Can LLM generate interesting mathematical research problems?
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866908901286346752 |
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| author | Chen, Xiaoyang Jiang, Xiang |
| author_facet | Chen, Xiaoyang Jiang, Xiang |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_18813 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Can LLM generate interesting mathematical research problems? Chen, Xiaoyang Jiang, Xiang Artificial Intelligence 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. |
| title | Can LLM generate interesting mathematical research problems? |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2603.18813 |