A Measure-Theoretic Analysis of Reasoning in Transformers: Structural Generalization and Approximation Limits.

arXiv:2605.19944v2 Announce Type: replace-cross Abstract: Scaling laws for reasoning in large language models (LLMs) are well documented, but little theory explains their out-of-distribution (OOD) generalization. We formalize reasoning with optimal transport: