Adversarial Learning

Certifying Fairness of Probabilistic Circuits AAAI 2023 CFA: Class-Wise Calibrated Fair Adversarial Training CVPR 2023 CodeAttack: Code-Based Adversarial Attacks for Pre-trained Programming Language Models AAAI 2023 COLA: Orchestrating Error Coding and Learning for Robust Neural Network Inference Against Hardware Defects ICML 2023 Combating Mode Collapse via Offline Manifold Entropy Estimation AAAI 2023 Combining Adversaries with Anti-adversaries in Training AAAI 2023 Competitive Physics Informed Networks ICLR 2023 Computational Asymmetries in Robust Classification ICML 2023 Content-based Unrestricted Adversarial Attack NeurIPS 2023 Contrastive Learning with Adversarial Examples for Alleviating Pathology of Language Model ACL 2023 Contrastive Self-Supervised Learning Leads to Higher Adversarial Susceptibility AAAI 2023 Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers ACL 2023 Converge to the Truth: Factual Error Correction via Iterative Constrained Editing AAAI 2023 Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets CVPR 2023 Cooperative and Adversarial Learning: Co-enhancing Discriminability and Transferability in Domain Adaptation AAAI 2023 CoopInit: Initializing Generative Adversarial Networks via Cooperative Learning AAAI 2023 Corrupting Neuron Explanations of Deep Visual Features ICCV 2023 Counterfactual Debiasing for Fact Verification ACL 2023 Cross-Entropy Loss Functions: Theoretical Analysis and Applications ICML 2023 CSTAR: Towards Compact and Structured Deep Neural Networks with Adversarial Robustness AAAI 2023 CUDA: Convolution-Based Unlearnable Datasets CVPR 2023 Data augmentation alone can improve adversarial training ICLR 2023 Deep Manifold Attack on Point Clouds via Parameter Plane Stretching AAAI 2023 Deep Perturbation Learning: Enhancing the Network Performance via Image Perturbations ICML 2023 Defending against Insertion-based Textual Backdoor Attacks via Attribution ACL 2023