| --- |
| license: mit |
| base_model: |
| - CodeGoat24/UnifiedReward-2.0-qwen3vl-2b |
| --- |
| |
| ## Model Summary |
|
|
| `UnifiedReward-Think-qwen3vl-2b` is the first unified multimodal CoT reward model, capable of multi-dimensional, step-by-step long-chain reasoning for both visual understanding and generation reward tasks. |
|
|
| For further details, please refer to the following resources: |
| - 📰 Paper: https://arxiv.org/pdf/2505.03318 |
| - 🪐 Project Page: https://codegoat24.github.io/UnifiedReward/think |
| - 🤗 Model Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-models-67c3008148c3a380d15ac63a |
| - 🤗 Dataset Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-training-data-67c300d4fd5eff00fa7f1ede |
| - 👋 Point of Contact: [Yibin Wang](https://codegoat24.github.io) |
|
|
| 🚀 All inference code is provided at [Github](https://github.com/CodeGoat24/UnifiedReward/tree/main/UnifiedReward-Think/inference_qwen/UnifiedReward-Think-qwen3-inference). |
|
|
| ## Citation |
|
|
| ``` |
| @article{unifiedreward-think, |
| title={Unified multimodal chain-of-thought reward model through reinforcement fine-tuning}, |
| author={Wang, Yibin and Li, Zhimin and Zang, Yuhang and Wang, Chunyu and Lu, Qinglin and Jin, Cheng and Wang, Jiaqi}, |
| journal={arXiv preprint arXiv:2505.03318}, |
| year={2025} |
| } |
| ``` |
