In ML research, "grokking" is not used as a synonym for "generalization"; rather, it names a sometimes-observed delayed‑generalization training phenomenon in which training and held‑out performance do …

Jan 6, 2022 · In this paper we propose to study generalization of neural networks on small algorithmically generated datasets. In this setting, questions about data efficiency, memorization, …

Grok may be the only English word that derives from Martian. Yes, we do mean the language of the planet Mars. No, we're not getting spacey; we've just ventured into the realm of science fiction. Grok …

May 15, 2025 · Grokking forces us to reconsider established practices in training neural networks. It challenges the validity of early stopping criteria and suggests that a model appearing to overfit might …

Jun 14, 2024 · One of the most intriguing is the phenomenon of grokking, where neural networks exhibit surprisingly delayed generalization, achieving high performance on unseen data long after they have...

Grokking, or delayed generalization, is a phenomenon where generalization in a deep neural network (DNN) occurs long after achieving near zero training error. Previous studies have reported the …

Oct 13, 2025 · Grokking implies experiential, embodied learning, something beyond surface-level exposure. It hints of an orientation towards fluid intuition, rather than rigid knowing or memorization.

Apr 11, 2025 · Grokking describes when an AI system appears to suddenly "get it" after a lengthy period of seemingly minimal progress. Initially, the AI memorizes training examples without grasping …

Feb 3, 2025 · Grokking, or delayed generalization, is an intriguing learning phenomenon where test set loss decreases sharply only after a model’s training set loss has converged. This challenges …

Jun 20, 2025 · Grokking is a term used to describe a sudden change in how neural networks perform during their training. In this process, these networks can switch from merely memorizing information …