| | --- |
| | base_model: |
| | - Qwen/Qwen2.5-VL-7B-Instruct |
| | language: |
| | - en |
| | license: apache-2.0 |
| | tags: |
| | - transformers |
| | - multimodal |
| | pipeline_tag: visual-question-answering |
| | --- |
| | |
| | # VL-Rethinker-72B |
| |
|
| | **🚀 News:** <u>We release our meticulously curated collection of RL training queries for multimodal reasoning: [ViRL39K](https://huggingface.co/datasets/TIGER-Lab/ViRL39K).</u> |
| |
|
| | **VL-Rethinker-72B** achieves SoTA results on various multimodal reasoning benchmarks. |
| |
|
| | It is trained using the **Forced Rethinking** technique, on top of [**VL-Reasoner**](https://huggingface.co/TIGER-Lab/VL-Reasoner-72B/) with **GRPO-SSR** training. |
| |
|
| | For details of our approach and performance comparison, please see our [paper](https://github.com/TIGER-AI-Lab/VL-Rethinker/blob/main/paper.pdf). |
| |
|
| | For details of training and evaluation, please see our [code repo](https://github.com/TIGER-AI-Lab/VL-Rethinker/). |
| |
|
| | Explore further via the following links: |
| |
|
| | | [**🚀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**](https://huggingface.co/datasets/TIGER-Lab/ViRL39K) | |
| |
|
| | ## Prompt |
| | Append the following after the user query: |
| | ```python |
| | """Guidelines: |
| | Please think step by step, and **regularly perform self-questioning, self-verification, self-correction to check your ongoing reasoning**, using connectives such as "Wait a moment", "Wait, does it seem right?", etc. Remember to put your final answer within \\boxed{}. |
| | """ |
| | ``` |
| |
|
| | ## Citation |
| |
|
| | If you feel this model useful, please give us a free cite: |
| | ```bibtex |
| | @article{vl-rethinker, |
| | title={VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning}, |
| | author = {Wang, Haozhe and Qu, Chao and Huang, Zuming and Chu, Wei and Lin, Fangzhen and Chen, Wenhu}, |
| | journal={arXiv preprint arXiv:2504.08837}, |
| | year={2025} |
| | } |
| | ``` |
| |
|