Partially Recentralization Softmax Loss for Vision-Language Models Robustness

As Large Language Models make a breakthrough in natural language processing tasks (NLP), multimodal technique becomes extremely popular. However, it has been shown that multimodal NLP are vulnerable to adversarial attacks, where the outputs of a model can be dramatically changed by a perturbation to the input. While several defense techniques have been proposed both in computer vision and NLP models, the multimodal robustness of models have not been fully explored. In this paper, we study the adversarial robustness provided …

adversarial adversarial attacks attacks cs.ai cs.cl defense language language models language processing large language large language models loss multimodal natural natural language natural language processing nlp popular processing robustness softmax tasks vision vision-language models vulnerable