LLMs Should Express Uncertainty Explicitly

ArXi:2604.05306v1 Announce Type: cross Large language models are increasingly used in settings where uncertainty must drive decisions such as abstention, retrieval, and verification. Most existing methods treat uncertainty as a latent quantity to estimate after generation rather than a signal the model is trained to express. We instead study uncertainty as an interface for control.