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Generating Scientific Articles with Machine Learning

Authors :
Ayache, Eliot H.
Omand, Conor M. B.
Publication Year :
2022

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.<br />Comment: Happy April Fools!

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2203.16569
Document Type :
Working Paper