NCA-GENM Question 76
Select 4A data scientist is building a multimodal model that combines textual and visual data for medical image diagnosis. During the research phase, they notice that the textual dataset has fewer examples compared to the visual dataset. Which factors should the data scientist consider to ensure the research results are not biased or compromised?
- A
The imbalance in dataset sizes between textual and visual data
- B
The potential for overfitting due to the smaller size of the textual dataset
- C
The quality and relevance of the textual and visual data to the research problem
- D
The compatibility of the model architecture with multimodal data input
- E
The computational cost of training the model on a balanced dataset
Show answer and explanation
Correct answers: A, B, C, D
Explanation
In multimodal generative AI research, ensuring balanced, high-quality datasets and using compatible architectures are key to identifying accurate relationships and trends. Addressing potential issues like data imbalance or overfitting ensures the research results are reliable and meaningful. Computational cost, while important, is not a direct factor in the validity of the research conclusions.
- A. Correct.
An imbalance in dataset sizes can skew the model's learning process and lead to biased predictions, so this is a critical factor to address.
- B. Correct.
A smaller dataset can lead to overfitting, where the model memorizes the data instead of generalizing, affecting the reliability of the results.
- C. Correct.
The quality and relevance of the data are crucial to ensure the model learns meaningful relationships and trends for the research problem.
- D. Correct.
The model architecture must support multimodal inputs effectively; otherwise, the results could be inaccurate or misleading.
- E. Incorrect.
Although computational cost is an important consideration, it does not directly impact the relationships or trends in the research results.