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English(EN) CodeWalk: Generating Coding Benchmarks by Walking a Problem Graph

CodeWalk 通过组合现有问题来生成具有挑战性的编码基准

研究人员开发了一种名为 CodeWalk 的新颖方法,通过以编程方式组合现有问题来生成编码基准。这种方法绕过了昂贵的人工策划或语言模型生成和验证的需要。生成的任务已被证明对当前前沿模型具有挑战性,并且作为训练数据非常有效,展示了 Qwen3.5-9B 性能的提升。 AI

影响 这种方法可以显著降低创建具有挑战性基准的成本,从而可能加速 AI 模型在编码任务中的开发。

排序理由 该集群描述了一篇详细介绍生成编码基准的新颖方法的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

CodeWalk 通过组合现有问题来生成具有挑战性的编码基准

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该集群描述了一篇详细介绍生成编码基准的新颖方法的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jiaxin Fang, Runyuan He, Arnav Gupta, Sahil Kumawat, Huanzhi Mao, Alvin Cheung ·

    CodeWalk:通过遍历问题图生成编码基准

    arXiv:2610.15345v1 Announce Type: cross Abstract: High-quality coding problems are expensive to collect. Benchmarks such as SWE-bench rely on substantial human curation, while synthetic alternatives typically rely on costly model generation and validation. In this work, we show t…