GAGAR Framework for Quality-Aware Credit Redistribution in Code Agent RL
September 25, 2026
GAGAR uses an SFT-trained agentic grader to redistribute advantages within rollout groups, preventing identical rewards for different implementation qualities. This allows RL to distinguish between passing code that is clean and passing code that is out-of-scope.
HOW THIS AFFECTS YOU
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builderThis could improve the reliability and code quality of agentic coding tools.
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researcherYou can use agentic grading to move beyond binary executable rewards in RL training.