Add link to paper

This PR adds a link to the research paper [CraterBench-R: Instance-Level Crater Retrieval for Planetary Scale](https://huggingface.co/papers/2604.06245) to the dataset card.

README.md

@@ -1,22 +1,24 @@
 ---
 license: cc-by-4.0
+size_categories:
+- 10K<n<100K
 task_categories:
-  - image-to-image
-  - image-feature-extraction
-tags:
-  - mars
-  - crater
-  - retrieval
-  - remote-sensing
-  - planetary-science
-  - vision-transformer
+- image-to-image
+- image-feature-extraction
 pretty_name: CraterBench-R
-size_categories:
-  - 10K<n<100K
+tags:
+- mars
+- crater
+- retrieval
+- remote-sensing
+- planetary-science
+- vision-transformer
 ---
 
 # CraterBench-R
 
+[Paper](https://huggingface.co/papers/2604.06245)
+
 CraterBench-R is an instance-level crater retrieval benchmark built from Mars CTX imagery.
 
 This repository contains the released benchmark images, official split files, relevance metadata, and a minimal evaluation example.
@@ -151,4 +153,4 @@ python scripts/validate_release.py
 
 - Image paths in manifests are relative and portable.
 - `splits/test.json` is the official benchmark entrypoint.
-- `splits/train.json` is intended for training or fine-tuning experiments.
+- `splits/train.json` is intended for training or fine-tuning experiments.