Add link to paper

README.md

@@ -1,23 +1,25 @@
 ---
 language: en
 license: cc-by-4.0
+size_categories:
+- 10K<n<100K
 task_categories:
-  - image-to-image
-tags:
-  - object-centric-learning
-  - intervention-faithfulness
-  - CLEVR
-  - synthetic
-  - computer-vision
+- image-to-image
 pretty_name: EditCLEVR Phase 1
-size_categories:
-  - 10K<n<100K
+tags:
+- object-centric-learning
+- intervention-faithfulness
+- CLEVR
+- synthetic
+- computer-vision
 ---
 
 # EditCLEVR Phase 1
 
 EditCLEVR is a synthetic benchmark for evaluating **intervention faithfulness** in object-centric representations. Each example is a paired before/after scene where exactly one object-level factor may change.
 
+Paper: [EditCLEVR: A Paired-Scene Intervention Benchmark for Compositional Faithfulness of Object-Centric Representations](https://huggingface.co/papers/2607.22705)
+
 ## Dataset summary
 
 - **~20k paired edits** across six evaluation splits
@@ -89,4 +91,4 @@ If you use this dataset, please cite:
 
 > Anuraag Gadehothur Karnam and Tarunesh Sathish. *EditCLEVR: A Paired-Scene Intervention Benchmark for Compositional Faithfulness of Object-Centric Representations.* ICML 2026 Workshop on Combining Theory and Benchmarks: Towards A Virtuous Cycle to Understand and Guarantee Foundation Model Performance, 2026. Paper URL work in progress.
 
-See [`CITATION.cff`](https://github.com/torux-bughunter/EditCLEVR/blob/main/CITATION.cff) in the code repository.
+See [`CITATION.cff`](https://github.com/torux-bughunter/EditCLEVR/blob/main/CITATION.cff) in the code repository.