Update README.md

README.md

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 ## Recent News
-- 🎉 **MJ-PreferGen** is **accepted by ICLR25**! Check out the paper: [*MJ-PreferGen: An Automatic Framework for Preference Data Synthesis*](https://openreview.net/forum?id=WpZyPk79Fu)
+- 🎉 **MJ-PreferGen** is **accepted by ICLR25**! Check out the paper: [*MJ-PreferGen: An Automatic Framework for Preference Data Synthesis*](https://openreview.net/forum?id=WpZyPk79Fu).
 - 🔥 We have released [**MJ-Video**](https://aiming-lab.github.io/MJ-VIDEO.github.io/). All datasets and model checkpoints are available [here](https://huggingface.co/MJ-Bench)!
 
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 ## 😎 [**MJ-Video**: Fine-Grained Benchmarking and Rewarding Video Preferences in Video Generation](https://aiming-lab.github.io/MJ-VIDEO.github.io/)
 
+- **Project page**: [https://aiming-lab.github.io/MJ-VIDEO.github.io/](https://aiming-lab.github.io/MJ-VIDEO.github.io/)
+- **Code repository**: [https://github.com/aiming-lab/MJ-Video](https://github.com/aiming-lab/MJ-Video)
+
 We release **MJ-Bench-Video**, a comprehensive fine-grained video preference benchmark, and **MJ-Video**, a powerful MoE-based multi-dimensional video reward model!
 
 <p align="center">
@@ -54,6 +57,10 @@ We release **MJ-Bench-Video**, a comprehensive fine-grained video preference ben
 
 Text-to-image models like DALLE-3 and Stable Diffusion are proliferating rapidly, but they often encounter challenges such as hallucination, bias, and unsafe or low-quality output. To effectively address these issues, it’s crucial to align these models with desired behaviors based on feedback from a **multimodal judge**.
 
+<p align="center">
+  <img src="https://raw.githubusercontent.com/MJ-Bench/MJ-Bench/main/assets/overview_new.png" alt="MJ-Bench Dataset Overview" width="80%"/>
+</p>
+
 However, current multimodal judges are often **under-evaluated**, leading to possible misalignment and safety concerns during fine-tuning. To tackle this, we introduce **MJ-Bench**, a new benchmark featuring a comprehensive preference dataset to evaluate multimodal judges on four critical dimensions:
 
 1. **Alignment**  
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 - 11 open-source VLMs (e.g., the LLaVA family)  
 - 4 closed-source VLMs (e.g., GPT-4, Claude 3)
 
-<p align="center">
-  <img src="https://raw.githubusercontent.com/MJ-Bench/MJ-Bench/main/assets/overview_new.png" alt="MJ-Bench Dataset Overview" width="80%"/>
-</p>
 
 🔥 **We are actively updating the [leaderboard](https://mj-bench.github.io/)!**  
 You are welcome to submit your multimodal judge’s evaluation results on [our dataset](https://huggingface.co/datasets/MJ-Bench/MJ-Bench) to the [Hugging Face leaderboard](https://huggingface.co/spaces/MJ-Bench/MJ-Bench-Leaderboard).