Arctic-Text2SQL-R1: Simple Rewards, Strong Reasoning in Text-to-SQL

Understand

Translating natural language into SQL (Test2SQL) is a longstanding challenge at the intersection of natural language understanding and structured data access.

• While large language models (LLMs) have significantly improved fluency in SQL generation, producing correct and executable SQL--particularly for complex queries--remains a bottleneck.
• We present Arctic-Text2SQL-R1, a reinforcement learning (RL) framework and model family designed to generate accurate, executable SQL using a lightweight reward signal based solely on execution correctness.
• Our approach avoids brittle intermediate supervision and complex reward shaping, promoting stable training and alignment with the end task.