AI co-mathematician: Accelerating mathematicians with agentic AI
On the map: LLM agents and tool use → Educational agents and math problem solving
Abstract (arXiv)
We introduce the AI co-mathematician, a workbench for mathematicians to interactively leverage AI agents to pursue open-ended research. The AI co-mathematician is optimized to provide holistic support for the exploratory and iterative reality of mathematical workflows, including ideation, literature search, computational exploration, theorem proving and theory building. By providing an asynchronous, stateful workspace that manages uncertainty, refines user intent, tracks failed hypotheses, and outputs native mathematical artifacts, the system mirrors human collaborative workflows. In early tests, the AI co-mathematician helped researchers solve open problems, identify new research directions, and uncover overlooked literature references. Besides demonstrating a highly interactive paradigm for AI-assisted mathematical discovery, the AI co-mathematician also achieves state of the art results on hard problem-solving benchmarks, including scoring 48% on FrontierMath Tier 4, a new high score among all AI systems evaluated.
Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). Placed in Educational agents and math problem solving, one of 16 directions in LLM agents and tool use. Builds on 35 of its 66 references that are in the map. First posted on arXiv 7 May 2026.
Builds on
35 of 66 references.
Closest ancestors · 2
Same direction, newest first
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Other references · 33
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Citing papers per year: 2026: 17.
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- 2026Stable Menus of Public Goods: AI-Enabled Progresscited by 0
- 2026From Meta Idea to Advanced Mathematical Discovery -- Human-AI Co-Discovery of Sign-Embedding Quantum Algorithmscited by 0
- 2026Mathematical Discovery in the Wild: AI-Guided Proofs in Banach Space Theorycited by 0
- 2026EULER: Exploring Underused Links with Evidence-Checked Return for Multi-Agent Mathematical Discoverycited by 0
- 2026Continuous Optimization for p-adic Modelscited by 0
- 2026GenLimitLib: A Formal Library for Language Generation in the Limit and AI-Assisted Mathematical Researchcited by 0
- 2026GenLimitLib: A Formal Library for Language Generation in the Limit and AI-Assisted Mathematical Research29 Sep 2026
- 2026Continuous Optimization for p-adic Models21 Sep 2026
- 2026EULER: Exploring Underused Links with Evidence-Checked Return for Multi-Agent Mathematical Discovery28 Aug 2026
- 2026The Problem Is the Problem: Towards Scalable Mathematical Discovery17 Aug 2026
- 2026Extremal Chowla sets and their linear analogues: A human-AI mathematical investigation using Co-Scientist25 Jul 2026
- 2026Mathematical Discovery in the Wild: AI-Guided Proofs in Banach Space Theory19 Jul 2026
- 2026Stable Menus of Public Goods: AI-Enabled Progress15 Jun 2026
- 2026From Meta Idea to Advanced Mathematical Discovery -- Human-AI Co-Discovery of Sign-Embedding Quantum Algorithms12 Jun 2026
- 2026LeanMarathon: Toward Reliable AI Co-Mathematicians through Long-Horizon Lean Autoformalization3 Jun 2026
- 2026Human agency in initial human-AI proof formalization workflows2 Jun 2026
- 2026Every finite group admits a just finite presentation11 May 2026
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