AI RESEARCH
Probabilistic Calibration Is a Trainable Capability in Language Models
arXiv CS.CL
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ArXi:2605.11845v1 Announce Type: new Language models are increasingly used in settings where outputs must satisfy user-specified randomness constraints, yet their generation probabilities are often poorly calibrated to those targets. We study whether this capability can be improved directly through fine-tuning.