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Computer Science > Machine Learning

arXiv:2203.16569 (cs)
[Submitted on 30 Mar 2022]

Title:Generating Scientific Articles with Machine Learning

Authors:Eliot H. Ayache, Conor M.B. Omand
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Abstract:In recent years, the field of machine learning has seen rapid growth, with applications in a variety of domains, including image recognition, natural language processing, and predictive modeling. In this paper, we explore the application of machine learning to the generation of scientific articles. We present a method for using machine learning to generate scientific articles based on a data set of scientific papers. The method uses a machine-learning algorithm to learn the structure of a scientific article and a set of training data consisting of scientific papers. The machine-learning algorithm is used to generate a scientific article based on the data set of scientific papers. We evaluate the performance of the method by comparing the generated article to a set of manually written articles. The results show that the machine-generated article is of similar quality to the manually written articles.
Comments: Happy April Fools!
Subjects: Machine Learning (cs.LG)
Cite as: arXiv:2203.16569 [cs.LG]
  (or arXiv:2203.16569v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2203.16569

Submission history

From: Eliot Ayache [view email]
[v1] Wed, 30 Mar 2022 18:01:04 UTC (917 KB)
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