# Quantifying the Memorization-to-Generalization Transition: Scaling Laws and Phase Structure in Grokking

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**Published:** 2026年9月12日
**Author:** Anish Kataria
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/zh/articles/quantifying-the-memorization-to-generalization-transition-scaling-laws-a

arXiv:2609.10657v1 Announce Type: new Abstract: Neural networks trained past memorization frequently undergo a delayed transition to generalization, a phenomenon known as grokking. Despite theoretical progress on \emph{why} this transition occurs, the quantitative structure of…

> 内容来自原始来源： **arXiv — cs.AI**
> [在 arXiv — cs.AI 阅读全文](https://arxiv.org/abs/2609.10657)

**标签：** #arXiv

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