Update README.md

Author: zimmer-m

README.md

@@ -1,8 +1,8 @@
-## On the Byzantine-Resilience of Distillation-Based Federated Learning
+## [ICLR25] On the Byzantine-Resilience of Distillation-Based Federated Learning
 
 *Authors: [Christophe Roux](http://christopheroux.de/), [Max Zimmer](https://maxzimmer.org/), [Sebastian Pokutta](http://www.pokutta.com/)*
 
-This repository contains the code to reproduce the experiments from the paper ["On the Byzantine-Resilience of Distillation-Based Federated Learning"](https://arxiv.org/abs/2402.12265).
+This repository contains the code to reproduce the experiments from the ICLR25 paper ["On the Byzantine-Resilience of Distillation-Based Federated Learning"](https://arxiv.org/abs/2402.12265).
 The code is based on [PyTorch 1.9](https://pytorch.org/) and the experiment-tracking platform [Weights & Biases](https://wandb.ai).
 
 ### Structure and Usage
@@ -31,10 +31,11 @@ Define the parameters in the [`main.py`](main.py) defaults-dictionary and run it
 In case you find the paper or the implementation useful for your own research, please consider citing:
 
 ```
-@article{roux2024byzantine,
-  author = {Roux, Christophe and Zimmer, Max and Pokutta, Sebastian},
-  title = {On the Byzantine-Resilience of Distillation-Based Federated Learning},
-  year = {2024},
-  journal = {arXiv preprint arXiv:2402.12265},
+@inproceedings{roux2025on,
+title={On the Byzantine-Resilience of Distillation-Based Federated Learning},
+author={Christophe Roux and Max Zimmer and Sebastian Pokutta},
+booktitle={The Thirteenth International Conference on Learning Representations},
+year={2025},
+url={https://openreview.net/forum?id=of6EuHT7de}
 }
 ```