Adversarial Learning

Towards Stable and Efficient Adversarial Training against l_1 Bounded Adversarial Attacks ICML 2023 Towards Transferable Targeted Adversarial Examples CVPR 2023 Towards Verifying the Geometric Robustness of Large-Scale Neural Networks AAAI 2023 Towards Viewpoint-Invariant Visual Recognition via Adversarial Training ICCV 2023 Tracing the Origin of Adversarial Attack for Forensic Investigation and Deterrence ICCV 2023 Tractable and Near-Optimal Adversarial Algorithms for Robust Estimation in Contaminated Gaussian Models JMLR 2023 Trade-Off Between Robustness and Accuracy of Vision Transformers CVPR 2023 Training Meta-Surrogate Model for Transferable Adversarial Attack AAAI 2023 Training on Foveated Images Improves Robustness to Adversarial Attacks NeurIPS 2023 Training-Time Attacks against K-nearest Neighbors AAAI 2023 Transferable Adversarial Attack for Both Vision Transformers and Convolutional Networks via Momentum Integrated Gradients ICCV 2023 Transferable Adversarial Attacks on Vision Transformers With Token Gradient Regularization CVPR 2023 Transferable Unlearnable Examples ICLR 2023 Transformer-Based Named Entity Recognition for French Using Adversarial Adaptation to Similar Domain Corpora (Student Abstract) AAAI 2023 Treatment Learning Causal Transformer for Noisy Image Classification WACV 2023 TRM-UAP: Enhancing the Transferability of Data-Free Universal Adversarial Perturbation via Truncated Ratio Maximization ICCV 2023 TrojanSQL: SQL Injection against Natural Language Interface to Database EMNLP 2023 TrojDiff: Trojan Attacks on Diffusion Models With Diverse Targets CVPR 2023 TrojViT: Trojan Insertion in Vision Transformers CVPR 2023 T-SEA: Transfer-Based Self-Ensemble Attack on Object Detection CVPR 2023 Turning Strengths Into Weaknesses: A Certified Robustness Inspired Attack Framework Against Graph Neural Networks CVPR 2023 TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization CVPR 2023 UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction MLHC 2023 Uncovering Adversarial Risks of Test-Time Adaptation ICML 2023 Understanding and Defending Patched-based Adversarial Attacks for Vision Transformer ICML 2023