Cover Image

Enhancing Adversarial Transferability in Visual-Language Pre-training Models via Local Shuffle and Sample-based Attack

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Xin, Zhou, Aoyang
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Downstream Transfer Attack: Adversarial Attacks on Downstream Models with Pre-trained Vision Transformers
by: Zheng, Weijie, et al.
Published: (2024)

A Two-Stage Globally-Diverse Adversarial Attack for Vision-Language Pre-training Models
by: Chen, Wutao, et al.
Published: (2026)

HQA-VLAttack: Towards High Quality Adversarial Attack on Vision-Language Pre-Trained Models
by: Liu, Han, et al.
Published: (2026)

Patch is Enough: Naturalistic Adversarial Patch against Vision-Language Pre-training Models
by: Kong, Dehong, et al.
Published: (2024)

VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models
by: Yin, Ziyi, et al.
Published: (2024)

A Unified Understanding of Adversarial Vulnerability Regarding Unimodal Models and Vision-Language Pre-training Models
by: Zheng, Haonan, et al.
Published: (2024)

Feedback-based Modal Mutual Search for Attacking Vision-Language Pre-training Models
by: Ding, Renhua, et al.
Published: (2024)

PersGuard: Preventing Malicious Personalization via Backdoor Attacks on Pre-trained Text-to-Image Diffusion Models
by: Liu, Xinwei, et al.
Published: (2025)

Attribution for Enhanced Explanation with Transferable Adversarial eXploration
by: Zhu, Zhiyu, et al.
Published: (2024)

Comment-aided Video-Language Alignment via Contrastive Pre-training for Short-form Video Humor Detection
by: Liu, Yang, et al.
Published: (2024)

Adversarial Attack for RGB-Event based Visual Object Tracking
by: Chen, Qiang, et al.
Published: (2025)

Boosting the Transferability of Adversarial Examples via Local Mixup and Adaptive Step Size
by: Liu, Junlin, et al.
Published: (2024)

3D Modality-Aware Pre-training for Vision-Language Model in MRI Multi-organ Abnormality Detection
by: Zhu, Haowen, et al.
Published: (2026)

Longitudinal Mammogram Exam-based Breast Cancer Diagnosis Models: Vulnerability to Adversarial Attacks
by: Zhou, Zhengbo, et al.
Published: (2024)

Bayesian Exploration of Pre-trained Models for Low-shot Image Classification
by: Miao, Yibo, et al.
Published: (2024)

Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving
by: Wang, Lu, et al.
Published: (2025)

Transferable Adversarial Face Attack with Text Controlled Attribute
by: Li, Wenyun, et al.
Published: (2024)

Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition
by: Lu, Feng, et al.
Published: (2024)

Enhancing Adversarial Robustness of Vision-Language Models through Low-Rank Adaptation
by: Ji, Yuheng, et al.
Published: (2024)

Black-box Membership Inference Attacks on the Pre-training Data of Image-generation Models
by: Qi, Tao, et al.
Published: (2026)

Break the Visual Perception: Adversarial Attacks Targeting Encoded Visual Tokens of Large Vision-Language Models
by: Wang, Yubo, et al.
Published: (2024)

UniPre3D: Unified Pre-training of 3D Point Cloud Models with Cross-Modal Gaussian Splatting
by: Wang, Ziyi, et al.
Published: (2025)

Towards a 3D Transfer-based Black-box Attack via Critical Feature Guidance
by: Pang, Shuchao, et al.
Published: (2025)

Enhancing Adversarial Transferability by Balancing Exploration and Exploitation with Gradient-Guided Sampling
by: Niu, Zenghao, et al.
Published: (2025)

Adversarial Prompt Injection Attack on Multimodal Large Language Models
by: Ding, Meiwen, et al.
Published: (2026)

Emotion Loss Attacking: Adversarial Attack Perception for Skeleton based on Multi-dimensional Features
by: Liu, Feng, et al.
Published: (2024)

One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models
by: Li, Lin, et al.
Published: (2024)

On Pre-training of Multimodal Language Models Customized for Chart Understanding
by: Fan, Wan-Cyuan, et al.
Published: (2024)

Grounded Knowledge-Enhanced Medical Vision-Language Pre-training for Chest X-Ray
by: Deng, Qiao, et al.
Published: (2024)

Robustness Evaluation of OCR-based Visual Document Understanding under Multi-Modal Adversarial Attacks
by: Tien, Dong Nguyen, et al.
Published: (2025)

Do Pre-trained Vision-Language Models Encode Object States?
by: Newman, Kaleb, et al.
Published: (2024)

Transferable Adversarial Facial Images for Privacy Protection
by: Li, Minghui, et al.
Published: (2024)

Adversarial Attack Against Images Classification based on Generative Adversarial Networks
by: Yang, Yahe
Published: (2024)

Beyond Attack Success Rate: A Multi-Metric Evaluation of Adversarial Transferability in Medical Imaging Models
by: Curl, Emily, et al.
Published: (2026)

Pre-trained Vision-Language Models Learn Discoverable Visual Concepts
by: Zang, Yuan, et al.
Published: (2024)

A Knowledge-guided Adversarial Defense for Resisting Malicious Visual Manipulation
by: Zhou, Dawei, et al.
Published: (2025)

RadCLIP: Enhancing Radiologic Image Analysis through Contrastive Language-Image Pre-training
by: Lu, Zhixiu, et al.
Published: (2024)

Devling into Adversarial Transferability on Image Classification: Review, Benchmark, and Evaluation
by: Wang, Xiaosen, et al.
Published: (2026)

Instance-Level Trojan Attacks on Visual Question Answering via Adversarial Learning in Neuron Activation Space
by: Sun, Yuwei, et al.
Published: (2023)

When Alignment Fails: Multimodal Adversarial Attacks on Vision-Language-Action Models
by: Yan, Yuping, et al.
Published: (2025)