AnalysisAI ModelsSeptember 11, 2026

Paper: LLM information geometry is shared across architectures

Read original source →arxiv.org

A paper on arXiv reports that next-token probabilities share a Fisher-Rao geometry across transformers, state-space, and recurrent models, enabling minimum-disturbance local interventions and reusable control. The shared read-out geometry also predicts learning dynamics and semantic-category transfer.

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