docs: add arXiv paper link and BibTeX citation

README.md

@@ -15,6 +15,8 @@ prompt-alignment, temporal, persistence, and 13 physical-law sub-rubrics.
 Released alongside the companion dataset
 [`NU-World-Model-Embodied-AI/phyground`](https://huggingface.co/datasets/NU-World-Model-Embodied-AI/phyground).
 
+Paper: [PhyGround: Benchmarking Physical Reasoning in Generative World Models (arXiv:2605.10806)](https://arxiv.org/abs/2605.10806)
+
 The base model identifier required to attach this adapter is recorded in
 `adapter_config.json` (`base_model_name_or_path`); the inference script
 reads it automatically.
@@ -160,6 +162,20 @@ See the companion dataset
 [`NU-World-Model-Embodied-AI/phyground`](https://huggingface.co/datasets/NU-World-Model-Embodied-AI/phyground)
 for prompts, physical-law tags, and example videos.
 
+## Citation
+
+```bibtex
+@misc{lin2026phygroundbenchmarkingphysicalreasoning,
+      title={PhyGround: Benchmarking Physical Reasoning in Generative World Models},
+      author={Juyi Lin and Arash Akbari and Yumei He and Lin Zhao and Haichao Zhang and Arman Akbari and Xingchen Xu and Zoe Y. Lu and Enfu Nan and Hokin Deng and Edmund Yeh and Sarah Ostadabbas and Yun Fu and Jennifer Dy and Pu Zhao and Yanzhi Wang},
+      year={2026},
+      eprint={2605.10806},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2605.10806},
+}
+```
+
 ## License
 
 The base model is released by its respective authors; this LoRA adapter