adversarial robustness

LyaNet: A Lyapunov Framework for Training Neural ODEs ICML 2022 Masking Adversarial Damage: Finding Adversarial Saliency for Robust and Sparse Network CVPR 2022 Measure and Improve Robustness in NLP Models: A Survey NAACL 2022 Metric-Fair Active Learning ICML 2022 MIA-Former: Efficient and Robust Vision Transformers via Multi-Grained Input-Adaptation AAAI 2022 MockingBERT: A Method for Retroactively Adding Resilience to NLP Models COLING 2022 Modeling Adversarial Noise for Adversarial Training ICML 2022 MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples NeurIPS 2022 Neuro-Symbolic Verification of Deep Neural Networks IJCAI 2022 Node Feature Kernels Increase Graph Convolutional Network Robustness AISTATS 2022 Non-Uniform Adversarially Robust Pruning AutoML 2022 On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles CVPR 2022 On Distributionally Robust Optimization and Data Rebalancing AISTATS 2022 On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds AISTATS 2022 Online Evasion Attacks on Recurrent Models:The Power of Hallucinating the Future IJCAI 2022 On Robust Multiclass Learnability NeurIPS 2022 On the Adversarial Robustness of Causal Algorithmic Recourse ICML 2022 On the Adversarial Robustness of Mixture of Experts NeurIPS 2022 On the Limitations of Stochastic Pre-processing Defenses NeurIPS 2022 On the Robustness of Offensive Language Classifiers ACL 2022 On the Sensitivity and Stability of Model Interpretations in NLP ACL 2022 Personalized Federated Learning towards Communication Efficiency, Robustness and Fairness NeurIPS 2022 Perturbation type categorization for multiple adversarial perturbation robustness UAI 2022 Phrase-level Textual Adversarial Attack with Label Preservation NAACL 2022 PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures CVPR 2022