Retrieval-Augmented Generation (RAG) Objective Questions and Answers - Set 3

This RAG quiz contains carefully curated objective questions with correct answers and clear explanations. It is designed for developers and AI engineers preparing for real-world LLM applications, covering retrieval pipelines, vector search, embeddings, ranking, and optimization techniques. This is part 3 of the series.

Practice Retrieval-Augmented Generation (RAG) MCQs with Detailed Explanations

Answer at least 12 questions to submit and verify answers.

31 What is caching in RAG? Medium

32 What is semantic chunking? High

33 Which is bad chunking? Medium

34 What is metadata filtering? Medium

35 Which improves context quality? Medium

36 What is pipeline in RAG? Medium

37 Which is multi-hop retrieval? High

38 What is dense retrieval? Medium

39 What is sparse retrieval? Medium

40 Which combines dense + sparse? Medium

41 What is query rewriting? High

42 What is negative sampling? High

43 Which reduces cost? Medium

44 What is streaming in RAG? Medium

45 Which affects retrieval accuracy? Medium