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What are label smoothing and mixup, and why do they help?

Two cheap regularizers that fix overconfident classifiers. The signal is knowing that one softens the target and the other softens the input, and exactly why softer signals calibrate the model. Here is the answer.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Two cheap regularizers that fix overconfident classifiers. The signal is knowing that one softens the target and the other softens the input, and exactly why softer signals calibrate the model. Here is the answer.

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