Bayesian Fine-tuning Yields Language Models that are as Bayesian as their Beliefs Allow
Language models (LMs) are increasingly used for tasks that require reasoning about hidden variables from a few observations, for which Bayesian inference is the normatively correct solution. While supervised fine-tuning of an LM on the outputs of an optimal $\textit{Bayesian}$ model leads to near-Bayesian behavior, sta...
Polina Tsvilodub, Andreas Waldis, Lin-Lu Qiu et al.
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