DarkLLM trains an LLM to generate language-driven adversarial perturbations that unify targeted, untargeted, segmentation, and multi-model attacks on foundation models.
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2026 2verdicts
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PRAF-Attack improves targeted attack transferability on black-box MLLMs by using multi-scale progressive resolution and adaptive intermediate feature alignment instead of final-layer global features.
citing papers explorer
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DarkLLM: Learning Language-Driven Adversarial Attacks with Large Language Models
DarkLLM trains an LLM to generate language-driven adversarial perturbations that unify targeted, untargeted, segmentation, and multi-model attacks on foundation models.
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Adversarial Attacks Against MLLMs via Progressive Resolution Processing and Adaptive Feature Alignment
PRAF-Attack improves targeted attack transferability on black-box MLLMs by using multi-scale progressive resolution and adaptive intermediate feature alignment instead of final-layer global features.