Turning Database Grading into RL Rewards: Post-Training Agent

A research team introduced ThinkingBox-Training, a post-training method that converts database grading into executable RL rewards. By fine-tuning Qwen3.8-27B with GRPO for 50 steps on an offline-selected training pool, average task success increased from 51.70% to 60.78%, and tasks completed correctly on all twenty attempts rose from 38 to 107. The reward signal was built by comparing final database states with expected outcomes in ThinkingBox-Bench's 507 tasks, which provide real backends and tools. The training pool was constructed using offline policy-relative difficulty and kept fixed throughout the run.

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1. 110月23日 00:00收录于 10月23日 06:56单一来源有修订

   Turning Database Grading into RL Rewards: Post-Training Agen

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