Added citation

README.md

@@ -10,13 +10,6 @@ size_categories:
 task_categories:
   - image-classification
   - image-segmentation
-citation: |
-  @inproceedings{rao2025,
-    title={Using Multiple Input Modalities can Improve Data‐Efficiency and O.O.D. Generalization for ML with Satellite Imagery},
-    author={Arjun Rao and Esther Rolf},
-    year={2025},
-    booktitle={Under Review},
-  }
 source_datasets:
   - SustainBench
   - USAVars
@@ -54,7 +47,7 @@ configs:
 ---
 
 
-## Geolayers-Data
+# Geolayers-Data
 <img src="osm_usavars.png" alt="Sample Geographic Inputs with the USAVars Dataset" width="800"/>
 
  -->
@@ -105,5 +98,19 @@ This dataset card contains usage instructions and metadata for all data-products
 ## Usage Instructions
 * Download the `.h5.gz` files in `data/<source dataset name>`. Our source datasets include SustainBench, USAVars, and BigEarthNet2.0
 * You may use pigz (https://linux.die.net/man/1/pigz) to decompress the archive. This is especially recommended for USAVars' train-split, which is 117 GB when uncompressed. This can be done with `pigz -d <.h5.gz>`
-* Datasets with auxiliary geographic inputs can be read with H5PY. 
----
+* Datasets with auxiliary geographic inputs can be read with H5PY.
+
+Citation:
+
+```
+@inproceedings{
+  rao2025using,
+  title={Using Multiple Input Modalities can Improve Data-Efficiency and O.O.D. Generalization for {ML} with Satellite Imagery},
+  author={Arjun Rao and Esther Rolf},
+  booktitle={TerraBytes - ICML 2025 workshop},
+  year={2025},
+  url={https://openreview.net/forum?id=p5nSQMPUyo}
+}
+```
+---
+