Update README.md

README.md

@@ -17,7 +17,9 @@ This model is for research and development only.
 
 ## References
 
-\[[Paper](https://arxiv.org/abs/2312.06709)\]\[[BibTex](#citing-radio)\]\[[GitHub examples](https://github.com/NVlabs/RADIO)\]
+\[[Paper](https://arxiv.org/abs/2312.06709)\]
+\[[PHI-S Paper](https://arxiv.org/abs/2410.01680)\]
+\[[BibTex](#citing-radio)\]\[[GitHub examples](https://github.com/NVlabs/RADIO)\]
 
 ## Model Architecture:
 **Architecture Type:** Neural Network  <br>
@@ -146,5 +148,18 @@ If you find this repository useful, please consider giving a star and citation:
 }
 ```
 
+```
+@misc{ranzinger2024phisdistributionbalancinglabelfree,
+      title={PHI-S: Distribution Balancing for Label-Free Multi-Teacher Distillation}, 
+      author={Mike Ranzinger and Jon Barker and Greg Heinrich and Pavlo Molchanov and Bryan Catanzaro and Andrew Tao},
+      year={2024},
+      eprint={2410.01680},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/2410.01680}, 
+}
+```
+
+
 # Ethical Considerations (For NVIDIA Models Only):
 NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications.  When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.