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

This story is from 2026-09-12. It is preserved in the archive; the latest stories are on the live feed.

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 \emph{when} it occurs…

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  1. 2026-09-12 04:00 · arXiv cs.AI
    Quantifying the Memorization-to-Generalization Transition: Scaling Laws and Phase Structure in Grokking

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