Update README.md

README.md

@@ -6,4 +6,38 @@ datasets:
 - ILSVRC/imagenet-1k
 tags:
 - Adversarial Robustness
----
+---
+
+# MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly Mixed Classifiers
+
+This is the official model repository of the preprint paper \
+*[MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly Mixed Classifiers](https://arxiv.org/abs/2402.02263)* \
+by [Yatong Bai](https://bai-yt.github.io), [Mo Zhou](https://cdluminate.github.io), [Vishal M. Patel](https://engineering.jhu.edu/faculty/vishal-patel), and [Somayeh Sojoudi](https://www2.eecs.berkeley.edu/Faculty/Homepages/sojoudi.html).
+
+**TL;DR:** MixedNUTS balances clean data classification accuracy and adversarial robustness without additional training
+via a mixed classifier with nonlinear base model logit transformations.
+
+Here, we provide the download links to the standard base classifiers used in the main results.
+| Dataset | Link |
+|-----------|-------|
+| CIFAR-10 | [Download](https://huggingface.co/Bai-YT/MixedNUTS/resolve/main/cifar10_std_rn152.pt?download=true) |
+| CIFAR-100 | [Download](https://huggingface.co/Bai-YT/MixedNUTS/resolve/main/cifar100_std_rn152.pt?download=true) |
+| ImageNet | [Download](https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_large_22k_224_ema.pt) |
+
+For code and detailed usage, please refer to our [GitHub repository](https://github.com/Bai-YT/MixedNUTS).
+
+<center>
+<img src=“main_figure.png” alt=“MixedNUTS Results” title=“Results” width=“800"/>
+</center>
+
+
+#### Citing our work (BibTeX)
+
+```bibtex
+@article{MixedNUTS,
+title={MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly Mixed Classifiers},
+author={Bai, Yatong and Zhou, Mo and Patel, Vishal M. and Sojoudi, Somayeh},
+journal={arXiv preprint arXiv:2402.02263},
+year={2024}
+}
+```