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English(EN) Are AI Coders Snitches? An Empirical Study of Pretraining Data Detection on Code Large Language Models

研究探讨 AI 代码模型训练数据检测的有效性

一项发表在 arXiv 上的新研究调查了代码大型语言模型(CodeLLMs)的训练数据检测(TDD)方法的有效性。研究人员引入了 CodeSnitch,一个包含 9,000 个跨三种编程语言的代码样本的基准数据集,用于评估七种最先进的 TDD 技术。该研究还根据 Type-1 到 Type-4 克隆检测分类法,测试了这些方法对代码变异的鲁棒性。 AI

影响 这项研究旨在通过改进检测专有训练数据使用情况的方法,来促进代码生成模型的负责任部署。

排序理由 该集群包含一篇学术论文,详细介绍了新的基准数据集和关于 AI 模型训练数据检测的实证研究。[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 →

研究探讨 AI 代码模型训练数据检测的有效性

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该集群包含一篇学术论文,详细介绍了新的基准数据集和关于 AI 模型训练数据检测的实证研究。[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) · Tianlin Li, Yunxiang Wei, Zhiming Li, Aishan Liu, Qing Guo, Xianglong Liu, Dongning Sun, Yang Liu ·

    AI 编码员是告密者吗?预训练数据在代码大语言模型上的检测实证研究

    arXiv:2507.17389v2 Announce Type: replace-cross Abstract: Recent advances in code large language models (CodeLLMs) have made them indispensable tools in modern software engineering. However, these models occasionally produce outputs that contain proprietary or sensitive code snip…