NCA-GENM Exam Dumps | You're working with a multimodal model that fuses text and image features. You've noticed that the model

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Question 20/192

You're working with a multimodal model that fuses text and image features. You've noticed that the model performs poorly when the text and image are semantically misaligned (e.g., an image of a dog and the caption 'a cat on a mat'). Which of the following techniques can help improve the model's robustness to such misalignment?

A. Increasing the learning rate during training.

B. Adding a contrastive loss that penalizes embeddings of misaligned text-image pairs.

C. Decreasing the batch size.

D. Using only positive text-image pairs for training.

E. Removing dropout layers from the model architecture.

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