arXiv Computation and Language October 23, 2026 By Wen Yang, Junhong Wu, Chong Li, Chengqing Zong, Jiajun Zhang

How Well Does Mathematical Reasoning Transfer Across Languages in English-Centric LLMs?

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The paper investigates how mathematical reasoning improvements from Reinforcement Post-Training (RPT) in English-centric large language models (LLMs) transfer to other languages. Experiments show that transfer varies greatly depending on the initial model, target language, and training approach, and that stronger English initialization does not guarantee better transfer efficiency. Adding a single parallel language to the training data yields the largest boost, with additional languages providing smaller but consistent gains.

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