CIFAR-10.1 showed that state-of-the-art models lost roughly 3–4 percentage points of top-1 accuracy when the test distribution shifted slightly around 2019. It’s a tidy reminder that pattern fit isn’t pattern generalization, and why test set integrity matters as much as architecture tweaks. What other small dataset tweaks have you seen unmask leakage or overfitting?