Add metadata and link paper/code

README.md

@@ -1,31 +1,35 @@
+---
+license: apache-2.0
+pipeline_tag: robotics
+---
+
 # A Pragmatic VLA Foundation Model
+
 <p align="center">
-  <img src="assets/Teaser.png" width="100%">
+  <img src="https://huggingface.co/robbyant/lingbot-vla-4b/resolve/main/assets/Teaser.png" width="100%">
 </p>
 
+**LingBot-VLA** is a Vision-Language-Action (VLA) foundation model designed for robotic manipulation, emphasizing pragmatic deployment, efficiency, and strong generalization across tasks and platforms.
 
-**LingBot-VLA** has focused on **Pragmatic**:
-- **Large-scale Pre-training Data**: 20,000 hours of real-world
-data from 9 popular dual-arm robot configurations.
-- **Strong Performance**: Achieve clear superiority over competitors on simulation and real-world benchmarks.
-- **Training Efficiency**: Represent a 1.5 ∼ 2.8× (depending on the relied VLM base model) speedup over existing VLA-oriented codebases.
+- **Paper:** [A Pragmatic VLA Foundation Model](https://huggingface.co/papers/2601.18692)
+- **Repository:** [https://github.com/robbyant/lingbot-vla](https://github.com/robbyant/lingbot-vla)
+- **Project Page:** [https://technology.robbyant.com/lingbot-vla](https://technology.robbyant.com/lingbot-vla)
 
----
+## Highlights
 
-## Model Sources
-- Repository: https://github.com/robbyant/lingbot-vla
-- Paper: A Pragmatic VLA Foundation Model
-- Project Page: https://technology.robbyant.com/lingbot-vla
+- **Large-scale Pre-training Data**: Trained on 20,000 hours of real-world data from 9 popular dual-arm robot configurations.
+- **Strong Performance**: Achieves clear superiority over competitors on simulation and real-world benchmarks (GM-100 and RoboTwin 2.0).
+- **Training Efficiency**: Offers a 1.5 ~ 2.8× speedup over existing VLA-oriented codebases, ensuring it is well-suited for real-world deployment.
+
+---
 
 ## Related Models
 
-| Model Name | Huggingface | ModelScope | Description |
+| Model Name | Hugging Face | ModelScope | Description |
 | :--- | :---: | :---: | :---: |
 | LingBot-VLA-4B &nbsp; | [🤗 lingbot-vla-4b](https://huggingface.co/robbyant/lingbot-vla-4b) | [🤖 lingbot-vla-4b](https://modelscope.cn/models/Robbyant/lingbot-vla-4b) | LingBot-VLA *w/o* Depth|
 | LingBot-VLA-4B-Depth | [🤗 lingbot-vla-4b-depth](https://huggingface.co/robbyant/lingbot-vla-4b-depth) | [🤖 lingbot-vla-4b-depth](https://modelscope.cn/models/Robbyant/lingbot-vla-4b-depth) | LingBot-VLA *w/* Depth |
 
-
-
 ---
 
 ## Citation
@@ -46,4 +50,4 @@ This project is licensed under the [Apache-2.0 License](LICENSE).
 
 ## Acknowledgement
 
-This codebase is builded on the [VeOmni](https://arxiv.org/abs/2508.02317) project. Thanks for their excellent work!
+This codebase is built on the [VeOmni](https://arxiv.org/abs/2508.02317) and [LeRobot](https://github.com/huggingface/lerobot) projects. We thank the authors for their excellent work!