Add metadata, paper link, and GitHub repository

README.md

@@ -1,32 +1,54 @@
+---
+task_categories:
+- robotics
+- image-text-to-text
+license: other
+---
+
 # MUSON: A Reasoning-oriented Multimodal Dataset for Socially Compliant Navigation
 
+[Paper](https://huggingface.co/papers/2512.22867) | [GitHub](https://github.com/MUSON-dataset/MUSON)
+
 ## Overview
 
-MUSON is a reasoning-oriented multimodal dataset designed for short-horizon socially compliant navigation in urban environments.
+MUSON is a reasoning-oriented multimodal dataset designed for short-horizon socially compliant navigation in urban environments. It contains 10,110 egocentric samples collected across diverse indoor and outdoor social scenes.
 
 ## Dataset Structure
 
-- MUSON_images/: RGB images
-- MUSON_Annotations.json: Structured 5-step reasoning annotations
+After downloading and extracting the dataset package, the dataset is organized as follows:
+
+```text
+MUSON/
+├── MUSON_images/
+│   ├── 000001.jpg
+│   ├── 000002.jpg
+│   └── ...
+└── MUSON_Annotations.json
+```
+
+- `MUSON_images/`: RGB images
+- `MUSON_Annotations.json`: Structured 5-step reasoning annotations
 
 Each annotation contains:
-- perception
-- prediction
-- reasoning
-- action
-- explanation
+- **perception**: Static physical constraints and pedestrian visual attributes.
+- **prediction**: Anticipated pedestrian movements.
+- **reasoning**: Social norm compliance assessment.
+- **action**: Standardized action output chosen from a six-action decision space.
+- **explanation**: Natural language justification for the decision.
 
 ## Citation
 
 If you use this dataset, please cite:
 
+```bibtex
 @article{liu2025muson,
   title={MUSON: A Reasoning-oriented Multimodal Dataset for Socially Compliant Navigation in Urban Environments},
   author={Liu, Zhuonan and Zhang, Xinyu and Wang, Zishuo and Kawabata, Tomohito and Xiao, Xuesu and Xiao, Ling},
   journal={arXiv preprint arXiv:2512.22867},
   year={2025}
 }
+```
 
 ## License
 
-Research use only.
+Research use only.