Adversarial Learning

The Best Defense Is a Good Offense: Adversarial Augmentation Against Adversarial Attacks CVPR 2023 The Enemy of My Enemy Is My Friend: Exploring Inverse Adversaries for Improving Adversarial Training CVPR 2023 The Impacts of Unanswerable Questions on the Robustness of Machine Reading Comprehension Models EACL 2023 The Many Faces of Adversarial Machine Learning AAAI 2023 The multimarginal optimal transport formulation of adversarial multiclass classification JMLR 2023 Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness AISTATS 2023 There is more than one kind of robustness: Fooling Whisper with adversarial examples Interspeech 2023 The Test of Tests: A Framework for Differentially Private Hypothesis Testing ICML 2023 Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations ICML 2023 Toward Robust Diagnosis: A Contour Attention Preserving Adversarial Defense for COVID-19 Detection AAAI 2023 Towards Attack-tolerant Federated Learning via Critical Parameter Analysis ICCV 2023 Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks CVPR 2023 Towards Better Robustness against Common Corruptions for Unsupervised Domain Adaptation ICCV 2023 Towards Boosting the Open-Domain Chatbot with Human Feedback ACL 2023 Towards Building More Robust Models with Frequency Bias ICCV 2023 Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations CVPR 2023 Towards Efficient and Domain-Agnostic Evasion Attack with High-Dimensional Categorical Inputs AAAI 2023 Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly NeurIPS 2023 Towards Fairness-aware Adversarial Network Pruning ICCV 2023 Towards Imperceptible Document Manipulations against Neural Ranking Models ACL 2023 Towards Interpreting and Utilizing Symmetry Property in Adversarial Examples AAAI 2023 Towards More Robust Interpretation via Local Gradient Alignment AAAI 2023 Towards Optimal Randomized Strategies in Adversarial Example Game AAAI 2023 Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data ICML 2023 Towards Semantics- and Domain-Aware Adversarial Attacks IJCAI 2023