Yanchen Nie — accepted AI-conference papers

2026

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving

Chenyi Li, Yanchen Nie, Zhenyu Ming, Gong Zhang, Kun Yuan, Zaiwen Wen

ICML 2026poster

Recent advances in formal theorem proving have focused on Olympiad-level mathematics, leaving undergraduate domains largely unexplored. Optimization, fundamental to machine learning, operations research, and scientific computing, remains underserved by existing provers. Its reliance on domain-specif…

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2026

Scaling up Multi-Turn Off-Policy RL and Multi-Agent Tree Search for LLM Step-Provers

Ran Xin, Zeyu Zheng, Yanchen Nie, Kun Yuan, Xia Xiao

ICML 2026poster

The integration of Large Language Models (LLMs) with automated theorem proving has shown immense promise, yet is constrained by challenges in scaling up both training-time reinforcement learning (RL) and inference-time compute. This paper introduces BFS-Prover-V2, a step-level theorem proving system…

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