Variational Routing: A Scalable Bayesian Framework for Calibrated Mixture-of-Experts Transformers 事件

Variational Routing: A Scalable Bayesian Framework for Calibrated Mixture-of-Experts Transformers arXiv:2603.09453v3 Announce Type: replace-cross Abstract: Foundation models are increasingly being deployed in contexts where understanding the uncertainty of their outputs is critical to ensuring responsible deployment. While Bayesian methods offer a principled approach to uncertainty quantification, their computational overhead renders their use impractical for training or inference at foundation