Improving Adversarial Transferability in MLLMs via Dynamic Vision-Language Alignment Attack
Fuente:
arXiv
Guardado en:
| Autores principales: | Gu, Chenhe, Gu, Jindong, Hua, Andong, Qin, Yao |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Improving Adversarial Transferability via Model Alignment
por: Ma, Avery, et al.
Publicado: (2023)
por: Ma, Avery, et al.
Publicado: (2023)
Initialization Matters for Adversarial Transfer Learning
por: Hua, Andong, et al.
Publicado: (2023)
por: Hua, Andong, et al.
Publicado: (2023)
Transferable Adversarial Attacks on Black-Box Vision-Language Models
por: Hu, Kai, et al.
Publicado: (2025)
por: Hu, Kai, et al.
Publicado: (2025)
Improving Transferability of Adversarial Examples via Bayesian Attacks
por: Li, Qizhang, et al.
Publicado: (2023)
por: Li, Qizhang, et al.
Publicado: (2023)
An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
por: Luo, Haochen, et al.
Publicado: (2024)
por: Luo, Haochen, et al.
Publicado: (2024)
$Δ\mathrm{Energy}$: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization
por: Zhu, Lin, et al.
Publicado: (2025)
por: Zhu, Lin, et al.
Publicado: (2025)
Benchmarking Transferable Adversarial Attacks
por: Jin, Zhibo, et al.
Publicado: (2024)
por: Jin, Zhibo, et al.
Publicado: (2024)
Transferability of Adversarial Attacks in Video-based MLLMs: A Cross-modal Image-to-Video Approach
por: Huang, Linhao, et al.
Publicado: (2025)
por: Huang, Linhao, et al.
Publicado: (2025)
Flaw or Artifact? Rethinking Prompt Sensitivity in Evaluating LLMs
por: Hua, Andong, et al.
Publicado: (2025)
por: Hua, Andong, et al.
Publicado: (2025)
Model-agnostic Adversarial Attack and Defense for Vision-Language-Action Models
por: Xu, Haochuan, et al.
Publicado: (2025)
por: Xu, Haochuan, et al.
Publicado: (2025)
Improved Alignment of Modalities in Large Vision Language Models
por: Jangra, Kartik, et al.
Publicado: (2025)
por: Jangra, Kartik, et al.
Publicado: (2025)
Strong Transferable Adversarial Attacks via Ensembled Asymptotically Normal Distribution Learning
por: Fang, Zhengwei, et al.
Publicado: (2022)
por: Fang, Zhengwei, et al.
Publicado: (2022)
MMRL: Multi-Modal Representation Learning for Vision-Language Models
por: Guo, Yuncheng, et al.
Publicado: (2025)
por: Guo, Yuncheng, et al.
Publicado: (2025)
Similarity of Neural Architectures using Adversarial Attack Transferability
por: Hwang, Jaehui, et al.
Publicado: (2022)
por: Hwang, Jaehui, et al.
Publicado: (2022)
Boosting Adversarial Transferability via Ensemble Non-Attention
por: Zou, Yipeng, et al.
Publicado: (2025)
por: Zou, Yipeng, et al.
Publicado: (2025)
Boosting Adversarial Transferability via Residual Perturbation Attack
por: Peng, Jinjia, et al.
Publicado: (2025)
por: Peng, Jinjia, et al.
Publicado: (2025)
Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment
por: Jia, Xiaojun, et al.
Publicado: (2025)
por: Jia, Xiaojun, et al.
Publicado: (2025)
Improving the Transferability of Adversarial Attacks by an Input Transpose
por: Wan, Qing, et al.
Publicado: (2025)
por: Wan, Qing, et al.
Publicado: (2025)
AIM: Additional Image Guided Generation of Transferable Adversarial Attacks
por: Li, Teng, et al.
Publicado: (2025)
por: Li, Teng, et al.
Publicado: (2025)
Banana100: Breaking NR-IQA Metrics by 100 Iterative Image Replications with Nano Banana Pro
por: Tang, Kenan, et al.
Publicado: (2026)
por: Tang, Kenan, et al.
Publicado: (2026)
Ultrasound Vision-Language Alignment via Contrastive Learning
por: Lyu, Zhuoyang, et al.
Publicado: (2026)
por: Lyu, Zhuoyang, et al.
Publicado: (2026)
Bag of Tricks to Boost Adversarial Transferability
por: Zhang, Zeliang, et al.
Publicado: (2024)
por: Zhang, Zeliang, et al.
Publicado: (2024)
Enabling Heterogeneous Adversarial Transferability via Feature Permutation Attacks
por: Wu, Tao, et al.
Publicado: (2025)
por: Wu, Tao, et al.
Publicado: (2025)
RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment
por: Gu, Difei, et al.
Publicado: (2025)
por: Gu, Difei, et al.
Publicado: (2025)
Dynamic Label Adversarial Training for Deep Learning Robustness Against Adversarial Attacks
por: Liu, Zhenyu, et al.
Publicado: (2024)
por: Liu, Zhenyu, et al.
Publicado: (2024)
Improving Generalization of Universal Adversarial Perturbation via Dynamic Maximin Optimization
por: Zhang, Yechao, et al.
Publicado: (2025)
por: Zhang, Yechao, et al.
Publicado: (2025)
Can Multimodal Large Language Models Truly Perform Multimodal In-Context Learning?
por: Chen, Shuo, et al.
Publicado: (2023)
por: Chen, Shuo, et al.
Publicado: (2023)
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
por: Huang, Hanxun, et al.
Publicado: (2025)
por: Huang, Hanxun, et al.
Publicado: (2025)
Toward Universal and Transferable Jailbreak Attacks on Vision-Language Models
por: Cui, Kaiyuan, et al.
Publicado: (2026)
por: Cui, Kaiyuan, et al.
Publicado: (2026)
FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks
por: Yang, Hunmin, et al.
Publicado: (2024)
por: Yang, Hunmin, et al.
Publicado: (2024)
Fairness-Aware Fine-Tuning of Vision-Language Models for Medical Glaucoma Diagnosis
por: Gu, Zijian, et al.
Publicado: (2025)
por: Gu, Zijian, et al.
Publicado: (2025)
Not Blind but Silenced: Rebalancing Vision and Language via Adversarial Counter-Commonsense Equilibrium
por: Xiao, Qingxin, et al.
Publicado: (2026)
por: Xiao, Qingxin, et al.
Publicado: (2026)
Transfer Attack for Bad and Good: Explain and Boost Adversarial Transferability across Multimodal Large Language Models
por: Cheng, Hao, et al.
Publicado: (2024)
por: Cheng, Hao, et al.
Publicado: (2024)
Dynamic Adversarial Attacks on Autonomous Driving Systems
por: Chahe, Amirhosein, et al.
Publicado: (2023)
por: Chahe, Amirhosein, et al.
Publicado: (2023)
Personalized Vision via Visual In-Context Learning
por: Jiang, Yuxin, et al.
Publicado: (2025)
por: Jiang, Yuxin, et al.
Publicado: (2025)
Transferable Adversarial Attacks on SAM and Its Downstream Models
por: Xia, Song, et al.
Publicado: (2024)
por: Xia, Song, et al.
Publicado: (2024)
Constructive Distortion: Improving MLLMs with Attention-Guided Image Warping
por: Dalal, Dwip, et al.
Publicado: (2025)
por: Dalal, Dwip, et al.
Publicado: (2025)
Distribution Alignment for Fully Test-Time Adaptation with Dynamic Online Data Streams
por: Wang, Ziqiang, et al.
Publicado: (2024)
por: Wang, Ziqiang, et al.
Publicado: (2024)
Dynamic Parameter Optimization for Highly Transferable Transformation-Based Attacks
por: Liang, Jiaming, et al.
Publicado: (2025)
por: Liang, Jiaming, et al.
Publicado: (2025)
Transform-Dependent Adversarial Attacks
por: Tan, Yaoteng, et al.
Publicado: (2024)
por: Tan, Yaoteng, et al.
Publicado: (2024)
Ejemplares similares
-
Improving Adversarial Transferability via Model Alignment
por: Ma, Avery, et al.
Publicado: (2023) -
Initialization Matters for Adversarial Transfer Learning
por: Hua, Andong, et al.
Publicado: (2023) -
Transferable Adversarial Attacks on Black-Box Vision-Language Models
por: Hu, Kai, et al.
Publicado: (2025) -
Improving Transferability of Adversarial Examples via Bayesian Attacks
por: Li, Qizhang, et al.
Publicado: (2023) -
An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
por: Luo, Haochen, et al.
Publicado: (2024)