TY  - GEN
A1  - Zarriess, Sina
A1  - Schlangen, David
T1  - Objects of Unknown Categories
T2  - The 57th Annual Meeting of the Association for Computational Linguistics
N2  - Zero-shot learning in Language & Vision is the task of correctly labelling (or naming) objects of novel categories. Another strand of work in L&V aims at pragmatically informative rather than "correct" object descriptions, e.g. in reference games. We combine these lines of research and model zero-shot reference games, where a speaker needs to successfully refer to a novel object in an image. Inspired by models of "rational speech acts", we extend a neural generator to become a pragmatic speaker reasoning about uncertain object categories. As a result of this reasoning, the generator produces fewer nouns and names of distractor categories as compared to a literal speaker. We show that this conversational strategy for dealing with novel objects often improves communicative success, in terms of resolution accuracy of an automatic listener.
Y1  - 2019
SN  - 978-1-950737-48-2
SP  - 654
EP  - 659
PB  - Association for Computational Linguistics
CY  - Stroudsburg
ER  -