What is faithfulness in RAG evaluation?

Faithfulness measures whether the generated answer is grounded in the retrieved context, not in the model's internal knowledge. A faithful answer only uses facts from the retrieved chunks. Faithfulness catches hallucinations where the model asserts something the context does not support. It is one of the most important RAG metrics, often computed by an LLM judge comparing answer claims to context.