GenAI & LLM Engineering Objective Questions and Answers - Set 4

This GenAI & LLM engineering quiz contains carefully curated objective questions with correct answers and clear explanations. It is designed for developers and ML engineers to test your skills in building, optimizing, evaluating, and deploying LLM-powered applications. This is part 4 of the series.

Practice GenAI & LLM Engineering MCQs with Detailed Explanations

Answer at least 12 questions to submit and verify answers.

46 What is a key challenge in evaluating LLMs for reasoning tasks? Hard

47 Which method improves robustness against adversarial prompts? Hard

48 What is the main benefit of asynchronous inference in LLM APIs? Medium

49 Which practice best supports continuous improvement of prompts? Medium

50 What is the main risk of exposing internal prompts to end users? Hard

51 Which approach improves determinism in structured outputs? Medium

52 What is the main drawback of relying solely on fine-tuning instead of RAG? Medium

53 Which strategy best supports cost control in peak traffic scenarios? Hard

54 What is the key challenge of multi-agent LLM systems? Hard

55 Which technique improves grounding when retrieved context is noisy? Hard

56 What is the main benefit of token streaming to frontend apps? Medium

57 Which failure mode occurs when the LLM follows retrieved context even if it is incorrect? Hard

58 Which method helps ensure structured JSON outputs from LLMs? Medium

59 What is the main operational risk of long-running agent workflows? Hard

60 Which approach best supports safe deployment of autonomous LLM agents? Hard