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This paper proposes a novel deep learning architecture called ViT-BERT, which combines the strengths of Vision Transformer (ViT) and BERT for multimodal understanding. The authors demonstrate the effectiveness of their approach on several vision-language tasks, achieving state-of-the-art performance.