In this paper, we investigate whether a neural network model can learn the meaning of natural language quantifiers (no, some and all) from their use in visual contexts. We show that memory networks perform well in this task, and that explicit counting is not necessary to the system’s performance, supporting psycholinguistic evidence on the acquisition of quantifiers.
['Ionut Sorodoc', 'Angeliki Lazaridou', 'Gemma Boleda', 'Aurélie Herbelot', 'Sandro Pezzelle', 'Raffaella Bernardi']
"Look, some green circles!": Learning to quantify from images