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.
Cotran: An llm-based code translator using reinforcement learning with feedback from compiler and symbolic execution
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Multi-stage LLM training plus compiler-guided error repair boosts functional equivalence in Java-to-Cangjie translation by 6.06% over prior methods despite scarce parallel data.
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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.
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Boosting Automatic Java-to-Cangjie Translation with Multi-Stage LLM Training and Error Repair
Multi-stage LLM training plus compiler-guided error repair boosts functional equivalence in Java-to-Cangjie translation by 6.06% over prior methods despite scarce parallel data.