2026
Toward Calibrated Mixture-of-Experts Under Distribution Shift
ICML 2026poster
Calibration aligns a model's predictive uncertainty with the frequencies of its empirical outcomes and is important toward understanding and trusting reported probabilities. Recent work shows that enforcing calibration at the level of individual predictors can substantially improve ensemble performa…