Retrieval-Augmented Generation (RAG) Objective Questions and Answers - Set 2

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 2 of the series.

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

Answer at least 12 questions to submit and verify answers.

16 What is ANN? Medium

17 Which improves latency in RAG? Medium

18 What is context window? Medium

19 What is hallucination in RAG? Medium

20 Which reduces hallucination? Medium

21 What is embedding dimensionality? High

22 Which improves retrieval recall? Medium

23 What is top-k retrieval? Medium

24 Which is a vector DB? Medium

25 What is FAISS? Medium

26 Which improves precision? High

27 What is query embedding? Medium

28 Which is used in semantic search? Medium

29 What is retrieval latency? Medium

30 Which improves scalability? High