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Ling-Hao Zhang

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#machine learning Preprint Sep 2026

Groupwise Agentic Grading and Advantage Redistribution for Code Agent RL

Reinforcement learning (RL) for code agents often uses executable tests to provide binary rewards. With these rewards, Group Relative Policy Optimization (GRPO) assigns identical advantages to test-passing trajectories within each rollout group, overlooking differences in implementation quality and adherence to task re...

Jin-Hao Dong, Liang Zhao, Zi-Hao Yue et al. · 0 citations
#artificial intelligence Preprint Sep 2026

CodeMidas: Scaling Agentic Coding RL Environments from Code Itself

Training capable coding agents via reinforcement learning (RL) requires diverse tasks with reliable verifiers. Open-source codebases offer a rich source of such tasks, while existing methods typically rely on development artifacts such as issues and commits, limiting the range of tasks that can be extracted. To better...

Bo-Wen Ye, Lei Li, Shi-Cheng Li et al. · 0 citations

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