Add link to paper, task category

README.md

@@ -1,5 +1,7 @@
 ---
 license: apache-2.0
+task_categories:
+- image-classification
 ---
 
 # Dataset Card for Self-Bench
@@ -8,6 +10,8 @@ license: apache-2.0
 
 **Self-Bench** is a diagnostic benchmark designed to explore the relationship between the generative and discriminative capabilities of diffusion models. It consists of images generated by different diffusion models, enabling controlled evaluations where the image domain is well-defined and consistent. The goal is to assess how well models can understand images that are most "familiar" to them—that is, images they themselves have generated.
 
+This dataset was used in [Diffusion Classifiers Understand Compositionality, but Conditions Apply](https://huggingface.co/papers/2505.17955).
+
 ## Diffusion Models Used
 
 We use three popular versions of Stable Diffusion to generate the dataset:
@@ -30,4 +34,4 @@ Each image is annotated with:
 
 This repository contains the full dataset.  
 If you are looking for the filtered versions curated by three annotators, please visit our GitHub repository:
-🔗 [https://github.com/self-bench/-9793055367](https://github.com/self-bench/-9793055367)
+🔗 [https://github.com/eugene6923/Diffusion-Classifiers-Compositionality](https://github.com/eugene6923/Diffusion-Classifiers-Compositionality)