Saved in:
| Main Authors: | Zhang, Zhifang, Zhang, Jiahan, Zhou, Shengjie, Wei, Qi, He, Shuo, Liu, Feng, Feng, Lei |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.19994 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning
by: Zhang, Zhifang, et al.
Published: (2024)
by: Zhang, Zhifang, et al.
Published: (2024)
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data
by: Zhang, Jiahan, et al.
Published: (2024)
by: Zhang, Jiahan, et al.
Published: (2024)
Unleashing the Power of Pre-trained Encoders for Universal Adversarial Attack Detection
by: Zhang, Yinghe, et al.
Published: (2025)
by: Zhang, Yinghe, et al.
Published: (2025)
VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models
by: Yin, Ziyi, et al.
Published: (2023)
by: Yin, Ziyi, et al.
Published: (2023)
Enhancing Adversarial Attacks: The Similar Target Method
by: Zhang, Shuo, et al.
Published: (2023)
by: Zhang, Shuo, et al.
Published: (2023)
TokenSwap: Backdoor Attack on the Compositional Understanding of Large Vision-Language Models
by: Zhang, Zhifang, et al.
Published: (2025)
by: Zhang, Zhifang, et al.
Published: (2025)
MAA: Meticulous Adversarial Attack against Vision-Language Pre-trained Models
by: Zhang, Peng-Fei, et al.
Published: (2025)
by: Zhang, Peng-Fei, et al.
Published: (2025)
Test-Time Multimodal Backdoor Detection by Contrastive Prompting
by: Niu, Yuwei, et al.
Published: (2024)
by: Niu, Yuwei, et al.
Published: (2024)
VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models
by: Yin, Ziyi, et al.
Published: (2024)
by: Yin, Ziyi, et al.
Published: (2024)
Learning on Less: Constraining Pre-trained Model Learning for Generalizable Diffusion-Generated Image Detection
by: Chen, Yingjian, et al.
Published: (2024)
by: Chen, Yingjian, et al.
Published: (2024)
SRAW-Attack: Space-Reweighted Adversarial Warping Attack for SAR Target Recognition
by: Zhang, Yiming, et al.
Published: (2026)
by: Zhang, Yiming, et al.
Published: (2026)
Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples
by: Zhou, Ziqi, et al.
Published: (2024)
by: Zhou, Ziqi, et al.
Published: (2024)
Improving Adversarial Transferability of Vision-Language Pre-training Models through Collaborative Multimodal Interaction
by: Fu, Jiyuan, et al.
Published: (2024)
by: Fu, Jiyuan, et al.
Published: (2024)
Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks
by: Zhang, Lei, et al.
Published: (2024)
by: Zhang, Lei, et al.
Published: (2024)
Test-Time Attention Purification for Backdoored Large Vision Language Models
by: Zhang, Zhifang, et al.
Published: (2026)
by: Zhang, Zhifang, et al.
Published: (2026)
Enhancing Adversarial Transferability in Visual-Language Pre-training Models via Local Shuffle and Sample-based Attack
by: Liu, Xin, et al.
Published: (2025)
by: Liu, Xin, et al.
Published: (2025)
Model Inversion Attacks Through Target-Specific Conditional Diffusion Models
by: Li, Ouxiang, et al.
Published: (2024)
by: Li, Ouxiang, et al.
Published: (2024)
Efficient and Effective Universal Adversarial Attack against Vision-Language Pre-training Models
by: Yang, Fan, et al.
Published: (2024)
by: Yang, Fan, et al.
Published: (2024)
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification
by: Miao, Yibo, et al.
Published: (2024)
by: Miao, Yibo, et al.
Published: (2024)
A Generative Adversarial Approach to Adversarial Attacks Guided by Contrastive Language-Image Pre-trained Model
by: Soor, Sampriti, et al.
Published: (2025)
by: Soor, Sampriti, et al.
Published: (2025)
Downstream Transfer Attack: Adversarial Attacks on Downstream Models with Pre-trained Vision Transformers
by: Zheng, Weijie, et al.
Published: (2024)
by: Zheng, Weijie, et al.
Published: (2024)
Towards Physically Realizable Adversarial Attacks in Embodied Vision Navigation
by: Chen, Meng, et al.
Published: (2024)
by: Chen, Meng, et al.
Published: (2024)
Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations
by: Kulkarni, Pranav, et al.
Published: (2024)
by: Kulkarni, Pranav, et al.
Published: (2024)
Pre-trained Multiple Latent Variable Generative Models are good defenders against Adversarial Attacks
by: Serez, Dario, et al.
Published: (2024)
by: Serez, Dario, et al.
Published: (2024)
Exploring Generalizable Pre-training for Real-world Change Detection via Geometric Estimation
by: Zhao, Yitao, et al.
Published: (2025)
by: Zhao, Yitao, et al.
Published: (2025)
Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model
by: Shi, Jiang-Xin, et al.
Published: (2024)
by: Shi, Jiang-Xin, et al.
Published: (2024)
Pre-training Everywhere: Parameter-Efficient Fine-Tuning for Medical Image Analysis via Target Parameter Pre-training
by: Lei, Xingliang, et al.
Published: (2024)
by: Lei, Xingliang, et al.
Published: (2024)
Scalable and Generalizable Correspondence Pruning via Geometry-Consistent Pre-training
by: Liao, Tangfei, et al.
Published: (2024)
by: Liao, Tangfei, et al.
Published: (2024)
MetaDAT: Generalizable Trajectory Prediction via Meta Pre-training and Data-Adaptive Test-Time Updating
by: Wang, Yuning, et al.
Published: (2026)
by: Wang, Yuning, et al.
Published: (2026)
Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial Robustness
by: Wang, Sibo, et al.
Published: (2024)
by: Wang, Sibo, et al.
Published: (2024)
Decoupling Forgery Semantics for Generalizable Deepfake Detection
by: Ye, Wei, et al.
Published: (2024)
by: Ye, Wei, et al.
Published: (2024)
BiTAA: A Bi-Task Adversarial Attack for Object Detection and Depth Estimation via 3D Gaussian Splatting
by: Zhang, Yixun, et al.
Published: (2025)
by: Zhang, Yixun, et al.
Published: (2025)
DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training
by: Wang, Zihao, et al.
Published: (2024)
by: Wang, Zihao, et al.
Published: (2024)
Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
by: Zhang, Jiacheng, et al.
Published: (2024)
by: Zhang, Jiacheng, et al.
Published: (2024)
A Two-Stage Globally-Diverse Adversarial Attack for Vision-Language Pre-training Models
by: Chen, Wutao, et al.
Published: (2026)
by: Chen, Wutao, et al.
Published: (2026)
AttentionDrag: Exploiting Latent Correlation Knowledge in Pre-trained Diffusion Models for Image Editing
by: Yang, Biao, et al.
Published: (2025)
by: Yang, Biao, et al.
Published: (2025)
V-Attack: Targeting Disentangled Value Features for Controllable Adversarial Attacks on LVLMs
by: Nie, Sen, et al.
Published: (2025)
by: Nie, Sen, et al.
Published: (2025)
Black-box Targeted Adversarial Attack on Segment Anything (SAM)
by: Zheng, Sheng, et al.
Published: (2023)
by: Zheng, Sheng, et al.
Published: (2023)
Double Visual Defense: Adversarial Pre-training and Instruction Tuning for Improving Vision-Language Model Robustness
by: Wang, Zeyu, et al.
Published: (2025)
by: Wang, Zeyu, et al.
Published: (2025)
PLIP: Language-Image Pre-training for Person Representation Learning
by: Zuo, Jialong, et al.
Published: (2023)
by: Zuo, Jialong, et al.
Published: (2023)
Similar Items
-
Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning
by: Zhang, Zhifang, et al.
Published: (2024) -
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data
by: Zhang, Jiahan, et al.
Published: (2024) -
Unleashing the Power of Pre-trained Encoders for Universal Adversarial Attack Detection
by: Zhang, Yinghe, et al.
Published: (2025) -
VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models
by: Yin, Ziyi, et al.
Published: (2023) -
Enhancing Adversarial Attacks: The Similar Target Method
by: Zhang, Shuo, et al.
Published: (2023)