Update README.md

README.md

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 license: mit
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-**ALMA** (**A**dvanced **L**anguage **M**odel-based tr**A**nslator) is an LLM-based translation model, which adopts a new translation model paradigm: it begins with fine-tuning on monolingual data and is further optimized using high-quality parallel data. This two-step fine-tuning process ensures superior translation accuracy and performance.
-
+**ALMA** (**A**dvanced **L**anguage **M**odel-based tr**A**nslator) is an LLM-based translation model, which adopts a new translation model paradigm: it begins with fine-tuning on monolingual data and is further optimized using high-quality parallel data. This two-step fine-tuning process ensures strong translation performance. 
+Please find more details in our [paper](https://arxiv.org/abs/2309.11674).
+```
+@misc{xu2023paradigm,
+      title={A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models}, 
+      author={Haoran Xu and Young Jin Kim and Amr Sharaf and Hany Hassan Awadalla},
+      year={2023},
+      eprint={2309.11674},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
 We release four translation models presented in the paper:
 - **ALMA-7B**: Full-weight Fine-tune LLaMA-2-7B on 20B monolingual tokens and then **Full-weight** fine-tune on human-written parallel data
 - **ALMA-7B-LoRA**: Full-weight Fine-tune LLaMA-2-7B on 20B monolingual tokens and then **LoRA** fine-tune on human-written parallel data