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Robustness

529 directly classified papers

Papers per year

Papers

ImageNet-D: Benchmarking Neural Network Robustness on Diffusion Synthetic Object CVPR 2024
PAD: Patch-Agnostic Defense against Adversarial Patch Attacks CVPR 2024
Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation CVPR 2024
MaxEnt Loss: Constrained Maximum Entropy for Calibration under Out-of-Distribution Shift AAAI 2024
DAP: A Dynamic Adversarial Patch for Evading Person Detectors CVPR 2024
Navigate Beyond Shortcuts: Debiased Learning Through the Lens of Neural Collapse CVPR 2024
UMA: Facilitating Backdoor Scanning via Unlearning-Based Model Ablation AAAI 2024
A Subspace-Constrained Tyler's Estimator and its Applications to Structure from Motion CVPR 2024
1-Lipschitz Layers Compared: Memory Speed and Certifiable Robustness CVPR 2024
Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models CVPR 2024
Benchmarking Segmentation Models with Mask-Preserved Attribute Editing CVPR 2024
“Flex Tape Can’t Fix That”: Bias and Misinformation in Edited Language Models EMNLP 2024
Attacking CNNs in Histopathology with SNAP: Sporadic and Naturalistic Adversarial Patches (Student Abstract) AAAI 2024
Defog Artificial Intelligence Glasses: Neural Networks for the Imperfect Real World AAAI 2024
Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning NIPS 2024
VeriCompress: A Tool to Streamline the Synthesis of Verified Robust Compressed Neural Networks from Scratch AAAI 2024
A Dual Stealthy Backdoor: From Both Spatial and Frequency Perspectives AAAI 2024
Data-Driven Discovery of Design Specifications (Student Abstract) AAAI 2024
Data-Free Hard-Label Robustness Stealing Attack AAAI 2024
Consistency and Uncertainty: Identifying Unreliable Responses From Black-Box Vision-Language Models for Selective Visual Question Answering CVPR 2024
Solving Non-rectangular Reward-Robust MDPs via Frequency Regularization AAAI 2024
Fostering Trustworthiness in Machine Learning Algorithms AAAI 2024
Robust Active Measuring under Model Uncertainty AAAI 2024
Towards Trustworthy Deep Learning AAAI 2024
Agnostic Multi-Robust Learning using ERM AISTATS 2024