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cs.AI2026

ProofCouncil: An LLM Agent for Solving Open Mathematical Problems

Johannes Schmitt, Tim Gehrunger, Jasper Dekoninck +4

Large language models (LLMs) have shown increasing promise in solving open problems in mathematics. However, their performance can be further improved through agentic workflows tai…

cs.AI2026

QED-Nano: Teaching a Tiny Model to Prove Hard Theorems

LM-Provers, Yuxiao Qu, Amrith Setlur +6

Proprietary AI systems have recently demonstrated impressive capabilities on complex proof-based problems, with gold-level performance reported at the 2025 International Mathematic…

cs.AI2026

MathArena: Evaluating LLMs on Uncontaminated Math Competitions

Mislav Balunović, Jasper Dekoninck, Ivo Petrov +2

The rapid advancement of reasoning capabilities in large language models (LLMs) has led to notable improvements on mathematical benchmarks. However, many of the most commonly used…

cs.AI2025

BrokenMath: A Benchmark for Sycophancy in Theorem Proving with LLMs

Ivo Petrov, Jasper Dekoninck, Martin Vechev

Large language models (LLMs) have recently shown strong performance on mathematical benchmarks. At the same time, they are prone to hallucination and sycophancy, often providing co…

cs.AI2025

MathConstruct: Challenging LLM Reasoning with Constructive Proofs

Mislav Balunović, Jasper Dekoninck, Nikola Jovanović +2

While Large Language Models (LLMs) demonstrate impressive performance in mathematics, existing math benchmarks come with significant limitations. Many focus on problems with fixed…