Skews in the Phenomenon Space Hinder Generalization in Text-to-Image Generation

arXiv:2403.16394v1 Announce Type: new
Abstract: The literature on text-to-image generation is plagued by issues of faithfully composing entities with relations. But there lacks a formal understanding of how entity-relation compositions can be effectively learned. Moreover, the underlying phenomenon space that meaningfully reflects the problem structure is not well-defined, leading to an arms race for larger quantities of data in the hope that generalization emerges out of large-scale pretraining. We hypothesize that the underlying phenomenological coverage has not been proportionally scaled …

abstract arxiv cs.ai cs.cl hinder image image generation literature relations space text text-to-image type understanding