Free NVIDIA NCA-GENL Exam Questions

Become NVIDIA Certified with updated NCA-GENL exam questions and correct answers

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Total 395 Questions | Updated On: Jun 16, 2026

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Question 1

Which metric is commonly used to evaluate machine-translation models?

A : F1 Score

B : BLEU score

C : ROUGE score

D : Perplexity

Answer: B

Question 2

What is the purpose of the NVIDIA NeMo Toolkit?

A : NeMo focuses on the morphology of a language by studying its words, and how they are formed.

B : NeMo helps researchers to develop models that trade-off size with minimum loss impact.

C : NeMo facilitates the creation of models for speech recognition and natural language understanding.

D : NeMo helps researchers develop state-of-the-art models for computer vision based on convolutions.

Answer: C

Question 3

What is Retrieval Augmented Generation (RAG)?

A : RAG is an architecture used to optimize the output of an LLM by retraining the model with domain-specific data.

B : RAG is a methodology that combines an information retrieval component with a response generator.

C : RAG is a method for manipulating and generating text-based data using Transformer-based LLMs.

D : RAG is a technique used to fine-tune pre-trained LLMs for improved performance.

Answer: B

Question 4

In the evaluation of Natural Language Processing (NLP) systems, what do ‘validity’ and ‘reliability’ imply regarding the selection of evaluation metrics?

A : Validity involves the metric’s ability to predict future trends in data, and reliability refers to its capacity to integrate with multiple data sources.

B : Validity ensures the metric accurately reflects the intended property to measure, while reliability ensures consistent results over repeated measurements.

C : Validity is concerned with the metric’s computational cost, while reliability is about its applicability across different NLP platforms.

D : Validity refers to the speed of metric computation, whereas reliability pertains to the metric’s performance in high-volume data processing

Answer: B

Question 5

In the development of trustworthy AI systems, what is the primary purpose of implementing redteaming exercises during the alignment process of large language models?

A : To optimize the model's inference speed for production deployment.

B : To identify and mitigate potential biases, safety risks, and harmful outputs.

C : To increase the model's parameter count for better performance.

D : To automate the collection of training data for fine-tuning.

Answer: B

Page: 1 / 79

Total 395 Questions | Updated On: Jun 16, 2026

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