@inproceedings{auersperger-pecina-2022-defending,
title = "Defending Compositionality in Emergent Languages",
author = "Auersperger, Michal and
Pecina, Pavel",
editor = "Ippolito, Daphne and
Li, Liunian Harold and
Pacheco, Maria Leonor and
Chen, Danqi and
Xue, Nianwen",
booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop",
month = jul,
year = "2022",
address = "Hybrid: Seattle, Washington + Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.naacl-srw.35",
doi = "10.18653/v1/2022.naacl-srw.35",
pages = "285--291",
abstract = "Compositionality has traditionally been understood as a major factor in productivity of language and, more broadly, human cognition. Yet, recently some research started to question its status showing that artificial neural networks are good at generalization even without noticeable compositional behavior. We argue some of these conclusions are too strong and/or incomplete. In the context of a two-agent communication game, we show that compositionality indeed seems essential for successful generalization when the evaluation is done on a suitable dataset.",
}
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%0 Conference Proceedings
%T Defending Compositionality in Emergent Languages
%A Auersperger, Michal
%A Pecina, Pavel
%Y Ippolito, Daphne
%Y Li, Liunian Harold
%Y Pacheco, Maria Leonor
%Y Chen, Danqi
%Y Xue, Nianwen
%S Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop
%D 2022
%8 July
%I Association for Computational Linguistics
%C Hybrid: Seattle, Washington + Online
%F auersperger-pecina-2022-defending
%X Compositionality has traditionally been understood as a major factor in productivity of language and, more broadly, human cognition. Yet, recently some research started to question its status showing that artificial neural networks are good at generalization even without noticeable compositional behavior. We argue some of these conclusions are too strong and/or incomplete. In the context of a two-agent communication game, we show that compositionality indeed seems essential for successful generalization when the evaluation is done on a suitable dataset.
%R 10.18653/v1/2022.naacl-srw.35
%U https://aclanthology.org/2022.naacl-srw.35
%U https://doi.org/10.18653/v1/2022.naacl-srw.35
%P 285-291
Markdown (Informal)
[Defending Compositionality in Emergent Languages](https://aclanthology.org/2022.naacl-srw.35) (Auersperger & Pecina, NAACL 2022)
ACL
- Michal Auersperger and Pavel Pecina. 2022. Defending Compositionality in Emergent Languages. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop, pages 285–291, Hybrid: Seattle, Washington + Online. Association for Computational Linguistics.