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English(EN) SWE-rebench V2: Language-Agnostic SWE Task Collection at Scale

SWE-rebench V2 扩展软件工程代理的训练数据

研究人员推出了 SWE-rebench V2,这是一个旨在为训练软件工程代理创建大规模、语言无关数据集的新管道。该系统自动化了从真实软件存储库中收集可执行任务的过程,生成可复现的执行环境和测试套件。该管道利用交互式设置代理和 LLM 裁判来过滤和验证任务,生成了跨越 20 种编程语言的 32,000 多个任务的数据集,并额外发布了 120,000 多个任务用于进一步训练。 AI

影响 为生成多样化的训练数据以改进软件工程 AI 代理提供了一种可扩展的方法。

排序理由 这是一篇描述用于训练 AI 代理的新数据集和管道的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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

SWE-rebench V2 扩展软件工程代理的训练数据

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这是一篇描述用于训练 AI 代理的新数据集和管道的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Ibragim Badertdinov, Maksim Nekrashevich, Anton Shevtsov, Alexander Golubev ·

    SWE-rebench V2:大规模语言无关的SWE任务集

    arXiv:2602.23866v2 Announce Type: replace-cross Abstract: Software engineering agents (SWE) are improving rapidly, with recent gains largely driven by reinforcement learning (RL). However, RL training is constrained by the scarcity of large-scale task collections with reproducibl…