Update model card: Add main paper link, update project page and citation

README.md

@@ -1,11 +1,11 @@
 ---
-pipeline_tag: robotics
 library_name: transformers
 license: cc-by-nc-sa-4.0
+pipeline_tag: robotics
 tags:
-  - vision-language-model
-  - video-language-model
-  - navigation
+- vision-language-model
+- video-language-model
+- navigation
 ---
 
 <div id="top" align="center">
@@ -13,18 +13,13 @@ tags:
 
 </div>
 
-
-
-
 # InternVLA-N1: An Open Dual-System Navigation Foundation Model with Learned Latent Plans
 
-[![Code](https://img.shields.io/badge/GitHub-Code-181717?logo=github)](https://github.com/InternRobotics/InternNav)
-
-Project page: https://internrobotics.github.io/internvla-n1.github.io/
-
-Technical report: https://internrobotics.github.io/internvla-n1.github.io/static/pdfs/InternVLA_N1.pdf
-
-Data: https://huggingface.co/datasets/InternRobotics/InternData-N1
+**Paper:** [Ground Slow, Move Fast: A Dual-System Foundation Model for Generalizable Vision-and-Language Navigation](https://huggingface.co/papers/2512.08186)
+**Code:** [![Code](https://img.shields.io/badge/GitHub-Code-181717?logo=github)](https://github.com/InternRobotics/InternNav)
+**Project Page:** https://internrobotics.github.io/internvla-n1-dualvln.github.io/
+**Technical Report (InternVLA-N1):** https://internrobotics.github.io/internvla-n1.github.io/static/pdfs/InternVLA_N1.pdf
+**Data:** https://huggingface.co/datasets/InternRobotics/InternData-N1
 
 
 
@@ -35,13 +30,13 @@ Data: https://huggingface.co/datasets/InternRobotics/InternData-N1
 * We recommend using this official release for research and deployment, as it contains the most stable and up-to-date improvements.
 
 ### Key Difference: Preview vs Official
-| Feature       | InternVLA-N1-Preview                      | InternVLA-N1 (official)                                                  |
-| ------------- | ----------------------------------------- | ------------------------------------------------------------------------ |
-| System Design | Dual-System (synchronous)                 | Dual-System (asynchronous)                                               |
-| Training      |  System 1 trained only at System 2 inferrence step | System 1 trained on denser step (~25 cm), using latest System 2 hidden state |
-| Inference     | System 1, 2 infered at same frequency (~2 hz)      | System 1, 2 infered asynchronously, allowing dynamic obstacle avoidance |
-| Performance   | Solid baseline in simulation & benchmarks | Improved smoothness, efficiency, and real-world zero-shot generalization |
-| Status        | Historical preview                        | Stable official release (recommended)
+| Feature | InternVLA-N1-Preview | InternVLA-N1 (official) |
+|---|---|---|
+| System Design | Dual-System (synchronous) | Dual-System (asynchronous) |
+| Training | System 1 trained only at System 2 inferrence step | System 1 trained on denser step (~25 cm), using latest System 2 hidden state |
+| Inference | System 1, 2 infered at same frequency (~2 hz) | System 1, 2 infered asynchronously, allowing dynamic obstacle avoidance |
+| Performance | Solid baseline in simulation & benchmarks | Improved smoothness, efficiency, and real-world zero-shot generalization |
+| Status | Historical preview | Stable official release (recommended)
 
 ## Highlights
 
@@ -66,11 +61,11 @@ Please refer to [InternNav](https://github.com/InternRobotics/InternNav) for its
 If you find our work helpful, please consider starring this repo 🌟 and cite:
 
 ```bibtex
-@misc{internvla-n1,
-    title = {{InternVLA-N1: An} Open Dual-System Navigation Foundation Model with Learned Latent Plans},
-    author = {InternVLA-N1 Team},
-    year = {2025},
-    booktitle={arXiv},
+@article{wei2025ground,
+  title={Ground Slow, Move Fast: A Dual-System Foundation Model for Generalizable Vision-and-Language Navigation},
+  author={Wei, Meng and Wan, Chenyang and Peng, Jiaqi and Yu, Xiqian and Yang, Yuqiang and Feng, Delin and Cai, Wenzhe and Zhu, Chenming and Wang, Tai and Pang, Jiangmiao and Liu, Xihui},
+  journal={arXiv preprint arXiv:2512.08186},
+  year={2025}
 }
 ```