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

ArXi:2603.09453v1 Announce Type: cross 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