@inproceedings{weissenhorn-etal-2022-compositional,
title = "Compositional generalization with a broad-coverage semantic parser",
author = "Wei{\ss}enhorn, Pia and
Donatelli, Lucia and
Koller, Alexander",
editor = "Nastase, Vivi and
Pavlick, Ellie and
Pilehvar, Mohammad Taher and
Camacho-Collados, Jose and
Raganato, Alessandro",
booktitle = "Proceedings of the 11th Joint Conference on Lexical and Computational Semantics",
month = jul,
year = "2022",
address = "Seattle, Washington",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.starsem-1.4/",
doi = "10.18653/v1/2022.starsem-1.4",
pages = "44--54",
abstract = "We show how the AM parser, a compositional semantic parser (Groschwitz et al., 2018) can solve compositional generalization on the COGS dataset. It is the first semantic parser that achieves high accuracy on both naturally occurring language and the synthetic COGS dataset. We discuss implications for corpus and model design for learning human-like generalization. Our results suggest that compositional generalization can be best achieved by building compositionality into semantic parsers."
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%0 Conference Proceedings
%T Compositional generalization with a broad-coverage semantic parser
%A Weißenhorn, Pia
%A Donatelli, Lucia
%A Koller, Alexander
%Y Nastase, Vivi
%Y Pavlick, Ellie
%Y Pilehvar, Mohammad Taher
%Y Camacho-Collados, Jose
%Y Raganato, Alessandro
%S Proceedings of the 11th Joint Conference on Lexical and Computational Semantics
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, Washington
%F weissenhorn-etal-2022-compositional
%X We show how the AM parser, a compositional semantic parser (Groschwitz et al., 2018) can solve compositional generalization on the COGS dataset. It is the first semantic parser that achieves high accuracy on both naturally occurring language and the synthetic COGS dataset. We discuss implications for corpus and model design for learning human-like generalization. Our results suggest that compositional generalization can be best achieved by building compositionality into semantic parsers.
%R 10.18653/v1/2022.starsem-1.4
%U https://aclanthology.org/2022.starsem-1.4/
%U https://doi.org/10.18653/v1/2022.starsem-1.4
%P 44-54
Markdown (Informal)
[Compositional generalization with a broad-coverage semantic parser](https://aclanthology.org/2022.starsem-1.4/) (Weißenhorn et al., *SEM 2022)
ACL