"Language models have methods for detecting some ungrounded or confabulated answers, but these methods do not provide a universal guarantee of truth."
Farquhar and colleagues develop semantic-entropy methods that detect an important subset of hallucinations by measuring uncertainty over meanings rather than word sequences. Their results demonstrate that models can expose useful uncertainty signals while leaving the broader challenge of universally reliable factual grounding unresolved.
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