A PPO-based RL framework with execution-aware dense rewards and token-level mapping improves pass@1 by 19% on MBPP and reduces execution failures by 51% on RoboEval for LLM code generation.
OpenCodeInstruct : A large-scale instruction tuning dataset for code LLMs , 2025
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Domain-Adaptable Reinforcement Learning for Code Generation with Dense Rewards
A PPO-based RL framework with execution-aware dense rewards and token-level mapping improves pass@1 by 19% on MBPP and reduces execution failures by 51% on RoboEval for LLM code generation.