What do LLMs actually mean when they say they're uncertain? A calibration debate
sineadwilliamso · x · 2026-10-06
A short technical exchange on LLM uncertainty: asked whether RLCR-style approaches would perform better, the author agrees such models will likely be better calibrated since they behave more like traditional classifiers trained under proper losses.
But she's less interested in calibration metrics than in understanding what LLMs actually "mean" when they express uncertainty — a question about semantics rather than scores.
Related event: Statisticians debate what LLM uncertainty expressions really mean(2 posts)→
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