Add robotics task category and paper/code links

README.md

@@ -1,5 +1,8 @@
 ---
 license: mit
+pretty_name: SafeLIBERO
+task_categories:
+- robotics
 tags:
 - robotics
 - reinforcement-learning
@@ -7,13 +10,15 @@ tags:
 - benchmark
 - libero
 - simulation
-pretty_name: SafeLIBERO
 ---
+
 <h1 align="center" style="font-size: 75px; font-weight: bold; margin-top: 30px;">
   📊 SafeLIBERO Benchmark
 </h1>
 
 <div align="center">
+  <a href="https://huggingface.co/papers/2512.11891"><img src="https://img.shields.io/badge/arXiv-Paper-red" alt="Paper" height="25"></a>
+  <a href="https://github.com/THU-RCSCT/vlsa-aegis"><img src="https://img.shields.io/badge/GitHub-Code-blue" alt="Code" height="25"></a>
   <a href="https://vlsa-aegis.github.io/benchmark.html"><img src="https://img.shields.io/badge/-Detailed_Overview-3776AB?logo=readthedocs&logoColor=white" alt="Detailed Overview" height="25"></a>
   <a href="https://vlsa-aegis.github.io/"><img src="https://img.shields.io/badge/-Video_Demos-FF0000?logo=youtube&logoColor=white" alt="Video Demos" height="25"></a>
 </div>
@@ -26,7 +31,7 @@ pretty_name: SafeLIBERO
 
 ## 📖 Overview
 
-**SafeLIBERO** is a benchmark designed to evaluate robotic model performance in complex, safety-critical environments. It extends each LIBERO suite by selecting **four representative tasks**, with each task further divided into two scenarios varying by safety level based on obstacle interference:
+**SafeLIBERO** is a benchmark designed to evaluate robotic model performance in complex, safety-critical environments, introduced in the paper [VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer](https://huggingface.co/papers/2512.11891). It extends each LIBERO suite by selecting **four representative tasks**, with each task further divided into two scenarios varying by safety level based on obstacle interference:
 
 * **Level I**: Scenarios where the obstacle is positioned in **close proximity** to the target object.
 * **Level II**: Scenarios where the obstacle is located further away but **obstructs the movement path**.
@@ -61,14 +66,14 @@ Please run the following commands in order to set up the environment for **SafeL
 ```bash
 conda create -n libero python=3.8.13
 conda activate libero
-git clone [https://github.com/THU-RCSCT/vlsa-aegis.git](https://github.com/THU-RCSCT/vlsa-aegis.git)
+git clone https://github.com/THU-RCSCT/vlsa-aegis.git
 cd SafeLIBERO/safelibero
 pip install -r requirements.txt
 ```
 
 
 ## 🚀 Running Evaluation
-```
+```bash
 export PYTHONPATH=$PYTHONPATH:$PWD/safelibero
 python main_demo.py \
     --task-suite-name safelibero_spatial \
@@ -101,7 +106,7 @@ for i in obstacle_names:
 **2. Detect Collision (Inside Loop)** 
 
 Then, inside the simulation loop, check for collisions by monitoring the obstacle's displacement. If the obstacle moves significantly from its initial position, it is flagged as a collision:
-```
+```python
 if not collide_flag:
     curr_pos = obs[f"{obstacle_name}_pos"]
     displacement = np.sum(np.abs(curr_pos - initial_obstacle_pos))
@@ -149,8 +154,7 @@ The following research works have utilized the **SafeLIBERO Benchmark** for expe
 
 | Title | Journal / Conference / Preprints | Year | 
 |:-----:|:--------------------------------:|:----:|
-| VLSA: Vision-Language-Action Models with <br> Plug-and-Play Safety Constraint Layer | arXiv | 2025 | 
-| xxx | xxx | xxx | 
+| [VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer](https://huggingface.co/papers/2512.11891) | arXiv | 2025 | 
 
 
 **Add Your Work**: If you have used this benchmark in your research, please feel free to share your work with us. We are happy to include it in this list to support the research community. We sincerely appreciate the support of the research community and encourage researchers to share their publications using this benchmark. Thank you for your contributions! 
@@ -160,7 +164,7 @@ If you find the project helpful for your research, please consider citing our pa
 ```bibtex
 @article{hu2025vlsa,
   title={VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer},
-  author={Hu, Songqiao and Liu, Zeyi and Liu, Shuang and Cen, Jun and Meng, Zihan and He, Xiao},
+  author={Hu, Songqiao and Liu, Zeyi and Liu, Shuang  and Cen, Jun and Meng, Zihan and He, Xiao},
   journal={arXiv preprint arXiv:2512.11891},
   year={2025}
 }