aiqbench analysis
Bolzano represents a significant leap in automated mathematical research by leveraging multi-agent systems to solve open problems without human guidance, effectively scaling proof search from expert-led cases to thousands of theoretical computer science challenges. This development highlights the evolving capability of large language models to handle rigorous verification tasks traditionally reserved for domain experts, marking a concrete advancement in AI-driven formal reasoning.
From Expert-Guided Proof Search to Automated Open-Problem Solving
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 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.
Abstract: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.
Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
arXiv:2610.09769 [cs.AI]
(or arXiv:2610.09769v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2610.09769 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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