Statistical models view this relationship probabilistically, addressing it in terms of whether a human would likely infer H from P. In this paper, we wish to bridge these two perspectives, by arguing for a visually-grounded version of the Textual Entailment task.
we ask whether models can perform better if, in addition to P and H, there is also an image (corresponding to the relevant "world" or "situation").