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Can LLM generate interesting mathematical research problems?

arXiv cs.AI / 3/20/2026

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Key Points

  • The paper is the second in a series examining the mathematical creativity of LLMs and builds on prior criteria and benchmarks for evaluation.
  • It develops an agent to generate unknown mathematical problems and reports producing 665 differential geometry problems.
  • Human verification indicates many generated problems were unknown to experts, suggesting potential novelty and research value.
  • The results imply LLMs can contribute to generating valuable research questions, potentially accelerating mathematical discovery.
  • The work provides a benchmark dataset and an evaluation framework for assessing AI-generated mathematical problems.

Abstract

This paper is the second one in a series of work on the mathematical creativity of LLM. In the first paper, the authors proposed three criteria for evaluating the mathematical creativity of LLM and constructed a benchmark dataset to measure it. This paper further explores the mathematical creativity of LLM, with a focus on investigating whether LLM can generate valuable and cutting-edge mathematical research problems. We develop an agent to generate unknown problems and produced 665 research problems in differential geometry. Through human verification, we find that many of these mathematical problems are unknown to experts and possess unique research value.