Update README.md

README.md

@@ -8,9 +8,19 @@ The **accuracy** reaches 80%, and **F1 score** is 79%. Both are much higher than
 Due to the fact that the output values are continuous, it is better to use mean squared errors (MSE) or mean absolute error (MAE) to evaluate the model's performance. 
 When both metrics are smaller, it indciates that the model performs better. Our models performance: **MSE: 0.07**, **MAE: 0.14**.
 
-Please **cite**: "Wang, R., and Sun, K. 2024. Personality Detection Models with Continuous Ouput Values Trained by Mixed Strategies" if you use this model.
-
-The project of predicting human cognition and emotoon, and training details are available at: https://github.com/fivehills/detecting_personality
+Please **cite**: 
+
+```
+article{wang2024personality,
+  title={Continuous Output Personality Detection Models via Mixed Strategy Training},
+  author={Rong Wang, Kun Sun},
+  year={2024},
+  journal={ArXiv},
+  url={https://arxiv.org/abs/2406.16223}
+}
+```
+
+The project of predicting human cognition and emotion, and training details are available at: https://github.com/fivehills/detecting_personality
 
 The following provides the code to implement the task of detecting personality from an input text.