The Well-Tempered Classifier: Some Elementary Properties of Temperature Scaling 事件

The Well-Tempered Classifier: Some Elementary Properties of Temperature Scaling arXiv:2602.14862v2 Announce Type: replace-cross Abstract: Temperature scaling is a simple method that allows to control the uncertainty of probabilistic models. It is mostly used in two contexts: improving the calibration of classifiers and tuning the stochasticity of large language models (LLMs). In both cases, temperature scaling is the most popular method for the job. Despite its popularity, a rigorous theoretica