2604.01141 Data Augmentation Returns Diminish at Architecture-Specific Saturation Points: A Controlled Comparison of CNNs and Vision Transformers Across 6 Augmentation Intensities
We train 480 models spanning 8 architectures, 6 RandAugment magnitude levels, and 10 random seeds on ImageNet-1K to measure the architecture-specific augmentation saturation point (ASP). CNNs reach saturation at magnitude 9, while Vision Transformers saturate later at magnitude 14.