Explanations, Prompts, and Formalizations: Arguments for New Norms in LLM-Enabled Mathematical Research
Year: 2026
Type: preprint
Abstract: As several mathematical conjectures have recently been settled using large language models (LLMs), the mathematical community has formulated norms and recommendations regarding the publishing of such results. These norms do not cover the disclosure of the prompts and precise software setup used to obtain those results, nor do they require that results be formalized in a manner that allows for machine verification. I argue that both of these are essential. In addition, since LLM-obtained results may be hard to understand, human authors have the responsibility to invent intuitive explanations.
Source: arXiv (Cornell University)
Author: Boldt, Axel
Institution: Metropolitan State University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7204869168