Author

Andreas Waldis

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#natural language process... Preprint Sep 2026

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. · 0 citations

Preprint Jul 2026

AIMO Interpretability Challenge

We propose the AIMO Interpretability Challenge, a competition on distinguishing robust from spurious reasoning in frontier mathematical language models based on the models'internal mechanisms. The challenge is motivated by a central limitation of standard reasoning benchmarks: strong final-answer accuracy does not reve...

Michal vStef'anik, Philipp Mondorf, Andreas Waldis et al. · 0 citations