Update dataset card with paper info, project page, and GitHub link

README.md

@@ -9,7 +9,13 @@ configs:
   data_files: data/*/*.parquet
 ---
 
-This dataset was exported from Robometer processed datasets in LeRobot v3 format.
+# Robometer: RBM-1M-OOD
+
+[**Project Page**](https://robometer.github.io/) | [**Paper**](https://huggingface.co/papers/2603.02115) | [**GitHub**](https://github.com/robometer/robometer)
+
+RBM-1M is a large-scale reward-learning dataset comprising over one million trajectories spanning diverse robot embodiments and tasks. It includes substantial suboptimal and failure data to support the training of general-purpose robotic reward models. 
+
+This specific repository contains the **Out-of-Distribution (OOD)** subset of the RBM-1M dataset, exported in the **LeRobot v3** format for evaluation purposes.
 
 <a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=robometer/rbm-1m-ood">
 <img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl.svg"/>
@@ -132,3 +138,14 @@ This dataset was exported from Robometer processed datasets in LeRobot v3 format
     }
 }
 ```
+
+## Citation
+
+```bibtex
+@inproceedings{liang2026robometer,
+  title     = {Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons},
+  author={Anthony Liang and Yigit Korkmaz and Jiahui Zhang and Minyoung Hwang and Abrar Anwar and Sidhant Kaushik and Aditya Shah and Alex S. Huang and Luke Zettlemoyer and Dieter Fox and Yu Xiang and Anqi Li and Andreea Bobu and Abhishek Gupta and Stephen Tu and Erdem Biyik and Jesse Zhang},
+  year={2026},
+  booktitle={Robotics: Science and Systems 2026},
+}
+```