Update README.md

README.md

@@ -17,6 +17,28 @@ size_categories:
 
 # Dataset Card for PhysTool-Bench
 
+<div align="center">
+
+  <a href="https://github.com/ModalityDance/PhysTool-Bench">
+    <img src="https://img.shields.io/badge/GitHub-Official_Codebase-181717?style=for-the-badge&logo=github&logoColor=white" alt="GitHub">
+  </a>
+
+  <a href="{project_page_url}">
+    <img src="https://img.shields.io/badge/Project-Page-6a5acd?style=for-the-badge" alt="Project Page">
+  </a>
+
+  <a href="{paper_url}">
+    <img src="https://img.shields.io/badge/Paper-arXiv-b31b1b?style=for-the-badge&logo=arxiv" alt="Paper">
+  </a>
+
+  <a href="{huggingface_papers_url}">
+    <img src="https://img.shields.io/badge/HuggingFace-Papers-fcc21b?style=for-the-badge&logo=huggingface&logoColor=white" alt="HF Papers">
+  </a>
+
+</div>
+
+<br>
+
 ## 📊 Dataset Summary
 
 **PhysTool-Bench** is a multimodal benchmark designed to evaluate how well Multimodal Large Language Models (MLLMs) perceive, select, and sequence physical tools in real-world scenes. Unlike traditional tool-use benchmarks that focus on digital APIs, this dataset probes an MLLM's ability to ground functional reasoning in cluttered, physical environments. 
@@ -117,4 +139,4 @@ If you use **PhysTool-Bench** in your research, please cite our paper:
 
 ## 📜 License
 
-The dataset (images and annotations) is released under the **MIT** license for non-commercial research use.
+The dataset is released under the **MIT** license.