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Certain but not Probable? Differentiating Certainty from Probability in LLM Token Outputs for Probabilistic Scenarios

arXiv — cs.CL•Tuesday, November 4, 2025 at 5:00:00 AM
NeutralArtificial Intelligence

Certain but not Probable? Differentiating Certainty from Probability in LLM Token Outputs for Probabilistic Scenarios

A recent study highlights the importance of reliable uncertainty quantification (UQ) in large language models, particularly for decision-support applications. The research emphasizes that while model certainty can be gauged through token logits and derived probability values, this method may fall short in probabilistic scenarios. Understanding the distinction between certainty and probability is crucial for enhancing the trustworthiness of these models in knowledge-intensive tasks, making this study significant for developers and researchers in the field.
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