Link dataset to paper and Github repository

README.md

@@ -1,8 +1,12 @@
 ---
 license: cc-by-4.0
+size_categories:
+- 10K<n<100K
 task_categories:
 - image-classification
 - image-segmentation
+- other
+pretty_name: Moonstone
 tags:
 - lunar
 - moon
@@ -10,9 +14,6 @@ tags:
 - multimodal
 - foundation-model
 - planetary-science
-pretty_name: Moonstone
-size_categories:
-- 10K<n<100K
 configs:
 - config_name: benchmark
   data_files: benchmark/*
@@ -22,7 +23,11 @@ configs:
 
 # Moonstone: A Multimodal Foundation Model Benchmark for Lunar Remote Sensing
 
-28-channel, 128 pixels-per-degree (~237 m/pixel) global multimodal lunar dataset assembled from
+This repository contains the dataset for the paper [Moonstone: A Multimodal Foundation Model and Benchmark for Lunar Remote Sensing](https://huggingface.co/papers/2607.03644).
+
+The official code is available at [GitHub](https://github.com/ayushprd/Moonstone).
+
+A 28-channel, 128 pixels-per-degree (~237 m/pixel) global multimodal lunar dataset assembled from
 seven instrument families across five missions (LRO WAC/LOLA/Diviner/Mini-RF, Chandrayaan-1 M3,
 GRAIL, Lunar Prospector GRS, Clementine). All channels are aligned to a common equirectangular
 grid (46,080 x 23,040 px, lunar sphere a=b=1,737,400 m) and organized into 7 physical modality
@@ -87,4 +92,4 @@ evaluation for all six tasks): <https://github.com/ayushprd/Moonstone>
 
 ## Provenance
 All data derived from public NASA PDS / USGS / ODE archives. Built via the 15-step pipeline in
-the Moonstone code repository (steps 01-15 + fix_minirf). Normalization: z-score, NaN->0 after norm.
+the Moonstone code repository (steps 01-15 + fix_minirf). Normalization: z-score, NaN->0 after norm.