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arXiv · 1603.02618

The red one!: On learning to refer to things based on their discriminative properties

Angeliki Lazaridou·Nghia The Pham·Marco Baroni
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Abstract

As a first step towards agents learning to communicate about their visual environment, we propose a system that, given visual representations of a referent (cat) and a context (sofa), identifies their discriminative attributes, i.e., properties that distinguish them (has_tail). Moreover, despite the lack of direct supervision at the attribute level, the model learns to assign plausible attributes to objects (sofa-has_cushion). Finally, we present a preliminary experiment confirming the referential success of the predicted discriminative attributes.

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Angeliki Lazaridou, Nghia The Pham, Marco Baroni. 2016-03-08. The red one!: On learning to refer to things based on their discriminative properties. https://arxiv.org/abs/1603.02618

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