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cs.LG2026
Elicitation without Backpropagation: Steering Model Behavior by Optimizing the Latent Posterior
Garrett Baker, Vinayak Pathak, Daniel Murfet +1
In the \emph{latent posterior model} of transformer behavior, the next-token distribution arises from a posterior over latent predictive models conditioned on the context, mixed to…
cs.LG2026
What does a Bayes-filtered transformer believe? A predictive Monte Carlo approach
Afiq Abdillah Effiezal Aswadi, Haotong Ma, Susan Wei
A Bayes-filtered transformer (BFT) is a transformer trained on sequences that are generated in two steps: first a latent task is drawn from a prior, then observations are drawn con…
stat.ML2026
Uncertainty Decomposition for Bayes-Filtered Transformers via Bayesian Predictive Inference
Sandra Fortini, Kenyon Ng, Sonia Petrone +2
Bayes-filtered transformers are transformers meta-learned on sequences from a prior predictive distribution to approximate the corresponding posterior predictive distribution. They…