Improve dataset card

Hi! I'm Niels from the community science team at Hugging Face.

This PR improves the dataset card for Ego2Web by adding:
- Metadata for `task_categories` and `license`.
- Links to the paper, project page, and GitHub repository.
- A brief overview of the benchmark.
- The official BibTeX citation.

README.md

@@ -1,5 +1,28 @@
-Reproduce for CVRP 2026 paper Ego2Web: A Web Agent Benchmark Grounded in Egocentric Videos
-
 ---
 license: mit
+task_categories:
+- video-text-to-text
 ---
+
+# Ego2Web: A Web Agent Benchmark Grounded in Egocentric Videos
+
+[**Project Page**](https://ego2web.github.io/) | [**Paper**](https://huggingface.co/papers/2603.22529) | [**Code**](https://github.com/Yui010206/Ego2Web)
+
+Ego2Web is the first benchmark designed to bridge egocentric video perception and web agent execution. It pairs real-world first-person video recordings with web tasks that require visual understanding, web task planning, and interaction in an online environment for successful completion.
+
+The benchmark connects real-world human activities with web-based tasks, enabling research at the intersection of embodied perception and web interaction across diverse domains such as e-commerce, media retrieval, and knowledge lookup.
+
+## Citation
+
+If you find this work useful, please cite:
+
+```bibtex
+@article{yu2026ego2web,
+  title={Ego2Web: Benchmarking Web Agents with Egocentric Video Grounding},
+  author={Yu, Shoubin and Shu, Lei and Yang, Antoine and Fu, Yao and 
+          Sunkara, Srinivas and Wang, Maria and Chen, Jindong and 
+          Bansal, Mohit and Gong, Boqing},
+  journal={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  year={2026}
+}
+```