RubricRefine is a training-free pre-execution method that creates rubrics to score and fix inter-tool contract violations in agent code, reaching 0.86 average on M3ToolEval across seven models with zero executions and lower latency.
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
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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RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement
RubricRefine is a training-free pre-execution method that creates rubrics to score and fix inter-tool contract violations in agent code, reaching 0.86 average on M3ToolEval across seven models with zero executions and lower latency.
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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.