New grokking research explains plateau length, weight decay and init effects

CatAstro_Piyush · x · 2026-10-21

Researcher dohmatobelvis and PhD student gningbayemalick released new work offering deep insights into the still poorly understood grokking phenomenon.

The work addresses core questions:

The accompanying figure shows a fast/slow dynamics decomposition: learning relaxes quickly onto an invariant manifold, a slower phase at timescale 1/ε (set by SNR) learns the core feature weight and accounts for the long plateau, and a final slowest phase—present only with unbalanced initialization—relaxes the "harmonic dual" variable at timescale 1/λ set by weight decay.

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