Unveiling Memorization-Generalization Coexistence: A Case Study on Arithmetic Tasks with Label Noise

In three linesStudy of memorization-generalization coexistence in over-parameterized neural networks. With 80% label noise on arithmetic tasks, models memorize noisy labels while maintaining an internal generalization structure. Frequency-based extraction achieves near-perfect accuracy. Task-agnostic partitioning into generalization/memorization components proposed.

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