Update README.md

README.md

@@ -10,6 +10,7 @@ pinned: false
 # 👩‍⚖️ [**MJ-Bench**: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?](https://mj-bench.github.io/)
 
 Project page: https://mj-bench.github.io/
+Code repository: https://github.com/MJ-Bench/MJ-Bench
 
 While text-to-image models like DALLE-3 and Stable Diffusion are rapidly proliferating, they often encounter challenges such as hallucination, bias, and the production of unsafe, low-quality output. To effectively address these issues, it is crucial to align these models with desired behaviors based on feedback from a multimodal judge. Despite their significance, current multimodal judges frequently undergo inadequate evaluation of their capabilities and limitations, potentially leading to misalignment and unsafe fine-tuning outcomes. 
 
@@ -23,7 +24,7 @@ Specifically, we evaluate a large variety of multimodal judges including
 - 11 open-source VLMs (e.g. LLaVA family)
 - 4 and close-source VLMs (e.g. GPT-4o, Claude 3)
 - 
-![Evaluation result](https://github.com/MJ-Bench/MJ-Bench.github.io/blob/main/static/images/radar_plot.png)
+![Radar Plot](https://raw.githubusercontent.com/MJ-Bench/MJ-Bench.github.io/main/static/images/radar_plot.png)
 
 
-We are actively updating the [leaderboard](https://mj-bench.github.io/) and you are welcome to submit the evaluation result of your multimodal judge on [our dataset](https://huggingface.co/datasets/MJ-Bench/MJ-Bench) to [huggingface leaderboard](https://huggingface.co/spaces/MJ-Bench/MJ-Bench-Leaderboard).
+🔥🔥We are actively updating the [leaderboard](https://mj-bench.github.io/) and you are welcome to submit the evaluation result of your multimodal judge on [our dataset](https://huggingface.co/datasets/MJ-Bench/MJ-Bench) to [huggingface leaderboard](https://huggingface.co/spaces/MJ-Bench/MJ-Bench-Leaderboard).