Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning

Ähnliche Einträge

• Align is not Enough: Multimodal Universal Jailbreak Attack against Multimodal Large Language Models
  von: Wang, Youze, et al.
  Veröffentlicht: (2025)
• Improving Adversarial Transferability of Vision-Language Pre-training Models through Collaborative Multimodal Interaction
  von: Fu, Jiyuan, et al.
  Veröffentlicht: (2024)
• Multimodal Pre-training Framework for Sequential Recommendation via Contrastive Learning
  von: Zhang, Lingzi, et al.
  Veröffentlicht: (2023)
• Listening to the Unspoken: Exploring "365" Aspects of Multimodal Interview Performance Assessment
  von: Li, Jia, et al.
  Veröffentlicht: (2025)
• Universal Adversarial Perturbations for Vision-Language Pre-trained Models
  von: Zhang, Peng-Fei, et al.
  Veröffentlicht: (2024)