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README.md

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 **Behavior-Skill** is a skill-centric dataset and evaluation benchmark built on [BEHAVIOR-1K](https://behavior.stanford.edu/) for Vision-Language-Action (VLA) policies in long-horizon mobile manipulation tasks. It establishes executable constituent skills as the fundamental unit for both policy learning and evaluation.
 
-**Paper:** Coming soon  |  **Code:** [GitHub](https://github.com/mafangniu/Behavior-Skill)
+**Paper:** [arXiv](https://arxiv.org/abs/2608.30536)  |  **Code:** [GitHub](https://github.com/mafangniu/Behavior-Skill)
 
 Behavior-Skill contains **235,492 skill instances** constructed from **10,000 demonstrations** across **50 household tasks** and **34 semantic skill categories**. Each annotated instance contains a skill instruction and its aligned frame interval in the corresponding BEHAVIOR-1K demonstration. For **500 evaluation demonstrations** (10 per task), the release additionally provides per-skill BDDL success conditions and restorable OmniGibson states for independent closed-loop evaluation.
 
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 ## Citation
 
-Citation information for the Behavior-Skill paper will be added once the paper becomes publicly available. In the meantime, please cite the dataset using [CITATION.cff](CITATION.cff).
+If you find Behavior-Skill useful in your research, please cite our paper:
+```bibtex
+@article{ma2026behaviorskill,
+  title   = {{Behavior-Skill}: A Fine-Grained Benchmark for Evaluating Vision-Language-Action Policies in Long-Horizon Tasks},
+  author  = {Ma, Chunyun and Luo, Lun and Luo, Xingjian and Feng, Xiexing and Zhang, Hang and Liu, Wei and Qiao, Feng and Wang, Yaonan and Lu, Huimin and Chen, Xieyuanli},
+  journal = {arXiv preprint arXiv:2608.30536},
+  year    = {2026},
+  url     = {https://arxiv.org/abs/2608.30536}
+}
+```
 
 Please also cite the original BEHAVIOR-1K benchmark: