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September 29, 2025Open Access

MMATH: A Multilingual Benchmark for Mathematical Reasoning

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MMATH showcases the need for improved multilingual reasoning in advanced language models, indicating potential performance disparities.
Models like DeepSeek R1 exhibit substantial issues generating responses in unintended languages, suggesting a critical gap.
Employing strategies such as targeted prompting can improve performance and consistency in multilingual reasoning tasks.
Addressing multilingual reasoning capabilities can significantly enhance large language models, providing practical insights.

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MMATH benchmarks multilingual complex reasoning across 374 math problems, revealing performance disparities in models like DeepSeek R1.

Luo et al. (2025) studied this question.

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