From Expert-Guided Proof Search to Automated Open-Problem Solving
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Abstract (arXiv)
Large language models are increasingly contributing to mathematical research, where progress often depends on efficient proof search, incremental improvements and careful verification. We describe Bolzano, a multi-agent open-source system that uses parallel prover agents with a verifier agent and maintains a human-readable research state. Initial manual use on expert-selected problems yielded 8 results whose proofs were checked by domain experts. Motivated by these case studies, we ran Bolzano without problem-specific human guidance on about 3,800 open problems extracted from four sets of papers, solving about 200 open problems. One experiment used papers accepted to STOC 2026, a top conference in theoretical computer science. There, we answered four questions raised in the papers, as confirmed by their authors.
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References · 8
- 2025AlphaEvolve: A coding agent for scientific and algorithmic discoverycited by 763
- 2025Early science acceleration experiments with GPT-5cited by 35
- 2026Towards Autonomous Mathematics Researchcited by 31
- 2026Semi-Autonomous Mathematics Discovery with Gemini: A Case Study on the ErdHos Problemscited by 24
- 2026Accelerating Scientific Research with Gemini: Case Studies and Common Techniquescited by 24
- 2026Bolzano: Case Studies in LLM-Assisted Mathematical Researchcited by 3
- 2025Hesse's Redemption: Efficient Convex Polynomial Programmingcited by 2
- 2026A Unified Approach to Memory-Sample Tradeoffs for Detecting Planted Structurescited by 2
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