29 citations · 116 across the 20 of their papers we have counts for
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cs.CV2024
Parameter-Efficient and Memory-Efficient Tuning for Vision Transformer: A Disentangled Approach
Taolin Zhang, Jiawang Bai, Zhihe Lu +4
Recent works on parameter-efficient transfer learning (PETL) show the potential to adapt a pre-trained Vision Transformer to downstream recognition tasks with only a few learnable…
cs.CV2024
Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained Vision Transformers
Sheng Yang, Jiawang Bai, Kuofeng Gao +3
Given the power of vision transformers, a new learning paradigm, pre-training and then prompting, makes it more efficient and effective to address downstream visual recognition tas…
cs.CV2024★ 2 cited
Adversarial Robustness for Visual Grounding of Multimodal Large Language Models
Kuofeng Gao, Yang Bai, Jiawang Bai +2
Multi-modal Large Language Models (MLLMs) have recently achieved enhanced performance across various vision-language tasks including visual grounding capabilities. However, the adv…