A new paper titled "Confidence Comes from Experience: Experiential Confidence Estimation from Reasoning to Agents" argues that reliable confidence estimation is central to the trustworthy deployment of language models, since a calibrated estimate of the probability that an output is correct decides what to ship, what to escalate, and what to retry. The work notes that existing confidence estimators share a single design premise, though the provided source text is truncated before that premise is stated.
Reliable confidence estimation is increasingly central to the trustworthy deployment of language models: a calibrated estimate of the probability that an output is correct decides what to ship, what to escalate, and what to retry. Existing confidence estimators, however, share one design premise: th
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