Cover Image

Boosting Adversarial Transferability via Ensemble Non-Attention

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zou, Yipeng, Liu, Qin, Wu, Jie, Peng, Yu, Chen, Guo, Zhou, Hui, Ye, Guanghui
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Boosting Adversarial Transferability via Residual Perturbation Attack
by: Peng, Jinjia, et al.
Published: (2025)

Bag of Tricks to Boost Adversarial Transferability
by: Zhang, Zeliang, et al.
Published: (2024)

Strong Transferable Adversarial Attacks via Ensembled Asymptotically Normal Distribution Learning
by: Fang, Zhengwei, et al.
Published: (2022)

Attention Transfer Is Not Universally Effective for Vision Transformers
by: Qin, Huaiyuan, et al.
Published: (2026)

Boosting Adversarial Transferability with Spatial Adversarial Alignment
by: Chen, Zhaoyu, et al.
Published: (2025)

Boosting Adversarial Transferability Against Defenses via Multi-Scale Transformation
by: Guo, Zihong, et al.
Published: (2025)

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples
by: Li, Jian-Wei, et al.
Published: (2025)

Improving Adversarial Transferability in MLLMs via Dynamic Vision-Language Alignment Attack
by: Gu, Chenhe, et al.
Published: (2025)

Boosting Imperceptibility of Stable Diffusion-based Adversarial Examples Generation with Momentum
by: Haque, Nashrah, et al.
Published: (2024)

Improving the Transferability of Adversarial Examples by Inverse Knowledge Distillation
by: Wu, Wenyuan, et al.
Published: (2025)

Boosting Adversarial Transferability via Commonality-Oriented Gradient Optimization
by: Gao, Yanting, et al.
Published: (2025)

MEAT: Median-Ensemble Adversarial Training for Improving Robustness and Generalization
by: Hu, Zhaozhe, et al.
Published: (2024)

Semi-Supervised Transfer Boosting (SS-TrBoosting)
by: Deng, Lingfei, et al.
Published: (2024)

Improving Transferability of Adversarial Examples via Bayesian Attacks
by: Li, Qizhang, et al.
Published: (2023)

Transferable Adversarial Attacks on Black-Box Vision-Language Models
by: Hu, Kai, et al.
Published: (2025)

Criticality Leveraged Adversarial Training (CLAT) for Boosted Performance via Parameter Efficiency
by: Gopal, Bhavna, et al.
Published: (2024)

Boosting the Local Invariance for Better Adversarial Transferability
by: Liu, Bohan, et al.
Published: (2025)

Adversarial-Robust Transfer Learning for Medical Imaging via Domain Assimilation
by: Chen, Xiaohui, et al.
Published: (2024)

Improving Adversarial Transferability via Model Alignment
by: Ma, Avery, et al.
Published: (2023)

Benchmarking Transferable Adversarial Attacks
by: Jin, Zhibo, et al.
Published: (2024)

Boosting the Transferability of Adversarial Attacks with Global Momentum Initialization
by: Wang, Jiafeng, et al.
Published: (2022)

Boosting Adversarial Training via Fisher-Rao Norm-based Regularization
by: Yin, Xiangyu, et al.
Published: (2024)

Rethinking Model Ensemble in Transfer-based Adversarial Attacks
by: Chen, Huanran, et al.
Published: (2023)

Transferable Adversarial Examples with Bayes Approach
by: Fan, Mingyuan, et al.
Published: (2022)

Enabling Heterogeneous Adversarial Transferability via Feature Permutation Attacks
by: Wu, Tao, et al.
Published: (2025)

Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
by: Yu, Yi, et al.
Published: (2025)

Mixture of Distributions Matters: Dynamic Sparse Attention for Efficient Video Diffusion Transformers
by: Liu, Yuxi, et al.
Published: (2026)

Boosting Model Resilience via Implicit Adversarial Data Augmentation
by: Zhou, Xiaoling, et al.
Published: (2024)

Boosting Text-to-Image Diffusion Models via Core Token Attention-Based Seed Selection
by: Zhang, Yunzhe, et al.
Published: (2026)

Boosting Transferability in Vision-Language Attacks via Diversification along the Intersection Region of Adversarial Trajectory
by: Gao, Sensen, et al.
Published: (2024)

Boosting the Robustness-Accuracy Trade-off of SNNs by Robust Temporal Self-Ensemble
by: Wang, Jihang, et al.
Published: (2025)

Boosting Adversarial Transferability via High-Frequency Augmentation and Hierarchical-Gradient Fusion
by: Zheng, Yayin, et al.
Published: (2025)

Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and Flatness
by: Fan, Mingyuan, et al.
Published: (2023)

Ensemble Adversarial Defense via Integration of Multiple Dispersed Low Curvature Models
by: Zhao, Kaikang, et al.
Published: (2024)

AIM: Additional Image Guided Generation of Transferable Adversarial Attacks
by: Li, Teng, et al.
Published: (2025)

Test-Time Defense Against Adversarial Attacks via Stochastic Resonance of Latent Ensembles
by: Lao, Dong, et al.
Published: (2025)

Boosting Adversarial Transferability for Skeleton-based Action Recognition via Exploring the Model Posterior Space
by: Diao, Yunfeng, et al.
Published: (2024)

Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability
by: Liu, Jiani, et al.
Published: (2025)

A Novel CNN Gradient Boosting Ensemble for Guava Disease Detection
by: Rijon, Tamim Ahasan, et al.
Published: (2025)

Boosting Adversarial Transferability with Low-Cost Optimization via Maximin Expected Flatness
by: Qiu, Chunlin, et al.
Published: (2024)