AIBullisharXiv – CS AI · 6h ago7/10
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Integrating Local and Global Entropy for Uncertainty Quantification in LLMs
Researchers propose Global-Local Uncertainty (GLU), a new method for quantifying uncertainty in large language models by combining hidden-state geometric entropy with token-level signals. The approach successfully identifies confident-but-wrong predictions that existing token-only methods miss, offering improved reliability assessment across multiple model families.