Recent large language models (LLMs) can generate and revise text with
human-level performance, and have been widely commercialized in systems like
ChatGPT. These models come with clear limitations: they can produce inaccurate
information, reinforce existing biases, and be easily misused. Yet, many
scientists have been using them to assist their scholarly writing. How
wide-spread is LLM usage in the academic literature currently? To answer this
question, we use an unbiased, large-scale approach, free from any assumptions
on academic LLM usage. We study vocabulary changes in 14 million PubMed
abstracts from 2010-2024, and show how the appearance of LLMs led to an abrupt
increase in the frequency of certain style words. Our analysis based on excess
words usage suggests that at least 10% of 2024 abstracts were processed with
LLMs. This lower bound differed across disciplines, countries, and journals,
and was as high as 30% for some PubMed sub-corpora. We show that the appearance
of LLM-based writing assistants has had an unprecedented impact in the
scientific literature, surpassing the effect of major world events such as the
Covid pandemic.

LLM 的出现对科学文献产生了前所未有的影响，超过了像 Covid 大流行等重大世界事件的影响，至少有 10% 的 2024 篇摘要使用了 LLMs 处理。

通过过多词汇探索 ChatGPT 在学术写作中的应用

Delving into ChatGPT usage in academic writing through excess vocabulary

Individuality and personalization comprise the distinctive characteristics
that make each writer unique and influence their words in order to effectively
engage readers while conveying authenticity. However, our growing reliance on
LLM-based writing assistants risks compromising our creativity and
individuality over time. We often overlook the negative impacts of this trend
on our creativity and uniqueness, despite the possible consequences. This study
investigates these concerns by performing a brief survey to explore different
perspectives and concepts, as well as trying to understand people's viewpoints,
in conjunction with past studies in the area. Addressing these issues is
essential for improving human-computer interaction systems and enhancing
writing assistants for personalization and individuality.

个性化与个性化组成了使每个作者独特的特征，影响他们的文字以有效地吸引读者并传达真实性。然而，我们对基于 LLM 的写作助手的依赖日益增长，却可能在时间上妥协了我们的创造力和个性。本研究通过进行简要调查，以探索不同观点和概念，并尝试理解人们的观点，结合在该领域的过去研究，来研究这些问题。解决这些问题对于改进人机交互系统和提高个性化与个人特有的写作助手至关重要。