How robust are discriminatively trained zero-shot learning models? This repository contains the PyTorch implementation of our paper How robust are dis

TextAttack 🐙 Generating adversarial examples for NLP models [TextAttack Documentation on ReadTheDocs] About • Setup • Usage • Design About TextAttack

Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and ap

⭐ [NEW] ⭐ T2F - 2.0 Teaser (coming soon ...) Please note that all the faces in the above samples are generated ones. The T2F 2.0 will be using MSG-GAN

Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder Authors: - Eashan Adhikarla - Dan Luo - Dr. Brian D. Davison Abstract Many

AMOS This repository contains the scripts for fine-tuning AMOS pretrained models on GLUE and SQuAD 2.0 benchmarks. Paper: Pretraining Text Encoders wi

Learning Transferable Adversarial Perturbations This is an official release of the paper Learning Transferable Adversarial Perturbations. The code is

Adversarial Training Against Location-Optimized Adversarial Patches arXiv | Paper | Code | Video | Slides Code for the paper: Sukrut Rao, David Stutz,

Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples This repository is the official implementation of "Tow

ARES This repository contains the code for ARES (Adversarial Robustness Evaluation for Safety), a Python library for adversarial machine learning rese

Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that