2026
Sample Margin-Aware Recalibration of Temperature Scaling
ICML 2026poster
Deep neural networks frequently exhibit overconfidence, undermining reliability in safety-critical applications. Existing adaptive methods rely on indirectly learned proxies of sample difficulty. We establish the logit margin as a direct and principled hardness indicator. We prove that margin tightl…