OpenAI is collaborating with an independent Advisory Group on Mathematics and Artificial Intelligence. The group’s role is to guide the review and communication of emerging AI results. This partnership aims to ensure rigorous oversight and clear dissemination of new developments in AI.
arXiv:2609. 25050v1 Announce Type: new Abstract: We introduce FrontierMath Erd\H{o}s (FME), a benchmark of 68 Erd\H{o}s problems that are open as of August 2026.
By Tom Adamczewski (Epoch AI), Thomas F. Bloom (University of Manchester)
OpenAI shares new results on long-standing open problems in mathematics and theoretical computer science, including advances in geometry, cryptography, and complexity.
arXiv:2610.09769v1 Announce Type: cross
Abstract: Large language models are increasingly contributing to mathematical research, where progress often depends on efficient proof search, incremental imp...
By Adri\'an Z\'ame\v{c}n\'ik, Mat\v{e}j Kripner, Martin Kouteck\'y, Martin Balko, Jan Greb\'ik, Pavel Hub\'a\v{c}ek, Robert \v{S}\'amal, V\'aclav Rozho\v{n}
OpenProblemBench is a new benchmark that presents 82 unresolved problems from mathematics and theoretical physics, each with detailed context, assumptions, and prior progress. The benchmark evaluates AI submissions on correctness, completeness, and progress using four independent evaluator models, without providing reference solutions. GPT‑6‑Astra achieved the highest mean judged solve rate of 14.0%, outperforming other evaluated models, and the study links stronger outcomes to improved problem representation, general reasoning, and proof steps.
By Zhiyi Li, Sihan Hu, Tianning Xiao, Xiansheng Cai, Xiaojun Tan, Youjin Deng, Kun Chen
In this video, we share how the o1 reasoning models can help in domains like coding, strategy, and research.
arXiv:2603. 02668v2 Announce Type: replace Abstract: We present SorryDB, a dynamically-updating benchmark of open Lean tasks drawn from 78 real world formalization projects on GitHub.
By Austin Letson, Leopoldo Sarra, Auguste Poiroux, Oliver Dressler, Paul Lezeau, Dhyan Aranha, Frederick Pu, Aaron Hill, Miguel Corredera Hidalgo, Julian Berman, George Tsoukalas, Lenny Taelman
arXiv:2608.28433v2 Announce Type: replace
Abstract: Proof assistants such as Lean 4 promise the paradigm of formally verified mathematics, but large-scale formalization projects have faced major barr...
By Shuze Chen, Kunal Marwaha, Xiaoyang Lu, Henry Yuen, Tianyi Peng
We’re releasing an API for accessing new AI models developed by OpenAI.
An OpenAI model solved the 80-year-old unit distance problem, disproving a major conjecture in discrete geometry and marking a milestone in AI-driven mathematics.
arXiv:2605. 22763v2 Announce Type: replace Abstract: Large language models (LLMs) increasingly excel at mathematical reasoning, but their unreliability limits their utility in mathematics research.
By George Tsoukalas, Anton Kovsharov, Sergey Shirobokov, Anja Surina, Moritz Firsching, Gergely B\'erczi, Francisco J. R. Ruiz, Arun Suggala, Adam Zsolt Wagner, Eric Wieser, Lei Yu, Aja Huang, Mikl\'os Z. Horv\'ath, Andrew Ferraiuolo, Henryk Michalewski, Edward Lockhart, Codrut Grosu, Thomas Hubert, Matej Balog, Pushmeet Kohli, Swarat Chaudhuri
OpenAI’s latest line of reasoning models will be used by nation’s leading scientists to drive scientific breakthroughs.