| | --- |
| | license: mit |
| | base_model: |
| | - CodeGoat24/UnifiedReward-2.0-qwen3vl-8b |
| | --- |
| | |
| | ## Model Summary |
| |
|
| | `UnifiedReward-Think-qwen3vl-8b` 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-qwen3vl-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} |
| | } |
| | ``` |
