Update README.md

README.md

@@ -1,29 +1,29 @@
----
-license: mit
-language:
-- en
-base_model:
-- Qwen/Qwen2.5-VL-7B-Instruct
-pipeline_tag: reinforcement-learning
-tags:
-- IQA
-- Reasoning
-- VLM
-- Pytorch
-- R1
----
+---
+license: mit
+language:
+- en
+base_model:
+- Qwen/Qwen2.5-VL-7B-Instruct
+pipeline_tag: reinforcement-learning
+tags:
+- IQA
+- Reasoning
+- VLM
+- Pytorch
+- R1
+- GRPO
+- RL2R
+---
 
 # VisualQuality-R1-7B
-This is the final version of VisualQuality-R1, trained on a diverse combination of synthetic and realistic datasets.<br>
+This is the latest version of VisualQuality-R1, trained on a diverse combination of synthetic and realistic datasets.<br>
 Paper link: [arXiv](https://arxiv.org/abs/2505.14460)<br>
 Code link: [github](https://github.com/TianheWu/VisualQuality-R1)
 
 > The first NR-IQA model enhanced by RL2R, capable of both quality description and rating through reasoning.
 
 
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/655de51982afda0fc479fb91/JZgVeMtAVASCCNYO5VCyn.png)
-
+<img src="https://cdn-uploads.huggingface.co/production/uploads/655de51982afda0fc479fb91/JZgVeMtAVASCCNYO5VCyn.png" width="600"/>
 
 
 ## Quick Start
@@ -327,6 +327,21 @@ print(answer)
 
 
 
+## Related Projects
+- [ECCV 2024] [A Comprehensive Study of Multimodal Large Language Models for Image Quality Assessment](https://arxiv.org/abs/2403.10854v2)
+- [CVPR 2025] [Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality Assumption](https://www.arxiv.org/abs/2503.11221)
 
 
+## 📧 Contact
+If you have any question, please email `[email protected]` or `[email protected]`.
 
+
+## BibTeX
+```
+@article{wu2025visualquality,
+  title={{VisualQuality-R1}: Reasoning-Induced Image Quality Assessment via Reinforcement Learning to Rank},
+  author={Wu, Tianhe and Zou, Jian and Liang, Jie and Zhang, Lei and Ma, Kede},
+  journal={arXiv preprint arXiv:2505.14460},
+  year={2025}
+}
+```