Update README.md

README.md

@@ -22,7 +22,7 @@ This is a reward model used for PPO training trained on the Nectar 60k dataset.
 It was used to train [this](https://huggingface.co/allenai/tulu-v2.5-ppo-13b-nectar-60k) model.
 
 For more details, read the paper:
-[Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback](https://link.todo).
+[Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback](https://arxiv.org/abs/2406.09279).
 
 
 ## .Model description
@@ -76,6 +76,7 @@ If you find Tulu 2.5 is useful in your work, please cite it with:
       title={{Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback}}, 
       author={{Hamish Ivison and Yizhong Wang and Jiacheng Liu and Ellen Wu and Valentina Pyatkin and Nathan Lambert and Yejin Choi and Noah A. Smith and Hannaneh Hajishirzi}}
       year={2024},
+      eprint={2406.09279},
       archivePrefix={arXiv},
       primaryClass={cs.CL}
 }