Shared Information Geometry Across Large Language Models

Research shows that the Fisher-Rao geometry of next-token probabilities is shared across transformer, state-space, and recurrent models. This shared geometry supports semantic-category transfer and improves with scale, model-only calibration, and predictive accuracy.