Exam NCA-GENM Topic 1 Question 53 Discussion

Actual exam question for NVIDIA's NCA-GENM exam
Question #: 53
Topic #: 1
You are tasked with building a multimodal generative AI model to create marketing content from product images and descriptions. The image encoder uses a pre-trained ResNet50 model, and the text encoder uses a pre-trained BERT model. After initial training, the generated content frequently misinterprets the image. Which of the following strategies is MOST effective in improving the model's ability to correctly interpret the image within the multimodal context?

Suggested Answer: B Vote an answer

Fine-tuning ResNet50 with a relevant image dataset and a contrastive loss function directly addresses the issue of misinterpreting the image. Freezing weights prevents learning, increasing BERT's learning rate imbalances the model, and a simpler image encoder might lose crucial image details. Decreasing batch size can improve generalization but isn't the primary solution for image misinterpretation.

by Poppy at Aug 22, 2026, 04:34 PM

Limited Time Offer

15%

Off

Get Premium NCA-GENM Questions as Interactive Self Test Engine or PDF

Comments

Chosen Answer:
This is a voting comment (?) , you can switch to a simple comment.
Switch to a voting comment New
Nick name: Submit Cancel
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.
0
0
0
10