2026
Self-Soupervision: Cooking Model Soups without Labels
ICML 2026spotlight
Model soups are strange and strangely effective combinations of parameters. They take a model (the stock), fine-tune it into multiple models (the ingredients), and then mix their parameters back into one model (the soup) to improve predictions. While all known soups require supervised learning, and …