From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontier
Recent developments in AI for Mathematics (AI4Math), especially Large Language Model (LLM)-driven theorem provers, has achieved remarkable success in formal proof generation for well-defined mathematical problems through Interactive Theorem Proving (ITP) languages. However, current systems remain fundamentally limited in tackling frontier research mathematics, such as discovering new theorems or resolving open conjectures, which are often open-ended, under-specified, and involve multiple layers of abstraction. We argue that the next leap in AI4Math systems requires a decisive shift from predefined problem-solvers to research agents that can address frontier mathematical challenges with ri...
| Authors | Eric Jiang, Xiao Liang, Yikai Zhang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 8 July 2026 |
| Last updated at source | 8 July 2026 |
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