Copertina

Revisiting CroPA: A Reproducibility Study and Enhancements for Cross-Prompt Adversarial Transferability in Vision-Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Mittal, Atharv, Pandey, Agam, Tiwari, Amritanshu, Jindal, Sukrit, Swain, Swadesh
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

OmniPatch: A Universal Adversarial Patch for ViT-CNN Cross-Architecture Transfer in Semantic Segmentation
di: Aggarwal, Aarush, et al.
Pubblicazione: (2026)

Jailbreaking Vision-Language Models Through the Visual Modality
di: Azulay, Aharon, et al.
Pubblicazione: (2026)

Closed-Loop Bidirectional Prompting for Adversarial Robustness of Vision Language Models
di: Liu, Xiao, et al.
Pubblicazione: (2026)

Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models
di: Jia, Xiaojun, et al.
Pubblicazione: (2025)

An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
di: Luo, Haochen, et al.
Pubblicazione: (2024)

Revisiting Prompt Pretraining of Vision-Language Models
di: Chen, Zhenyuan, et al.
Pubblicazione: (2024)

IMAGE-ALCHEMY: Advancing subject fidelity in personalised text-to-image generation
di: Tiwari, Amritanshu, et al.
Pubblicazione: (2025)

CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning
di: Mushtaq, Erum, et al.
Pubblicazione: (2024)

Adversarial Prompt Tuning for Vision-Language Models
di: Zhang, Jiaming, et al.
Pubblicazione: (2023)

Adversarial Prompt Distillation for Vision-Language Models
di: Luo, Lin, et al.
Pubblicazione: (2024)

Revisiting the Adversarial Robustness of Vision Language Models: a Multimodal Perspective
di: Zhou, Wanqi, et al.
Pubblicazione: (2024)

SimCroP: Radiograph Representation Learning with Similarity-driven Cross-granularity Pre-training
di: Wang, Rongsheng, et al.
Pubblicazione: (2025)

Revisiting the Robust Generalization of Adversarial Prompt Tuning
di: Yang, Fan, et al.
Pubblicazione: (2024)

MoAPT: Mixture of Adversarial Prompt Tuning for Vision-Language Models
di: Zhao, Shiji, et al.
Pubblicazione: (2025)

FedAPT: Federated Adversarial Prompt Tuning for Vision-Language Models
di: Zhai, Kun, et al.
Pubblicazione: (2025)

Self-Calibrated Consistency can Fight Back for Adversarial Robustness in Vision-Language Models
di: Liu, Jiaxiang, et al.
Pubblicazione: (2025)

Constrained Prompt Enhancement for Improving Zero-Shot Generalization of Vision-Language Models
di: Yin, Xiaojie, et al.
Pubblicazione: (2025)

Self-Prompt SAM: Medical Image Segmentation via Automatic Prompt SAM Adaptation
di: Xie, Bin, et al.
Pubblicazione: (2025)

Reproducibility Study on Adversarial Attacks Against Robust Transformer Trackers
di: Nokabadi, Fatemeh Nourilenjan, et al.
Pubblicazione: (2024)

Hierarchical Cross-modal Prompt Learning for Vision-Language Models
di: Zheng, Hao, et al.
Pubblicazione: (2025)

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

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

TAPT: Test-Time Adversarial Prompt Tuning for Robust Inference in Vision-Language Models
di: Wang, Xin, et al.
Pubblicazione: (2024)

Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt
di: Ying, Zonghao, et al.
Pubblicazione: (2024)

RFMedSAM 2: Automatic Prompt Refinement for Enhanced Volumetric Medical Image Segmentation with SAM 2
di: Xie, Bin, et al.
Pubblicazione: (2025)

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

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models
di: Wang, Xin, et al.
Pubblicazione: (2026)

Prompt-and-Transfer: Dynamic Class-aware Enhancement for Few-shot Segmentation
di: Bi, Hanbo, et al.
Pubblicazione: (2024)

Efficient Generation of Targeted and Transferable Adversarial Examples for Vision-Language Models Via Diffusion Models
di: Guo, Qi, et al.
Pubblicazione: (2024)

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

Impact of Language Guidance: A Reproducibility Study
di: Puniani, Cherish, et al.
Pubblicazione: (2025)

CroMe: Multimodal Fake News Detection using Cross-Modal Tri-Transformer and Metric Learning
di: Choi, Eunjee, et al.
Pubblicazione: (2025)

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

NAP-Tuning: Neural Augmented Prompt Tuning for Adversarially Robust Vision-Language Models
di: Zhang, Jiaming, et al.
Pubblicazione: (2025)

Cross-modal Associations in Vision and Language Models: Revisiting the Bouba-Kiki Effect
di: Kouwenhoven, Tom, et al.
Pubblicazione: (2025)

Few-Shot Adversarial Prompt Learning on Vision-Language Models
di: Zhou, Yiwei, et al.
Pubblicazione: (2024)

MaskMed: Decoupled Mask and Class Prediction for Medical Image Segmentation
di: Xie, Bin, et al.
Pubblicazione: (2025)

Motion-Aware Transformer for Multi-Object Tracking
di: Yang, Xu, et al.
Pubblicazione: (2025)

A Unified Framework for Stealthy Adversarial Generation via Latent Optimization and Transferability Enhancement
di: Pei, Gaozheng, et al.
Pubblicazione: (2025)

Just Add Geometry: Gradient-Free Open-Vocabulary 3D Detection Without Human-in-the-Loop
di: Goel, Atharv, et al.
Pubblicazione: (2025)