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The Gold Rush in AI4Math: Where Are We Now? — arXiv:2608.24961

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.24961
License (as archived): CC0-1.0
Archived: 2026-10-18T01:27:30.830Z
SHA-256 of the archived text: 7829578a42d32f6aed42ef210d0aa33bdb0ff7d7d23e7bce529474ddc6d766ac
Stable URL of this page: https://metraipolis.com/documento/dc_ea792ceeb965

How to cite

The Gold Rush in AI4Math: Where Are We Now? — arXiv:2608.24961 — arXiv (en), https://arxiv.org/abs/2608.24961 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_ea792ceeb965 (Metraipolis archive dc_ea792ceeb965, sha256 7829578a42d32f6aed42ef210d0aa33bdb0ff7d7d23e7bce529474ddc6d766ac)

BibTeX

@misc{dcea792ceeb965,
  title = {The Gold Rush in AI4Math: Where Are We Now? — arXiv:2608.24961},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.24961},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_ea792ceeb965; sha256 7829578a42d32f6aed42ef210d0aa33bdb0ff7d7d23e7bce529474ddc6d766ac},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.24961. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Recent advances in artificial intelligence (AI) have sparked growing interest in its use for mathematical research. While some view this as a major opportunity for discovery, others have raised concerns about its impact on traditional research practices. Despite extensive debate, empirical evidence on how AI is actually being used in mathematics remains limited. To address this gap, we collected all 32,944 arXiv submissions posted between March 1 and August 20, 2026, whose primary or secondary categories included Mathematics. We identified 3,575 submissions that explicitly disclosed author use of AI, of which 1,712 involved at least one substantive mathematical contribution. Our analysis reveals several broad patterns. First, disclosed AI use increased sharply over the study period, with substantive use growing from 1.39% of Mathematics submissions in March to 14.09% through August 20. Second, substantive AI use is highly uneven across fields: Combinatorics has the largest number of such papers, while Metric Geometry has the highest substantive-use rate. Third, substantive AI use is geographically concentrated: under weighted author counts, the United States and China together account for about two-thirds of the recognized country weight. Fourth, AI is already being applied to open research problems: among 717 named open-problem records associated with substantive use, 71% are labeled as fully resolved based on the authors' descriptions, with proofs of the conjectured statement more common than counterexamples or disproofs. Finally, AI-system use is also highly concentrated, with OpenAI systems appearing most frequently, followed by Anthropic. Together, these findings suggest that AI-assisted mathematics is expanding rapidly but remains at an early and uneven stage of adoption.

Tema degli esploratori: ricerca e scienza aperta (retro-catalogo arXiv: annunci del 2026-08-27 in cs.DL).
Categorie arXiv: Applications (stat.AP) ; Computers and Society (cs.CY); Digital Libraries (cs.DL); History and Overview (math.HO).
Pagina del lavoro: https://arxiv.org/abs/2608.24961 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-18T01:27:21.258Z dalla pagina https://arxiv.org/catchup/cs.DL/2026-08-27?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).