Update README with arXiv link and citation

README.md

@@ -19,6 +19,8 @@ The dataset targets open-world counting settings where the intended counting gra
 
 Companion generation pipeline code is available at [Verg-Avesta/KubriCount](https://github.com/Verg-Avesta/KubriCount).
 
+The paper is available at [arXiv](https://arxiv.org/abs/2605.10887).
+
 The released dataset can be used directly and does **not** require running the generation pipeline.
 
 ## Highlights
@@ -333,9 +335,22 @@ The generation pipeline is released separately at [Verg-Avesta/KubriCount](https
 
 That repository contains the Kubric-based rendering code, asset preprocessing utilities, image-editing scripts, and VLM-filtering scripts used to construct KubriCount. It is only needed if you want to reproduce or extend the data generation pipeline.
 
+## Paper
+
+The paper is available at [arXiv](https://arxiv.org/abs/2605.10887).
+
 ## Citation
 
-The manuscript and citation will be updated when publicly available.
+If you find this dataset useful, please cite:
+
+```bibtex
+@article{liu2026count,
+  title={Count Anything at Any Granularity},
+  author={Liu, Chang and Wu, Haoning and Xie, Weidi},
+  journal={arXiv preprint arXiv:2605.10887},
+  year={2026}
+}
+```
 
 ## Acknowledgements