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Yuanbo Li

2 accepted papers

2026

Multi-Paradigm Collaborative Adversarial Attack Against Multi-Modal Large Language Models

CVPR 2026

The rapid progress of Multi-Modal Large Language Models (MLLMs) has significantly advanced downstream applications. However, this progress also exposes serious transferable adversarial vulnerabilities. In general, existing adversarial attacks against MLLMs typically rely on surrogate models trained

Cited by 0SourcecodeScholar
2026

Towards Highly Transferable Vision-Language Attack via Semantic-Augmented Dynamic Contrastive Interaction

CVPR 2026

With the rapid advancement and widespread application of vision-language pre-training (VLP) models, their vulnerability to adversarial attacks has become a critical concern. In general, the adversarial examples can typically be designed to exhibit transferable power, attacking not only different mod

Cited by 0SourcecodeScholar