Prove2Me: An Open Collaborative Platform for Scaling Math Formalization

arXiv:2603.19828v1 Announce Type: new Abstract: Autoformalization aims to translate natural-language mathematics into compilable, machine-checkable statements. However, semantic

arXiv:2603.26996v1 Announce Type: new Abstract: We present FormalProofBench, a private benchmark designed to evaluate whether AI models can produce formally verified mathematical

arXiv:2606.20642v1 Announce Type: new Abstract: Asymptotic statistical theory is a challenging domain for AI-assisted formalization: its central results mix convergence

arXiv:2604.15839v1 Announce Type: new Abstract: Most ATP benchmarks embed the final answer within the formal statement -- a convention we call "Easy Mode" -- a design that

arXiv:2604.06401v1 Announce Type: new Abstract: The large language models (LLMs) might produce a persuasive argument within mathematical and logical fields, although such argument

arXiv:2607.08986v1 Announce Type: new Abstract: We formalize a research result in the Lean 4 proof assistant by having a mathematician direct an AI system, and frame the activity

arXiv:2608.23691v1 Announce Type: new Abstract: We study autonomous mathematical discovery in the Station, an open-world multi-agent environment in which AI agents from different

arXiv:2606.13925v1 Announce Type: new Abstract: Large language models can often close proof gaps in interactive theorem provers, but a verified theorem is not the same thing as a