classifier robustness

Doppelgangers and Adversarial Vulnerability CVPR 2025 DiffAug: A Diffuse-and-Denoise Augmentation for Training Robust Classifiers NeurIPS 2024 VertAttack: Taking Advantage of Text Classifiers’ Horizontal Vision NAACL 2024 Auditing and Robustifying COVID-19 Misinformation Datasets via Anticontent Sampling AAAI 2023 Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation EMNLP 2023 A Manifold View of Adversarial Risk AISTATS 2022 ART-Point: Improving Rotation Robustness of Point Cloud Classifiers via Adversarial Rotation CVPR 2022 Learning Stable Classifiers by Transferring Unstable Features ICML 2022 Self-Healing Robust Neural Networks via Closed-Loop Control JMLR 2022 Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators’ Disagreement EMNLP 2021 Robustness between the worst and average case NeurIPS 2021 Do Models of Mental Health Based on Social Media Data Generalize? EMNLP 2020 SAM: The Sensitivity of Attribution Methods to Hyperparameters CVPR 2020 Are adversarial examples inevitable? ICLR 2019 Metric Learning for Adversarial Robustness NeurIPS 2019 Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution NeurIPS 2018 Adversarial vulnerability for any classifier NeurIPS 2018 Masking: A New Perspective of Noisy Supervision NeurIPS 2018 Robustness of classifiers to uniform ℓ_p and Gaussian noise AISTATS 2018 Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation NeurIPS 2017 Robustness of classifiers: from adversarial to random noise NeurIPS 2016