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在科学论文中量化大型语言模型的使用情况.

Weixin Liang1, Yaohui Zhang2, Zhengxuan Wu3

  • 1Department of Computer Science, Stanford University, Stanford, CA, USA. wxliang@stanford.edu.

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此摘要是机器生成的。

大型语言模型 (LLM) 越来越多地用于科学写作. 对100多万篇论文的分析显示,LLM修改的数量稳步增加,特别是在计算机科学领域.

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科学领域:

  • 科学出版业的科学出版.
  • 学术写作学术写作
  • 研究传播研究传播.

背景情况:

  • 关于在学术写作中采用大型语言模型 (LLM) 的程度存在猜测.
  • 科学出版对于分享研究成果至关重要.

研究的目的:

  • 系统地分析科学论文中LLM修改内容的流行程度.
  • 随着时间的推移,跟踪学术写作中LLM使用的趋势和增长.

主要方法:

  • 分析了从2020年1月到2024年9月的1,121,912份预印稿和发表论文.
  • 利用基于单词频率转移的人口级框架来估计LLM修改.
  • 数据来源包括arXiv,bioRxiv和Nature投资组合期刊.

主要成果:

  • 在科学学科中观察到LLM使用量的稳步增加.
  • 计算机科学论文显示LLM修改的最大和最快的增长,高达22%.
  • 数学论文和"自然"杂志的投资组合显示了较低的LLM修改率 (高达9%).
  • 较高的LLM修改估计与第一作者频繁发布预印稿,拥挤的研究领域和较短的论文长度相关.

结论:

  • 在科学写作中,LLM正在被广泛采用和使用.
  • 这些发现突出了LLM在研究传播中整合的显著和不断增长的趋势.
  • 学科和作者特定因素影响科学出版物中LLM修改率.