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  - multimodal
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  pipeline_tag: visual-question-answering
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  ---
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- # MM-Thinker-72B-Preview
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- ## Model Overview
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- - **MM-thinker-72B-Preview** improves visual reasoning upon [Qwen2.5-VL-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-72B-Instruct) model.
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- - As of April 3rd, 2025, **MM-thinker-72B-Preview** achieves superior results on various visual reasoning benchmarks ([MathVision](https://mathllm.github.io/mathvision/),[MathVista](https://mathvista.github.io/), [MathVerse](https://mathverse-cuhk.github.io/), [MMMU-Pro](), [EMMA](), [MEGA]()).
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- ## Evaluation
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- We will release a code repository for VLM evaluation. It supports RL training with simple rule-based rewards, meanwhile aligning with LLM-Judge results.
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-
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- Stay tuned!
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  ## Citation
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- If you find our model useful, please consider citing:
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  ```
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- @misc {MM-Thinker-72B,
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- author = { Wang, Haozhe and Lin, Fangzhen and Chen, Wenhu },
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- title = { MM-Thinker-72B },
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- year = 2025,
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- url = { https://huggingface.co/TIGER-Lab/MM-Thinker-72B},
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- publisher = { Hugging Face }
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- }
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  ```
 
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  - multimodal
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  pipeline_tag: visual-question-answering
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  ---
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+ # VL-Reasoner-72B
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+ **VL-Reasoner-72B** achieves superior results on various multimodal reasoning benchmarks.
 
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+ It is trained using the **GRPO-SSR** techniques, serving as the foundation for [**VL-Rethinker**](https://huggingface.co/TIGER-Lab/VL-Rethinker-72B/).
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+ For details of our approach and performance comparison, please see our [paper](https://github.com/TIGER-AI-Lab/VL-Rethinker/blob/main/paper.pdf).
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+ For details of training and evaluation, please see our [code repo](https://github.com/TIGER-AI-Lab/VL-Rethinker/).
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+ Explore further via the following links:
 
 
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+ | [**🚀Project Page**](https://tiger-ai-lab.github.io/VL-Rethinker/) | [**📖Paper**](https://arxiv.org/abs/2504.08837) | [**🔗Github**](https://github.com/TIGER-AI-Lab/VL-Rethinker/) | [**🤗Data** (Coming Soon)]() |
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  ## Citation
 
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+ If you feel this model useful, please give us a free cite:
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  ```
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+ @article{vl-rethinker,
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+ title={VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning},
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+ author = {Wang, Haozhe and Qu, Chao and Huang, Zuming and Chu, Wei and Lin, Fangzhen and Chen, Wenhu},
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+ journal={arXiv preprint arXiv:2504.08837},
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+ year={2025}
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+ }
 
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  ```