2 papers
cs.CV2025
What Drives Compositional Generalization? The Importance of Continuous Training Objectives in Visual Generative Models
Karim Farid, Rajat Sahay, Yumna Ali Alnaggar +4
Compositional generalization, the ability to generate novel combinations of known concepts, is a key ingredient for visual generative models. Yet, not all mechanisms that enable or…
cs.LG2024
On Calibration in Multi-Distribution Learning
Rajeev Verma, Volker Fischer, Eric Nalisnick
Modern challenges of robustness, fairness, and decision-making in machine learning have led to the formulation of multi-distribution learning (MDL) frameworks in which a predictor…