Adversarial Learning

Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM ACL 2024 Defending Against Backdoor Attacks by Layer-wise Feature Analysis (Extended Abstract) IJCAI 2024 Defending Jailbreak Prompts via In-Context Adversarial Game EMNLP 2024 Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization ACL 2024 Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization CVPR 2024 Defense Against Adversarial Cloud Attack on Remote Sensing Salient Object Detection WACV 2024 Detection Defenses: An Empty Promise Against Adversarial Patch Attacks on Optical Flow WACV 2024 Detector Collapse: Backdooring Object Detection to Catastrophic Overload or Blindness in the Physical World IJCAI 2024 DiffAM: Diffusion-based Adversarial Makeup Transfer for Facial Privacy Protection CVPR 2024 DiffHammer: Rethinking the Robustness of Diffusion-Based Adversarial Purification NeurIPS 2024 Diffusion Models are Certifiably Robust Classifiers NeurIPS 2024 Diffusion Models Meet Image Counter-Forensics WACV 2024 Distract Large Language Models for Automatic Jailbreak Attack EMNLP 2024 DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution UAI 2024 DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLMs Jailbreakers EMNLP 2024 Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability AISTATS 2024 Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization NeurIPS 2024 Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation ICLR 2024 Evaluating the Instruction-Following Robustness of Large Language Models to Prompt Injection EMNLP 2024 Evaluating the Validity of Word-level Adversarial Attacks with Large Language Models ACL 2024 Everyday Object Meets Vision-and-Language Navigation Agent via Backdoor NeurIPS 2024 Exploring Adversarial Robustness of Deep State Space Models NeurIPS 2024 FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks AAAI 2024 Fast Reliability Estimation for Neural Networks with Adversarial Attack-Driven Importance Sampling UAI 2024 Fast Stealthily Biased Sampling Using Sliced Wasserstein Distance ACML 2024