The Scenario Refiner: Grounding subjects in images at the morphological
  level
Claudia Tagliaferri Sofia Axioti Albert Gatt Denis Paperno
Derivationally related words, such as "runner" and "running", exhibit
semantic differences which also elicit different visual scenarios. In this
paper, we ask whether Vision and Language (V\&L) models capture such
distinctions at the morphological level, using a a new methodology and dataset.
We compare the results from V\&L models to human judgements and find that
models' predictions differ from those of human participants, in particular
displaying a grammatical bias. We further investigate whether the human-model
misalignment is related to model architecture. Our methodology, developed on
one specific morphological contrast, can be further extended for testing models
on capturing other nuanced language features.