Add model card metadata and links
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by
nielsr
HF Staff
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README.md
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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
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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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# 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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```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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@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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