Do vision transformers see like convolutional neural networks?

The article poses a research question comparing the visual processing of Vision Transformers (ViTs) and Convolutional Neural Networks (CNNs). The core inquiry is whether these two architectures, which approach image analysis differently, perceive and interpret visual information in similar ways. This is a fundamental question in understanding the inner workings and potential biases of these AI models.

• •The article explores a fundamental question about the similarity of visual processing between ViTs and CNNs.
• •Understanding how these architectures 'see' is crucial for improving AI model performance and mitigating biases.
• •The research likely involves analyzing the internal representations and attention mechanisms of both model types.