Hallucination Detection
Also called: Hallucination Checking, Hallucination Verification
The process of identifying AI-generated outputs that contain fabricated, inaccurate, or unsupported information by comparing responses against trusted sources, retrieved context, or established facts before or after they are presented.
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Related terms
The process of verifying that an AI system's responses are supported by the provided context, retrieved knowledge, or authoritative sources before they are presented or acted upon, helping prevent hallucinations and unsupported claims.
Fact CheckingThe process of verifying the factual accuracy of AI-generated content by comparing claims against trusted sources, evidence, or authoritative knowledge before or after a response is produced.
GroundednessAn evaluation metric that measures whether an AI system's output is supported by the provided context, retrieved information, or source material without introducing unsupported claims or hallucinations.
Retrieval-Augmented GenerationRAGAn architectural pattern that enhances generative model responses by retrieving relevant information from external knowledge bases.