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Reliable Hallucination Detection in Large Language Models // Jiaxin Zhang // AI in Production Talk
April 25, 2024, 1 p.m. | MLOps.community
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Hallucination detection is a critical step toward understanding the trustworthiness of modern language models (LMs). To achieve this goal, we re-examine existing detection approaches based on the self-consistency of LMs and uncover two types of hallucinations resulting from 1) question-level and 2) model-level, which cannot be effectively identified through self-consistency check alone. Building upon this discovery, we propose a novel sampling-based method, i.e., semantic-aware cross-check consistency (SAC3) that expands on the principle of self-consistency checking. Our SAC3 approach …
abstract detection hallucination hallucinations language language models large language large language models lms modern production question talk types understanding
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