Empirical tests on four GPT models across five uncertainty types found hyper-truth states (T+I+F>1) in 35% of cases, mostly under ethical contradictions and paradoxes.
A deeper look into aleatoric and epistemic uncertainty estimation.arXiv preprint arXiv:2204.09308,
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Breaking the Chains of Probability: Neutrosophic Logic as a New Framework for Epistemic Uncertainty in Large Language Models
Empirical tests on four GPT models across five uncertainty types found hyper-truth states (T+I+F>1) in 35% of cases, mostly under ethical contradictions and paradoxes.