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English(EN) CodeLift: Your Test Suite Is Secretly a Dense SWE Curriculum

CodeLift 方法将测试套件转化为密集的软件工程代理课程

研究人员开发了 CodeLift,一种旨在增强软件工程代理训练的新型强化学习方法。该方法通过动态校准通过率奖励来解决标准二元奖励系统的局限性,有效地将测试套件转化为自适应课程。CodeLift 对测试和补丁进行分组,以关注具有挑战性的方面,提供比传统方法更密集、更稳定的学习信号。在软件工程基准上的实验表明,CodeLift 在通过率方面比现有基线有持续的改进。 AI

影响 提高了专注于软件工程任务的 AI 代理的训练效率。

排序理由 详细介绍一种新 AI 代理训练方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

CodeLift 方法将测试套件转化为密集的软件工程代理课程

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详细介绍一种新 AI 代理训练方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Junjielong Xu, Huachao Zhu, Alyssa Wu, Zhichao Hu, Pinjia He ·

    CodeLift: Your Test Suite Is Secretly a Dense SWE Curriculum

    arXiv:2610.17224v2 Announce Type: replace Abstract: The pass-all-test binary reward has become a standard recipe for training software engineering agents, but its sparsity eliminates difference of partially correct patches. The test pass-rate is a natural alternative. However, we…