@inproceedings{zarriess-schlangen-2019-know,
title = "Know What You Don`t Know: Modeling a Pragmatic Speaker that Refers to Objects of Unknown Categories",
author = "Zarrie{\ss}, Sina and
Schlangen, David",
editor = "Korhonen, Anna and
Traum, David and
M{\`a}rquez, Llu{\'i}s",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/P19-1063/",
doi = "10.18653/v1/P19-1063",
pages = "654--659",
abstract = "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 {\textquotedblleft}correct{\textquotedblright} 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 {\textquotedblleft}rational speech acts{\textquotedblright}, 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."
}
Markdown (Informal)
[Know What You Don’t Know: Modeling a Pragmatic Speaker that Refers to Objects of Unknown Categories](https://preview.aclanthology.org/jlcl-multiple-ingestion/P19-1063/) (Zarrieß & Schlangen, ACL 2019)
ACL