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.
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.
Sep 2, 2025 · Definition of Grokking: Grokking refers to a surprising phenomenon of delayed generalization in neural network training. A model will perfectly fit the training data (near-100%.
Jul 11, 2025 · One such phenomenon is grokking. According to the Oxford English Dictionary, “to grok something” means “to understand something completely using your feelings rather than considering.
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.
Grokking refers to a fascinating phenomenon in deep learning where a neural network, after training for a significantly extended period—often long after it appears to have overfitted the training.
Nov 26, 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.
When Does Grokking Happen? It’s important to note that grokking is a contingent phenomenon — it goes away if model size, weight decay, data size and other hyper parameters aren’t just right.
