Databricks Certified Generative AI Engineer Associate · Free Practice Question Medium
Question 20
A Generative AI Engineer is tasked with designing a system that converts long academic papers into concise summaries for students. The system should highlight key arguments and conclusions. What LLM configuration is most effective?
- A Fine-tune a summarization LLM on academic texts to generate concise summaries.
- B Use a generic LLM without fine-tuning.
- C Reduce the model’s response length to ensure conciseness.
- D Increase the model’s temperature to produce more diverse summaries.
Reveal correct answer
Correct answer: A
Explanation
Fine-tuning a summarization LLM ensures that the generated summaries capture key arguments and conclusions accurately.A. Correct: Fine-tuning on domain-specific data ensures accurate and relevant summaries tailored to academic content.
B. Incorrect: Generic models may generate summaries that lack domain-specific insights.
C. Incorrect: Reducing response length does not guarantee meaningful summaries.
D. Incorrect: Higher temperature introduces randomness, which can reduce summary accuracy.
Discussion
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