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English(EN) Code Comprehensor: Hierarchical Documentation and Cross-Modal Retrieval for Large Repositories

Code Comprehensor 框架增强 LLM 对大型代码库的理解

研究人员开发了 Code Comprehensor,一个旨在改进大型语言模型(LLM)理解和交互复杂代码库的新框架。该系统集成了代码依赖调用图(CodeGraph)、LLM 生成的分层文档(CodeScribe)以及用于文本-代码嵌入的 CLIP 式双编码器模型(CodeContrast)。在 OpenCV 等大型代码库上的评估表明,Code Comprehensor 显著提高了跨模态检索的准确性和忠实度,在 LLM 作为裁判的评估中得分超过 90%。 AI

影响 增强了 LLM 理解和交互大型代码库的能力,可能提高开发人员的生产力和代码维护效率。

排序理由 介绍代码理解新框架的研究论文。[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 →

Code Comprehensor 框架增强 LLM 对大型代码库的理解

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介绍代码理解新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Sujoy Roychowdhury, Joseph H. R. Isaac, Jiangning Gao, Martin Klitte, Diarmuid Corcoran ·

    Code Comprehensor:大型代码库的分层文档和跨模态检索

    arXiv:2610.30016v1 Announce Type: cross Abstract: Understanding large, complex, and rapidly evolving code bases remains a core challenge for software engineering at scale, hindering onboarding, maintenance, refactoring, and impact analysis. Providing this information to a Large-L…