 papers
cs.LG2025
ConstrainedSQL: Training LLMs for Text2SQL via Constrained Reinforcement Learning
Weiqin Chen, Nhan Huu Pham, Michael Robert Glass +4
Reinforcement learning (RL) has demonstrated significant promise in enhancing the reasoning capabilities of Text2SQL LLMs, especially with advanced algorithms such as GRPO and DAPO…
cs.CL2025
Rationalization Models for Text-to-SQL
Gaetano Rossiello, Nhan Pham, Michael Glass +2
We introduce a framework for generating Chain-of-Thought (CoT) rationales to enhance text-to-SQL model fine-tuning. These rationales consist of intermediate SQL statements and expl…
cs.DB2025
Extractive Schema Linking for Text-to-SQL
Michael Glass, Mustafa Eyceoz, Dharmashankar Subramanian +3
Text-to-SQL is emerging as a practical interface for real world databases. The dominant paradigm for Text-to-SQL is cross-database or schema-independent, supporting application sch…