<div class="csl-bib-body">
<div class="csl-entry">Frieder, S., Berner, J., Petersen, P., & Lukasiewicz, T. (2023). Large Language Models for Mathematicians. <i>Internationale Mathematische Nachrichten</i>, <i>254</i>, 1–20. http://hdl.handle.net/20.500.12708/192474</div>
</div>
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dc.identifier.issn
0020-7926
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/192474
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dc.description.abstract
Large language models (LLMs) such as CHATGPT have received immense in terest 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 mathe maticians. 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 LMMs to change how mathematicians work.
en
dc.language.iso
en
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dc.relation.ispartof
Internationale Mathematische Nachrichten
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dc.subject
large language models
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dc.subject
ChatGPT
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dc.subject
mathematics
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dc.title
Large Language Models for Mathematicians
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dc.type
Article
en
dc.type
Artikel
de
dc.contributor.affiliation
University of Oxford, United Kingdom of Great Britain and Northern Ireland (the)