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In this paper, we address the challenging task of multimodal mathematical reasoning by incorporating the ability of "slow thinking" into multimodal large language models (MLLMs).
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Mathvista: Evaluating math reasoning in visual contexts with gpt-4v, bard, and other large multimodal models
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A survey on multimodal large language models
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Qwen2. 5-math technical report: Toward mathematical expert model via self-improvement
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Improve mathematical reasoning in language models by automated process supervision
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Math-llava: Bootstrapping mathematical reasoning for multimodal large language models
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Anthropic
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
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Llamav-o1: Rethinking step-by-step visual reasoning in llms
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Thoughts are all over the place: On the underthinking of o1-like llms
Yue Wang, Qiuzhi Liu, Jiahao Xu, Tian Liang, Xingyu Chen, Zhiwei He, Linfeng Song, Dian Yu, Juntao Li, Zhuosheng Zhang, et al · 2025
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R1-vision: Let’s first take a look at the image
Ya-Qi Yu, Minghui Liao, Jihao Wu, and Chao Weng · 2025
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