Add robotics pipeline tag and improve metadata

README.md

@@ -1,12 +1,19 @@
 ---
 license: cc-by-4.0
+pipeline_tag: robotics
+tags:
+- visual-navigation
+- sim-to-real
+- topological-navigation
 ---
 
 # FAINT
 
 Fast, Appearance-Invariant Navigation Transformer (FAINT) is a learned policy for vision-based topological navigation.
 
-Please see the [Project Page](https://lasuomela.github.io/faint/) for more information.
+This model is presented in the paper [Synthetic vs. Real Training Data for Visual Navigation](https://huggingface.co/papers/2509.11791).
+
+[**Project Page**](https://lasuomela.github.io/faint/) | [**Code**](https://github.com/lasuomela/faint)
 
 ## Model Details
 
@@ -25,7 +32,7 @@ See the main Github [repo](https://github.com/lasuomela/FAINT) for details, inpu
 
 Only dependency is Pytorch.
 
-```bash
+```python
 import torch
 ckpt_path = 'FAINT-Sim/model_torchscript.pt'
 model = torch.jit.load(ckpt_path)
@@ -35,7 +42,7 @@ model = torch.jit.load(ckpt_path)
 
 Need to have the Faint library installed.
 
-```bash
+```python
 import torch
 from faint.common.models.faint import FAINT
 
@@ -52,7 +59,7 @@ If you use FAINT in your research, please use the following BibTeX entry:
 ```bibtex
 @article{suomela2025synthetic, 
   title={Synthetic vs. Real Training Data for Visual Navigation},
-  author={Suomela, Lauri and Kuruppu Arachchige, Sasanka and Torres, German F. and Edelman, Harry and Kämäräinen, Joni-Kristian}
+  author={Suomela, Lauri and Kuruppu Arachchige, Sasanka and Torres, German F. and Edelman, Harry and Kämäräinen, Joni-Kristian},
   journal={arXiv:2509.11791},
   year={2025}
 }