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A publishing infrastructure for AI-assisted academic authoring

In this work we investigate how models with advanced natural language processing capabilities can be used to reduce the time-consuming process of writing and revising scholarly manuscripts. To this end, we integrate large language models into the Manubot publishing ecosystem to suggest revisions for...

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Detalles Bibliográficos
Autores principales: Pividori, Milton, Greene, Casey S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900745/
https://www.ncbi.nlm.nih.gov/pubmed/36747665
http://dx.doi.org/10.1101/2023.01.21.525030
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author Pividori, Milton
Greene, Casey S.
author_facet Pividori, Milton
Greene, Casey S.
author_sort Pividori, Milton
collection PubMed
description In this work we investigate how models with advanced natural language processing capabilities can be used to reduce the time-consuming process of writing and revising scholarly manuscripts. To this end, we integrate large language models into the Manubot publishing ecosystem to suggest revisions for scholarly text. We tested our AI-based revision workflow in three case studies of existing manuscripts, including the present one. Our results suggest that these models can capture the concepts in the scholarly text and produce high-quality revisions that improve clarity. Given the amount of time that researchers put into crafting prose, we anticipate that this advance will revolutionize the type of knowledge work performed by academics.
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spelling pubmed-99007452023-02-07 A publishing infrastructure for AI-assisted academic authoring Pividori, Milton Greene, Casey S. bioRxiv Article In this work we investigate how models with advanced natural language processing capabilities can be used to reduce the time-consuming process of writing and revising scholarly manuscripts. To this end, we integrate large language models into the Manubot publishing ecosystem to suggest revisions for scholarly text. We tested our AI-based revision workflow in three case studies of existing manuscripts, including the present one. Our results suggest that these models can capture the concepts in the scholarly text and produce high-quality revisions that improve clarity. Given the amount of time that researchers put into crafting prose, we anticipate that this advance will revolutionize the type of knowledge work performed by academics. Cold Spring Harbor Laboratory 2023-01-23 /pmc/articles/PMC9900745/ /pubmed/36747665 http://dx.doi.org/10.1101/2023.01.21.525030 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Pividori, Milton
Greene, Casey S.
A publishing infrastructure for AI-assisted academic authoring
title A publishing infrastructure for AI-assisted academic authoring
title_full A publishing infrastructure for AI-assisted academic authoring
title_fullStr A publishing infrastructure for AI-assisted academic authoring
title_full_unstemmed A publishing infrastructure for AI-assisted academic authoring
title_short A publishing infrastructure for AI-assisted academic authoring
title_sort publishing infrastructure for ai-assisted academic authoring
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900745/
https://www.ncbi.nlm.nih.gov/pubmed/36747665
http://dx.doi.org/10.1101/2023.01.21.525030
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