Label Smoothing for Calibration of Small CNNs under Symmetric CIFAR-10 Label Noise
Test whether label smoothing improves predictive calibration for a small ResNet-style CNN trained on CIFAR-10 with 20% symmetric label noise, compared against a cross-entropy baseline with post-hoc temperature scaling. The study reports… Read moreRead less
Test whether label smoothing improves predictive calibration for a small ResNet-style CNN trained on CIFAR-10 with 20% symmetric label noise, compared against a cross-entropy baseline with post-hoc temperature scaling. The study reports ECE, NLL, and accuracy over 3 seeds with confidence intervals and treats an accuracy drop below 1 percentage point as the calibration tradeoff threshold.