检索增强生成

题集来源:AMIT SHEKHAR(amitshekhariitbhu)收录项目:ai-engineering-interview-questions查看原题集

题目目录

42 道原题
  1. What is re-ranking, and how does it improve RAG retrieval quality?

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  2. What is ColBERT, and how does late interaction retrieval work?

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  3. Compare reranker architectures: cross-encoder, ColBERT, and LLM-based rerankers.

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  4. How do you handle multi-document and multi-hop questions in RAG?

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  5. What is the "lost in the middle" problem in RAG systems?

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  6. How do you evaluate a RAG system? Explain faithfulness, relevance, and context precision/recall.

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  7. Explain Self-RAG. How does the model decide when to retrieve?

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  8. What is GraphRAG, and when would you use it over traditional RAG?

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  9. Vectorless RAG

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  10. How do you handle structured data (tables, SQL databases) in a RAG pipeline?

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