# Generating Scientific Articles with Machine Learning

arXiv: https://arxiv.org/abs/2203.16569 · HTML: https://mlsanity.com/paper/2203.16569/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 4 references that are in the map.
- First posted on arXiv 30 Mar 2022.

## Built on by (most cited first, 1 of 1)

- [AINL-Eval 2025 Shared Task: Detection of AI-Generated Scientific Abstracts in Russian](https://mlsanity.com/paper/2508.09622/) (2025)

## Abstract (arXiv)

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.