adversarial attack

Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior ICML 2024 Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization NeurIPS 2024 Enhancing adversarial robustness in Natural Language Inference using explanations EMNLP 2024 Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach NeurIPS 2024 Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning NeurIPS 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 Explicitly Perceiving and Preserving the Local Geometric Structures for 3D Point Cloud Attack AAAI 2024 Exploiting Class Probabilities for Black-box Sentence-level Attacks EACL 2024 Exploiting LLM Quantization NeurIPS 2024 Exploiting Positional Bias for Query-Agnostic Generative Content in Search ACL 2024 Exploring Adversarial Robustness of Vision Transformers in the Spectral Perspective WACV 2024 Extreme Miscalibration and the Illusion of Adversarial Robustness ACL 2024 Faithfulness and the Notion of Adversarial Sensitivity in NLP Explanations EMNLP 2024 Fast Adversarial Attacks on Language Models In One GPU Minute ICML 2024 Fast Reliability Estimation for Neural Networks with Adversarial Attack-Driven Importance Sampling UAI 2024 Feature-Level Adversarial Attacks and Ranking Disruption for Visible-Infrared Person Re-identification NeurIPS 2024 Finding a Needle in the Adversarial Haystack: A Targeted Paraphrasing Approach For Uncovering Edge Cases with Minimal Distribution Distortion EACL 2024 Fooling Polarization-Based Vision using Locally Controllable Polarizing Projection CVPR 2024 Fooling the Textual Fooler via Randomizing Latent Representations ACL 2024 From LLMs to MLLMs: Exploring the Landscape of Multimodal Jailbreaking EMNLP 2024 From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models NeurIPS 2024 Full-Distance Evasion of Pedestrian Detectors in the Physical World NeurIPS 2024 Fully Exploiting Every Real Sample: SuperPixel Sample Gradient Model Stealing CVPR 2024 Fusion Is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection ICLR 2024