OpenAI Blog
Feb 20
Our First Proof submissions
We share our AI model’s proof attempts for the First Proof math challenge, testing research-grade reasoning on expert-level problems.
Solving (some) formal math olympiad problems
We built a neural theorem prover for Lean that learned to solve a variety of challenging high-school olympiad problems, including problems from the AMC12 and AIME competitions, as well as two problems adapted from the IMO.
Related stories
arXiv AI
Jun 17
First Proof Second Batch
arXiv:2606. 18119v1 Announce Type: new Abstract: To assess the ability of current AI systems to correctly solve research-level mathematics problems, we tested several AI systems on a set of ten problems in a broad range of mathematical fields; these problems arose naturally in the research process of the contributors.
OpenAI Blog
Jun 2, 2018
GamePad: A learning environment for theorem proving
DeepMind Blog
Oct 24, 2025
Advanced version of Gemini with Deep Think officially achieves gold-medal standard at the International Mathematical Olympiad
The International Mathematical Olympiad (“IMO”) is the world’s most prestigious competition for young mathematicians, and has been held annually since 1959. Each country taking part is represented by six elite, pre-university mathematicians who compete to solve six exceptionally difficult problems in algebra, combinatorics, geometry, and number theory.
arXiv AI
Jun 10
ComBench: A Benchmark for Rigorous Proof Reasoning and Constructive Realization in Olympiad-Level Combinatorics
arXiv:2606. 10479v1 Announce Type: new Abstract: Combinatorics is central to Olympiad-level mathematical problem solving, requiring deep discrete reasoning, creative constructions, and rigorous structural insight.
arXiv AI
Jun 3
LEAP: Supercharging LLMs for Formal Mathematics with Agentic Frameworks
arXiv:2606. 03303v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong informal mathematical reasoning but struggle to generate mechanically verifiable proofs in formal languages like Lean.
arXiv AI
Jun 16
SorryDB: Can AI Provers Complete Real-World Lean Theorems?
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.
arXiv AI
Jun 2
Formally Solving Answer-Construction Problems in Lean
arXiv:2505. 18492v5 Announce Type: replace Abstract: Mathematical competition problems fall into two broad types: theorem proving, which asks for a proof of a given statement, and answer construction, which requires constructing a property-satifying object with proofs.
arXiv AI
Jun 9
Advancing Mathematics Research with AI-Driven Formal Proof Search
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.
Towards Data Science
4d ago
Mathematical Experiments Are Becoming Abundant Through Human-Machine Teaming
Two open problems, exact-arithmetic checking and a proof assistant, over a single weekend. The post Mathematical Experiments Are Becoming Abundant Through Human-Machine Teaming appeared first on Towards Data Science .
arXiv Machine Learning
Jun 16
Escaping the Cognitive Well: Efficient Competition Math with Off-the-Shelf Models
arXiv:2602. 16793v2 Announce Type: replace Abstract: In the past year, custom and unreleased math reasoning models reached gold medal performance on the International Mathematical Olympiad (IMO).
arXiv Machine Learning
Jun 25
Discovering New Theorems via LLMs with In-Context Proof Learning in Lean
arXiv:2509. 14274v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated significant promise in formal theorem proving.