Update README.md

README.md

@@ -25,7 +25,7 @@ IntentNet is trained through Supervised Fine-Tuning (SFT) to improve upon the ba
 - Label the AI intention with binary labels, which indicates whether the AI thought decevptive or not (0: non-deceptive, 1:deceptive).
 
 ## Links
-- [Paper]() - arXiv:
+- [Paper](https://arxiv.org/abs/2504.13707) - arXiv: 2504.13707[v3]
 - [GitHub Repository](https://github.com/Simoniracle/OpenDeception-Framework) - Source code and framework
 
 ## Usage
@@ -107,13 +107,13 @@ print(f"Intention-Deceptiveness: {label}")
   author={Wu, Yichen and Gao, Qianqian and Pan, Xudong and Hong, Geng and Yang, Min},
   journal={arXiv preprint arXiv:},
   year={2026},
-  url={}
+  url={https://arxiv.org/abs/2504.13707}
 }
 ```
 
 ## Details
 
-For more information, visit the [GitHub repository](https://github.com/Simoniracle/OpenDeception-Framework) or read the [paper]().
+For more information, visit the [GitHub repository](https://github.com/Simoniracle/OpenDeception-Framework) or read the [paper](https://arxiv.org/abs/2504.13707).
 
 ### Framework versions