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'The Gold Rush in AI4Math': substantive AI use in arXiv math papers rises from 1.4% to 14% in five months

★★★after cutoffresearchJiashun JinZheng Tracy KeBingcheng Suiconfidence: high

A survey of 32,944 arXiv mathematics submissions (1 Mar – 20 Aug 2026) found 1,712 papers where AI made a substantive mathematical contribution. Their share rose from 1.39% in March to 14.09% by 20 August. Of 717 open-problem records, 510 were reported fully resolved (329 proofs, 181 disproofs). Its Table 3 lists AI disproofs of long-standing combinatorics conjectures such as Rota's conjecture for flats (1970).

Key facts

What happened

Statisticians Jiashun Jin, Zheng Tracy Ke and Bingcheng Sui classified AI disclosures in six months of arXiv math preprints. They catalogued the open problems those papers claim to settle.

Why it matters

It is one of the first quantitative measures of how fast AI entered research mathematics in 2026: roughly a tenfold rise in substantive use within one semester. It also shows that most AI-resolved "open problems" are lesser-known conjectures, not headline ones.

Changelog

  • 2026-09-29: created

Related events

  1. OpenAI says an internal model resolved 100+ long-standing open problems in 24 days of training; no list released ★★★
  2. Fields Medallists' open letter 'A Severe Misalignment of AI in Mathematics' criticises labs' race for famous problems ★★★

Sources (1)

id: 2026-08-25-gold-rush-ai4math-survey · updated 2026-09-29 · open in the interactive timeline