Hallucination Testing
Also called: Hallucination Evaluation, Hallucination Assessment
A testing process that evaluates an AI system's tendency to generate fabricated, unsupported, or factually incorrect information by comparing its outputs against trusted references, provided context, or authoritative sources.
Explore more about Testing
Related terms
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.
Hallucination RateAn evaluation metric that measures the proportion of an AI system's outputs that contain fabricated, unsupported, or factually incorrect information relative to a trusted reference, provided context, or authoritative source.
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.
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.