Cover Image

When Background Matters: Breaking Medical Vision Language Models by Transferable Attack

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ghosh, Akash, Baidya, Subhadip, Saha, Sriparna, Chen, Xiuying
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Exploring the Frontier of Vision-Language Models: A Survey of Current Methodologies and Future Directions
by: Ghosh, Akash, et al.
Published: (2024)

CarePilot: A Multi-Agent Framework for Long-Horizon Computer Task Automation in Healthcare
by: Ghosh, Akash, et al.
Published: (2026)

CURE-Med: Curriculum-Informed Reinforcement Learning for Multilingual Medical Reasoning
by: Onyame, Eric, et al.
Published: (2026)

Ask Me Again Differently: GRAS for Measuring Bias in Vision Language Models on Gender, Race, Age, and Skin Tone
by: Malik, Shaivi, et al.
Published: (2025)

Chain of Attack: On the Robustness of Vision-Language Models Against Transfer-Based Adversarial Attacks
by: Xie, Peng, et al.
Published: (2024)

A Comprehensive Survey of Hallucination in Large Language, Image, Video and Audio Foundation Models
by: Sahoo, Pranab, et al.
Published: (2024)

When Robots Obey the Patch: Universal Transferable Patch Attacks on Vision-Language-Action Models
by: Lu, Hui, et al.
Published: (2025)

When and Where to Attack? Stage-wise Attention-Guided Adversarial Attack on Large Vision Language Models
by: Kwak, Jaehyun, et al.
Published: (2026)

When Minor Edits Matter: LLM-Driven Prompt Attack for Medical VLM Robustness in Ultrasound
by: Medghalchi, Yasamin, et al.
Published: (2026)

SGHA-Attack: Semantic-Guided Hierarchical Alignment for Transferable Targeted Attacks on Vision-Language Models
by: Wang, Haobo, et al.
Published: (2026)

When Surfaces Lie: Exploiting Wrinkle-Induced Attention Shift to Attack Vision-Language Models
by: Hu, Chengyin, et al.
Published: (2026)

When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise
by: Shin, Philip Wootaek, et al.
Published: (2026)

Simulated Ensemble Attack: Transferring Jailbreaks Across Fine-tuned Vision-Language Models
by: Wang, Ruofan, et al.
Published: (2025)

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

Temporal Consistency Constrained Transferable Adversarial Attacks with Background Mixup for Action Recognition
by: Li, Ping, et al.
Published: (2025)

When Lighting Deceives: Exposing Vision-Language Models' Illumination Vulnerability Through Illumination Transformation Attack
by: Liu, Hanqing, et al.
Published: (2025)

Background Matters: A Cross-view Bidirectional Modeling Framework for Semi-supervised Medical Image Segmentation
by: Cao, Luyang, et al.
Published: (2025)

Focus on What Matters: Enhancing Medical Vision-Language Models with Automatic Attention Alignment Tuning
by: Chang, Aofei, et al.
Published: (2025)

VLA-Hijack: A Transferable Patch Attack against Vision-Language-Action Models via Visual Proprioception Hijacking
by: Fu, Jiyuan, et al.
Published: (2026)

HEART-VIT: Hessian-Guided Efficient Dynamic Attention and Token Pruning in Vision Transformer
by: Uddin, Mohammad Helal, et al.
Published: (2025)

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

Semantic-Aligned Adversarial Evolution Triangle for High-Transferability Vision-Language Attack
by: Jia, Xiaojun, et al.
Published: (2024)

TrojVLM: Backdoor Attack Against Vision Language Models
by: Lyu, Weimin, et al.
Published: (2024)

Assimilation Matters: Model-level Backdoor Detection in Vision-Language Pretrained Models
by: Wang, Zhongqi, et al.
Published: (2025)

FedMRL: Data Heterogeneity Aware Federated Multi-agent Deep Reinforcement Learning for Medical Imaging
by: Sahoo, Pranab, et al.
Published: (2024)

Web Artifact Attacks Disrupt Vision Language Models
by: Qraitem, Maan, et al.
Published: (2025)

Towards Highly Transferable Vision-Language Attack via Semantic-Augmented Dynamic Contrastive Interaction
by: Li, Yuanbo, et al.
Published: (2026)

Poetry in Pixels: Prompt Tuning for Poem Image Generation via Diffusion Models
by: Jamil, Sofia, et al.
Published: (2025)

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

Toward Universal and Transferable Jailbreak Attacks on Vision-Language Models
by: Cui, Kaiyuan, et al.
Published: (2026)

Container damage detection using advanced computer vision model Yolov12 vs Yolov11 vs RF-DETR A comparative analysis
by: Kumar, Subhadip
Published: (2025)

Detecting and Evaluating Medical Hallucinations in Large Vision Language Models
by: Chen, Jiawei, et al.
Published: (2024)

BackdoorVLM: A Benchmark for Backdoor Attacks on Vision-Language Models
by: Li, Juncheng, et al.
Published: (2025)

When Negation Is a Geometry Problem in Vision-Language Models
by: Sammani, Fawaz, et al.
Published: (2026)

When Words Can't Capture It All: Towards Video-Based User Complaint Text Generation with Multimodal Video Complaint Dataset
by: Das, Sarmistha, et al.
Published: (2025)

Few-shot Adaptation of Medical Vision-Language Models
by: Shakeri, Fereshteh, et al.
Published: (2024)

Full Conformal Adaptation of Medical Vision-Language Models
by: Silva-Rodríguez, Julio, et al.
Published: (2025)

On the Robustness of Medical Vision-Language Models: Are they Truly Generalizable?
by: Imam, Raza, et al.
Published: (2025)

ToxVidLM: A Multimodal Framework for Toxicity Detection in Code-Mixed Videos
by: Maity, Krishanu, et al.
Published: (2024)

Proxy Robustness in Vision Language Models is Effortlessly Transferable
by: Fu, Xiaowei, et al.
Published: (2026)