Entropy Distribution as a Fingerprint for Hallucinations in Generative Models

ArXi:2605.28264v1 Announce Type: new Large Language Models (LLMs) often generate factually incorrect outputs, commonly termed hallucinations, that undermine trust and limit deployment in high-stakes settings. Existing hallucination detection methods typically require multiple forward passes, or access to model internals.