Summary of Delving Into Chatgpt Usage in Academic Writing Through Excess Vocabulary, by Dmitry Kobak et al.
Delving into ChatGPT usage in academic writing through excess vocabulary
by Dmitry Kobak, Rita González-Márquez, Emőke-Ágnes Horvát, Jan Lause
First submitted to arxiv on: 11 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Digital Libraries (cs.DL); Social and Information Networks (cs.SI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The abstract presents a large-scale study on the use of Large Language Models (LLMs) in academic writing, specifically in PubMed abstracts from 2010-2024. The researchers used an unbiased approach to analyze vocabulary changes and found that LLMs led to an abrupt increase in the frequency of certain style words. They estimate that at least 10% of 2024 abstracts were processed with LLLMs, with varying levels across disciplines, countries, and journals. This study highlights the significant impact of LLMs on the scientific literature, surpassing major world events like the Covid pandemic. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models can generate text with human-level performance, but they have limitations. Scientists use them to write papers, but how common is this? The researchers looked at 14 million PubMed abstracts from 2010-2024 to find out. They analyzed vocabulary changes and found that LLMs caused an increase in certain words. At least 10% of 2024 abstracts might have been written with LLMs! This varies across fields, countries, and journals. |
