self rag

Applied AI interview questions tagged self rag, across every topic.

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Concepts behind "self rag"

The curriculum that explains the ideas these questions test.

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Agentic and Corrective RAGStandard RAG retrieves once and generates; agentic RAG wraps retrieval in a loop so the model decides whether to retrieve, what to query, evaluates the results, and retrieves again until it has what it needs. Corrective RAG adds a grader that checks retrieval quality and takes corrective action (re-retrieve, web search, or discard) when the context is poor. Applied-AI interviews probe it because complex, multi-hop questions defeat single-shot RAG, and self-correcting retrieval is the fix, at the cost of more calls and agent-reliability concerns.

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