What is faithfulness in RAG and how do you measure it?
mediumAnswer
- Faithfulness = every claim in the answer is supported by the retrieved context (no hallucinated additions).
- Measurement: (1) LLM-judge extracts claims from the answer, verifies each against the context, computes fraction supported (Ragas' faithfulness metric); (2) attribution / citation checking — model must cite doc IDs, then verifier confirms each cite; (3) NLI-based scoring — pretrained NLI model checks entailment of each claim by the context.
- Critical for production trust — low-faithfulness answers erode user confidence.
Check yourself — multiple choice
- Same as accuracy
- Every answer claim supported by retrieved context; measure via LLM-judge extract-and-verify, citation check, or NLI entailment
- Only human eval
- Impossible to measure
Faithfulness: answer claims ⊆ retrieved context; measured via extract-and-verify or NLI.
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