Update README.md

README.md

@@ -115,5 +115,21 @@ Our data processing pipeline is designed to construct a large-scale, high-qualit
 8. **Lip-sync**: Utilizes the SyncNet model to calculate confidence scores (LSE-C and LSE-D), discarding any samples with poor audio-visual alignment.
 9. **Audio feature & attribute labeling**: Extracts robust streaming features via Wav2Vec and annotates metadata including language, ethnicity, age, and gender.
 
+## 📚 Citation
+
+If you find our work useful in your research, please consider citing:
+
+```
+@misc{yu2026soulxflashheadoracleguidedgenerationinfinite,
+      title={SoulX-FlashHead: Oracle-guided Generation of Infinite Real-time Streaming Talking Heads}, 
+      author={Tan Yu and Qian Qiao and Le Shen and Ke Zhou and Jincheng Hu and Dian Sheng and Bo Hu and Haoming Qin and Jun Gao and Changhai Zhou and Shunshun Yin and Siyuan Liu},
+      year={2026},
+      eprint={2602.07449},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2602.07449}, 
+}
+```
+
 # License
 Our VividHead dataset is released under the CC-BY-4.0 license and is intended for research and non-commercial purposes. The video samples are collected from publicly available datasets.