adversarial sample

R-AT: Regularized Adversarial Training for Natural Language Understanding EMNLP 2022 Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP EMNLP 2022 BASAR:Black-Box Attack on Skeletal Action Recognition CVPR 2021 Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints AAAI 2021 Improving the Transferability of Adversarial Samples With Adversarial Transformations CVPR 2021 Language Model Augmented Relevance Score ACL 2021 BERT-ATTACK: Adversarial Attack Against BERT Using BERT EMNLP 2020 Boosting the Transferability of Adversarial Samples via Attention CVPR 2020 GreedyFool: Distortion-Aware Sparse Adversarial Attack NeurIPS 2020 Investigating Robustness of Adversarial Samples Detection for Automatic Speaker Verification Interspeech 2020 LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud Based Deep Networks CVPR 2020 Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning AAAI 2020 Cross-Modal Learning with Adversarial Samples NeurIPS 2019 Improving the Robustness of Deep Reading Comprehension Models by Leveraging Syntax Prior EMNLP 2019 Once a MAN: Towards Multi-Target Attack via Learning Multi-Target Adversarial Network Once ICCV 2019 Resisting Adversarial Attacks Using Gaussian Mixture Variational Autoencoders AAAI 2019 Deep Text Classification Can be Fooled IJCAI 2018