ChatGPT outperforms crowd workers for text-annotation tasks

Many NLP applications require manual text annotations for a variety of tasks, notably to train classifiers or evaluate the performance of unsupervised models. Depending on the size and degree of complexity, the tasks may be conducted by crowd workers on platforms such as MTurk as well as trained ann...

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Vydané v:	Proceedings of the National Academy of Sciences - PNAS Ročník 120; číslo 30; s. e2305016120
Hlavní autori:	Gilardi, Fabrizio, Alizadeh, Meysam, Kubli, Maël
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 25.07.2023
Predmet:	human annotations large language models text classification ChatGPT text as data
ISSN:	1091-6490, 1091-6490
On-line prístup:	Zistit podrobnosti o prístupe
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