6 citations · 8 across the 9 of their papers we have counts for
10 papers
New Records for the Hadamard Maximal Determinant Problem
Giorgi Butbaia, Pragatheeswaran Vipulanandan, Justin Tan +6
The Hadamard maximal determinant problem seeks an matrix with entries in , which maximizes the determinant for a given order $n \in…
New Snake-in-the-Box Records via Snakepit Surgery and Learned Construction
Paul Orland, Lucas Fagan, Michele Tarquini +7
The snake-in-the-box problem asks for a longest induced path in the hypercube graph . We find a length-191 snake in dimension , the lowest dimension where the maximum is…
Hierarchical Reinforcement Learning for Sparse-Reward Search in Commutative Algebra
Giorgi Butbaia, Paul Orland, Coco Huang +7
Applying machine learning techniques to solving long-standing mathematical conjectures can be particularly challenging due to their extreme reward sparsity. As an illustrative exam…
The Two-Hump Problem: Bridging the Difficulty Gap in Mathematical Reinforcement Learning
Lucas Fagan, Michele Tarquini, Ali Shehper +6
Mathematical search problems present a unique challenge for Reinforcement Learning (RL) due to vast search spaces and sparse rewards. In previous works, the Andrews-Curtis (AC) con…
Aletheia tackles FirstProof autonomously
Tony Feng, Junehyuk Jung, Sang-hyun Kim +14
We report the performance of Aletheia (Feng et al., 2026b), a mathematics research agent powered by Gemini 3 Deep Think, on the inaugural FirstProof challenge. Within the allowed t…
Aristotle: IMO-level Automated Theorem Proving
Tudor Achim, Alex Best, Alberto Bietti +20
We introduce Aristotle, an AI system that combines formal verification with informal reasoning, achieving gold-medal-equivalent performance on the 2025 International Mathematical O…
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)
Andrew Ferguson, Marisa LaFleur, Lars Ruthotto +97
This community paper developed out of the NSF Workshop on the Future of Artificial Intelligence (AI) and the Mathematical and Physics Sciences (MPS), which was held in March 2025 w…
What makes math problems hard for reinforcement learning: a case study
Ali Shehper, Anibal M. Medina-Mardones, Lucas Fagan +6
Using a long-standing conjecture from combinatorial group theory, we explore, from multiple perspectives, the challenges of finding rare instances carrying disproportionately high…
Learning BPS Spectra and the Gap Conjecture
Sergei Gukov, Rak-Kyeong Seong
We explore statistical properties of BPS q-series for 3d N=2 strongly coupled supersymmetric theories that correspond to a particular family of 3-manifolds Y. We discover that gaps…
Rigor with Machine Learning from Field Theory to the Poincaré Conjecture
Sergei Gukov, James Halverson, Fabian Ruehle
Machine learning techniques are increasingly powerful, leading to many breakthroughs in the natural sciences, but they are often stochastic, error-prone, and blackbox. How, then, s…