The Role of Linguistic Priors in Measuring Compositional Generalization
  of Vision-Language Models
Chenwei Wu Li Erran Li Stefano Ermon Patrick Haffner Rong Ge Zaiwei Zhang
Compositionality is a common property in many modalities including natural
languages and images, but the compositional generalization of multi-modal
models is not well-understood. In this paper, we identify two sources of
visual-linguistic compositionality: linguistic priors and the interplay between
images and texts. We show that current attempts to improve compositional
generalization rely on linguistic priors rather than on information in the
image. We also propose a new metric for compositionality without such
linguistic priors.