Update README.md

README.md

@@ -64,5 +64,18 @@ The model is a decoder-only transformer architecture with the following modifica
 * **ReLU Activation Function**: ReLU([Glorot et al., 2011](https://proceedings.mlr.press/v15/glorot11a/glorot11a.pdf)) activation functions are adopted in feed-forward networks.
 * **Tokenizer**: We use the SmolLM([Allal et al., 2024](https://huggingface.co/blog/smollm))'s tokenizer with a vocabulary size of 49,152. 
 
-## LICENSE
-* This repository is released under the [Apache-2.0](https://huggingface.co/mllmTeam/PhoneLM-1.5B-Instruct/blob/main/LICENSE) License. 
+## License
+* This repository is released under the [Apache-2.0](https://huggingface.co/mllmTeam/PhoneLM-1.5B-Instruct/blob/main/LICENSE) License.
+
+## Citation
+```
+@misc{yi2024phonelmanefficientcapablesmall,
+      title={PhoneLM:an Efficient and Capable Small Language Model Family through Principled Pre-training}, 
+      author={Rongjie Yi and Xiang Li and Weikai Xie and Zhenyan Lu and Chenghua Wang and Ao Zhou and Shangguang Wang and Xiwen Zhang and Mengwei Xu},
+      year={2024},
+      eprint={2411.05046},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2411.05046}, 
+}
+```