Large Language Models for Mathematicians
This addresses the problem of enhancing productivity and quality in mathematics, but it is incremental as it reviews existing studies without introducing new methods or data.
The paper examines the potential of large language models (LLMs) to assist professional mathematicians by discussing their mathematical abilities, best practices, and issues, and explores how LLMs could transform mathematical work.
Large language models (LLMs) such as ChatGPT have received immense interest for their general-purpose language understanding and, in particular, their ability to generate high-quality text or computer code. For many professions, LLMs represent an invaluable tool that can speed up and improve the quality of work. In this note, we discuss to what extent they can aid professional mathematicians. We first provide a mathematical description of the transformer model used in all modern language models. Based on recent studies, we then outline best practices and potential issues and report on the mathematical abilities of language models. Finally, we shed light on the potential of LLMs to change how mathematicians work.