CFGPatch combines curved fractal geometry with modality-specific spiral textures to create adversarial patches that fool VIS-IR VLMs and transfer across classification, captioning, and VQA tasks.
Infrared-LLaV A: Enhanc- ing understanding of infrared images in multi-modal large language models
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UCGP is a universal physical adversarial patch that compromises cross-modal semantic alignment in IR-VLMs through curved-grid parameterization and representation-space disruption.
citing papers explorer
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Exposing Vulnerabilities in Visible-Infrared VLMs: A Unified Geometric Adversarial Framework with Cross-Task Transferability
CFGPatch combines curved fractal geometry with modality-specific spiral textures to create adversarial patches that fool VIS-IR VLMs and transfer across classification, captioning, and VQA tasks.
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Revealing Physical-World Semantic Vulnerabilities: Universal Adversarial Patches for Infrared Vision-Language Models
UCGP is a universal physical adversarial patch that compromises cross-modal semantic alignment in IR-VLMs through curved-grid parameterization and representation-space disruption.