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Code2Math: Can Your Code Agent Effectively Evolve Math Problems Through Exploration?

Published in arXiv (Cornell University) • Mar 3, 2026
NobleIDNI5P706W838R477S591
Authors:
Dadi Guo
,
Yuejin Xie
,
Qingyu Liu

Abstract

As large language models (LLMs) advance their mathematical capabilities toward the IMO level, the scarcity of challenging, high-quality problems for training and evaluation has become a significant bottleneck. Simultaneously, recent code agents have demonstrated sophisticated skills in agentic codin...

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