"adversarial attacks" Papers
53 papers found • Page 1 of 2
Adversary Aware Optimization for Robust Defense
Daniel Wesego, Pedram Rooshenas
Bits Leaked per Query: Information-Theoretic Bounds for Adversarial Attacks on LLMs
Masahiro Kaneko, Timothy Baldwin
Bridging Symmetry and Robustness: On the Role of Equivariance in Enhancing Adversarial Robustness
Longwei Wang, Ifrat Ikhtear Uddin, Prof. KC Santosh (PhD) et al.
DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches
Yun Xing, Yue Cao, Nhat Chung et al.
Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks
Steffen Schotthöfer, Lexie Yang, Stefan Schnake
Fit the Distribution: Cross-Image/Prompt Adversarial Attacks on Multimodal Large Language Models
Hai Yan, Haijian Ma, Xiaowen Cai et al.
IPAD: Inverse Prompt for AI Detection - A Robust and Interpretable LLM-Generated Text Detector
Zheng CHEN, Yushi Feng, Jisheng Dang et al.
Jailbreaking Multimodal Large Language Models via Shuffle Inconsistency
Shiji Zhao, Ranjie Duan, Fengxiang Wang et al.
MIP against Agent: Malicious Image Patches Hijacking Multimodal OS Agents
Lukas Aichberger, Alasdair Paren, Guohao Li et al.
MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
Ping Guo, Cheng Gong, Fei Liu et al.
Stochastic Regret Guarantees for Online Zeroth- and First-Order Bilevel Optimization
Parvin Nazari, Bojian Hou, Davoud Ataee Tarzanagh et al.
Towards Certification of Uncertainty Calibration under Adversarial Attacks
Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz et al.
Virus Infection Attack on LLMs: Your Poisoning Can Spread "VIA" Synthetic Data
Zi Liang, Qingqing Ye, Xuan Liu et al.
$\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts
Guanjie Chen, Xinyu Zhao, Tianlong Chen et al.
Adv-Diffusion: Imperceptible Adversarial Face Identity Attack via Latent Diffusion Model
Decheng Liu, Xijun Wang, Chunlei Peng et al.
Adversarial Attacks on the Interpretation of Neuron Activation Maximization
Géraldin Nanfack, Alexander Fulleringer, Jonathan Marty et al.
Adversarially Robust Deep Multi-View Clustering: A Novel Attack and Defense Framework
Haonan Huang, Guoxu Zhou, Yanghang Zheng et al.
Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents
Chung-En Sun, Sicun Gao, Lily Weng
Comparing the Robustness of Modern No-Reference Image- and Video-Quality Metrics to Adversarial Attacks
Anastasia Antsiferova, Khaled Abud, Aleksandr Gushchin et al.
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks
Shashank Agnihotri, Steffen Jung, Margret Keuper
DataFreeShield: Defending Adversarial Attacks without Training Data
Hyeyoon Lee, Kanghyun Choi, Dain Kwon et al.
Enhancing Adversarial Robustness in SNNs with Sparse Gradients
Yujia Liu, Tong Bu, Ding Jianhao et al.
Exploring Vulnerabilities in Spiking Neural Networks: Direct Adversarial Attacks on Raw Event Data
Yanmeng Yao, Xiaohan Zhao, Bin Gu
Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions
Jon Vadillo, Roberto Santana, Jose A Lozano
Fast Adversarial Attacks on Language Models In One GPU Minute
Vinu Sankar Sadasivan, Shoumik Saha, Gaurang Sriramanan et al.
Graph Neural Network Explanations are Fragile
Jiate Li, Meng Pang, Yun Dong et al.
Improved Dimensionality Dependence for Zeroth-Order Optimisation over Cross-Polytopes
Weijia Shao
IOI: Invisible One-Iteration Adversarial Attack on No-Reference Image- and Video-Quality Metrics
Ekaterina Shumitskaya, Anastasia Antsiferova, Dmitriy Vatolin
Lyapunov-Stable Deep Equilibrium Models
Haoyu Chu, Shikui Wei, Ting Liu et al.
Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution
Eslam Zaher, Maciej Trzaskowski, Quan Nguyen et al.
MathAttack: Attacking Large Language Models towards Math Solving Ability
Zihao Zhou, Qiufeng Wang, Mingyu Jin et al.
MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models
Xin Liu, Yichen Zhu, Jindong Gu et al.
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
Yihao Zhang, Hangzhou He, Jingyu Zhu et al.
Rethinking Adversarial Robustness in the Context of the Right to be Forgotten
Chenxu Zhao, Wei Qian, Yangyi Li et al.
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data
Rui Miao, Kaixiong Zhou, Yili Wang et al.
Revisiting Character-level Adversarial Attacks for Language Models
Elias Abad Rocamora, Yongtao Wu, Fanghui Liu et al.
RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content
Zhuowen Yuan, Zidi Xiong, Yi Zeng et al.
Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
Christian Schlarmann, Naman Singh, Francesco Croce et al.
Robust Communicative Multi-Agent Reinforcement Learning with Active Defense
Lebin Yu, Yunbo Qiu, Quanming Yao et al.
Robustness Tokens: Towards Adversarial Robustness of Transformers
Brian Pulfer, Yury Belousov, Slava Voloshynovskiy
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models
Yongshuo Zong, Ondrej Bohdal, Tingyang Yu et al.
SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding
Chanho Park, Namyoon Lee
Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs
Dongjin Lee, Juho Lee, Kijung Shin
SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization
Xixu Hu, Runkai Zheng, Jindong Wang et al.
Stealthy Adversarial Attacks on Stochastic Multi-Armed Bandits
Zhiwei Wang, Hongning Wang, Huazheng Wang
The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks
Ziquan Liu, Yufei Cui, Yan Yan et al.
Towards Robust Image Stitching: An Adaptive Resistance Learning against Compatible Attacks
Zhiying Jiang, Xingyuan Li, Jinyuan Liu et al.
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
Ye Tian, Haolei Weng, Yang Feng
Trustworthy Actionable Perturbations
Jesse Friedbaum, Sudarshan Adiga, Ravi Tandon
Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection
Nils Palumbo, Yang Guo, Xi Wu et al.