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  license: apache-2.0
 
 
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  ---
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  # Model Card for AtomThinkPRM
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- The model is fine-tuned with atomic step execution based on math-psa and can be used for process supervision in multimodal reasoning chains.
 
 
 
 
 
 
 
 
 
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  # Citation
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- If you use this dataset in your research, please cite:
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- ```text
 
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  @article{xiang2024atomthink,
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  title={AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning},
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  author={Xiang, Kun and Liu, Zhili and Jiang, Zihao and Nie, Yunshuang and Huang, Runhui and Fan, Haoxiang and Li, Hanhui and Huang, Weiran and Zeng, Yihan and Han, Jianhua and others},
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  journal={arXiv preprint arXiv:2411.11930},
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  year={2024}
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  }
 
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  @article{wang2024openr,
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  title={OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models},
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  author={Wang, Jun and Fang, Meng and Wan, Ziyu and Wen, Muning and Zhu, Jiachen and Liu, Anjie and Gong, Ziqin and Song, Yan and Chen, Lei and Ni, Lionel M and others},
 
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+ ---
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  license: apache-2.0
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+ library_name: transformers
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+ pipeline_tag: image-text-to-text
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  ---
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  # Model Card for AtomThinkPRM
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+ The model is fine-tuned with atomic step execution based on math-psa and can be used for process supervision in multimodal reasoning chains. It is part of the **AtomThink** framework, which introduces "slow thinking" into multimodal large language models (MLLMs).
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+ - **Paper:** [AtomThink: Multimodal Slow Thinking with Atomic Step Reasoning](https://huggingface.co/papers/2411.11930)
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+ - **Repository:** [https://github.com/Kun-Xiang/AtomThink](https://github.com/Kun-Xiang/AtomThink)
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+ ## Description
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+ AtomThink incorporates the notion of "slow thinking" into MLLMs, allowing models to adaptively use different levels of reasoning for questions of varying complexity. It proposes a novel paradigm of Self-structured Chain of Thought (SCoT), which consists of minimal semantic atomic steps.
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+ AtomThinkPRM is designed for process supervision, enabling the evaluation of single-step reasoning quality within these multimodal chains.
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  # Citation
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+ If you use this model in your research, please cite:
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+
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+ ```bibtex
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  @article{xiang2024atomthink,
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  title={AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning},
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  author={Xiang, Kun and Liu, Zhili and Jiang, Zihao and Nie, Yunshuang and Huang, Runhui and Fan, Haoxiang and Li, Hanhui and Huang, Weiran and Zeng, Yihan and Han, Jianhua and others},
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  journal={arXiv preprint arXiv:2411.11930},
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  year={2024}
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  }
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+
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  @article{wang2024openr,
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  title={OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models},
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  author={Wang, Jun and Fang, Meng and Wan, Ziyu and Wen, Muning and Zhu, Jiachen and Liu, Anjie and Gong, Ziqin and Song, Yan and Chen, Lei and Ni, Lionel M and others},