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You are building a multimodal application that takes an image and a short text description as input and generates a more detailed text description of the image. Which of the following model architectures is BEST suited for this task?
Correct Answer: B
A Vision Transformer (ViT) excels at encoding image information, and a Transformer architecture is highly effective for text generation. The combination allows for effective processing of both modalities and generation of coherent, detailed text descriptions based on the image content and initial text prompt. CNN+LSTM could work, but is generally less performant. RNNs struggle with long-range dependencies. GANs are not ideal for this specific text generation task. MLPs don't capture the sequential dependencies well.