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README.md

@@ -1,11 +1,68 @@
 ---
 library_name: XTransferBench
+license: mit
+pipeline_tag: zero-shot-classification
 tags:
-- model_hub_mixin
+- not-for-all-audiences
 - pytorch_model_hub_mixin
+- model_hub_mixin
+---
+
+
+# X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
+<div align="center">
+  <a href="https://" target="_blank"><img src="https://img.shields.io/badge/arXiv-b5212f.svg?logo=arxiv" alt="arXiv"></a>
+</div>
+
+Baseline attacker [GD-UAP](https://arxiv.org/abs/1801.08092) used ICML2025 paper ["X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP"](https://)
+
+---
+
+## X-TransferBench
+X-TransferBench is an open-source benchmark that provides a comprehensive collection of UAPs/TUAPs capable of achieving universal adversarial transferability. These UAPs can simultaneously **transfer across data, domains, models**, and **tasks**. Essentially, they represent perturbations that can transform any sample into an adversarial example, effective against any model and for any task.
+
+## Model Details
+
+- Surrogate Model: ResNet
+- Surrogate Dataset: 
+- Threat Model: L_inf_eps=12/255
+- Perturbation Size: 3 x 224 x 224
+
+---
+## Model Usage
+
+```python
+from XTransferBench import attacker
+
+attacker = XTransferBench.zoo.load_attacker("linf_non_targeted", "gd_uap_resnet_with_data")
+images = # torch.Tensor [b, 3, h, w], values should be between 0 and 1
+adv_images = attacker(images) # adversarial examples
+```
+
 ---
 
-This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
-- Code: [More Information Needed]
-- Paper: [More Information Needed]
-- Docs: [More Information Needed]
+## Citation
+If you use this model in your work, please cite the accompanying paper:
+
+
+```
+@article{mopuri2018generalizable,
+  title={Generalizable data-free objective for crafting universal adversarial perturbations},
+  author={Mopuri, Konda Reddy and Ganeshan, Aditya and Babu, R Venkatesh},
+  journal={TPAMI},
+  year={2018},
+}
+```
+
+
+```
+@inproceedings{
+huang2025xtransfer,
+title={X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP},
+author={Hanxun Huang and Sarah Erfani and Yige Li and Xingjun Ma and James Bailey},
+booktitle={ICML},
+year={2025},
+}
+
+```
+