Add task category and link to paper

README.md

@@ -1,4 +1,13 @@
 ---
+license: cc-by-4.0
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- earth-observation
+- earth-science
+- remote-sensing
 dataset_info:
   features:
   - name: file_path
@@ -28,10 +37,12 @@ configs:
   data_files:
   - split: train
     path: data/train-*
-license: cc-by-4.0
 ---
+
 # EVE-Corpus
 
+[**Paper**](https://huggingface.co/papers/2604.13071) | [**GitHub**](https://github.com/eve-esa)
+
 EVE-Corpus is a large-scale, cleaned, and anonymized text corpus of Earth Observation (EO) documents formatted in Markdown.  
 It is designed to support research in EO and domain-specific LLM training.
 
@@ -144,12 +155,12 @@ Attributions to the original authors can be found in the [attribution.txt](attri
 If you use this project in academic or research settings, please cite:
 ```
 @misc{atrio2026evedomainspecificllmframework,
-      title={{EVE}: A Domain-Specific {LLM} Framework for Earth Intelligence}, 
-      author={Àlex R. Atrio and Antonio Lopez and Jino Rohit and Yassine El Ouahidi and Marcello Politi and Vijayasri Iyer and Umar Jamil and Sébastien Bratières and Nicolas Longépé},
-      year={2026},
-      eprint={2604.13071},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL},
-      url={https://arxiv.org/abs/2604.13071}, 
+      title={{EVE}: A Domain-Specific {LLM} Framework for Earth Intelligence}, 
+      author={Àlex R. Atrio and Antonio Lopez and Jino Rohit and Yassine El Ouahidi and Marcello Politi and Vijayasri Iyer and Umar Jamil and Sébastien Bratières and Nicolas Longépé},
+      year={2026},
+      eprint={2604.13071},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2604.13071}, 
 }
 ```