Free NVIDIA NCA-GENL Exam Questions
Absolute Free NCA-GENL Exam Practice for Comprehensive Preparation
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NVIDIA NCA-GENL Exam Questions
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Provided By: NVIDIA
- Exam: NCA - Generative AI LLMs
- Certification: NVIDIA Certified Associate
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Total Questions: 395
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Updated On: Sep 04, 2026
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Rated: 4.9 |
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Online Users: 790
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Question 1
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Which of the following prompt engineering techniques is most effective for improving an LLM's performance on multi-step reasoning tasks?
Answer: D
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Question 2
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You are developing a generative AI model to create personalized content recommendations for users. The user base is highly diverse, with varying preferences and behaviors. The model must balance relevance with the risk of over-personalization, which could lead to filter bubbles. Which strategy would most effectively address this challenge?
Answer: D
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You are developing a generative AI model to create personalized content recommendations for users. The user base is highly diverse, with varying preferences and behaviors. The model must balance relevance with the risk of over-personalization, which could lead to filter bubbles. Which strategy would most effectively address this challenge?
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Question 3
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You have trained two different generative AI models, Model X and Model Y, on the same dataset. To compare their performance, you calculate the Mean Squared Error (MSE) and the proportion of explained variance (R²). Model X has a lower MSE but also a lower R² compared to Model Y. Which model is likely better at explaining the variability in the data?
Answer: C
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You have trained two different generative AI models, Model X and Model Y, on the same dataset. To compare their performance, you calculate the Mean Squared Error (MSE) and the proportion of explained variance (R²). Model X has a lower MSE but also a lower R² compared to Model Y. Which model is likely better at explaining the variability in the data?
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Question 4
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You are working on deploying a Large Language Model (LLM) for a financial institution where it needs to generate detailed reports based on user inputs. The LLM occasionally generates responses that are logically correct but irrelevant to the user's query. The senior team member suggests a modification in the model’s attention mechanism to improve relevance. What adjustment to the attention mechanism would most likely improve the relevance of the LLM’s responses?
Answer: A
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You are working on deploying a Large Language Model (LLM) for a financial institution where it needs to generate detailed reports based on user inputs. The LLM occasionally generates responses that are logically correct but irrelevant to the user's query. The senior team member suggests a modification in the model’s attention mechanism to improve relevance. What adjustment to the attention mechanism would most likely improve the relevance of the LLM’s responses?
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Question 5
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In the evaluation of Natural Language Processing (NLP) systems, what do ‘validity’ and ‘reliability’ imply regarding the selection of evaluation metrics?
Answer: B
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