AI RESEARCH
What Drives Compositional Generalization? The Importance of Continuous Training Objectives in Visual Generative Models
arXiv CS.LG
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ArXi:2510.03075v3 Announce Type: replace-cross 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 inhibit it are fully understood. In this work, we conduct a systematic study of how various design choices influence compositional generalization in image and video generation in a positive or negative way. Through controlled experiments, we identify two key factors: (i) whether the.