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Geometric Uncertainty for Detecting and Correcting Hallucinations in LLMs

Phillips, Edward et al.
arXiv (All) · Papers
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computation-and-language
Large language models are known to hallucinate, generating linguistically plausible but incorrect answers to questions. Uncertainty quantification has been proposed as a strategy to detect such behaviour, but existing methods lack a unified framework to assess reliability at both the prompt and answ
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