I have a preprint out estimating how many scholarly papers are written using chatGPT etc? I estimate upwards of 60k articles (>1% of global output) published in 2023. https://arxiv.org/abs/2403.16887

How can we identify this? Simple: there are certain words that LLMs love, and they suddenly start showing up *a lot* last year. Twice as many papers call something "intricate", big rises for "commendable" and "meticulous".

#bibliometrics #scholcomm #chatgpt

ChatGPT "contamination": estimating the prevalence of LLMs in the scholarly literature

The use of ChatGPT and similar Large Language Model (LLM) tools in scholarly communication and academic publishing has been widely discussed since they became easily accessible to a general audience in late 2022. This study uses keywords known to be disproportionately present in LLM-generated text to provide an overall estimate for the prevalence of LLM-assisted writing in the scholarly literature. For the publishing year 2023, it is found that several of those keywords show a distinctive and disproportionate increase in their prevalence, individually and in combination. It is estimated that at least 60,000 papers (slightly over 1% of all articles) were LLM-assisted, though this number could be extended and refined by analysis of other characteristics of the papers or by identification of further indicative keywords.

arXiv.org
@generalising Any idea why LLMs like those words so much, if they don't show up with those frequencies in the training data?
@robinadams @generalising Probably to do with RLHF, the step after initial training where they are "humanised" into having a "personality". You can play with base models on openai playground if you have a dev account, and its fun to see the difference in usability and style from RLHF