Grokking reflects escape from a metastable low-dimensional regime where transverse curvature accumulates before generalization, with subspace motion necessary but curvature boost insufficient.
Grokking: Generalization beyond overfitting on small algorithmic datasets
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cs.LG 3years
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UNVERDICTED 3representative citing papers
Multi-task grokking in Transformers produces staggered generalization, low-dimensional manifolds, weight-decay phase structure, holographic solutions, and transverse redundancy.
Empirical tests confirm robust feature repulsion signs but reveal activation-dependent spectral lock-in in grokking, with x^2 yielding rank-2 updates at epoch ~174 and ReLU remaining rank-1.
citing papers explorer
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Low-Dimensional and Transversely Curved Optimization Dynamics in Grokking
Grokking reflects escape from a metastable low-dimensional regime where transverse curvature accumulates before generalization, with subspace motion necessary but curvature boost insufficient.
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The Geometry of Multi-Task Grokking: Transverse Instability, Superposition, and Weight Decay Phase Structure
Multi-task grokking in Transformers produces staggered generalization, low-dimensional manifolds, weight-decay phase structure, holographic solutions, and transverse redundancy.
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Feature Repulsion and Spectral Lock-in: An Empirical Study of Two-Layer Network Grokking
Empirical tests confirm robust feature repulsion signs but reveal activation-dependent spectral lock-in in grokking, with x^2 yielding rank-2 updates at epoch ~174 and ReLU remaining rank-1.