@inproceedings{malkin-etal-2021-gpt,
title = "{GPT} Perdetry Test: Generating new meanings for new words",
author = "Malkin, Nikolay and
Lanka, Sameera and
Goel, Pranav and
Rao, Sudha and
Jojic, Nebojsa",
editor = "Toutanova, Kristina and
Rumshisky, Anna and
Zettlemoyer, Luke and
Hakkani-Tur, Dilek and
Beltagy, Iz and
Bethard, Steven and
Cotterell, Ryan and
Chakraborty, Tanmoy and
Zhou, Yichao",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.naacl-main.439",
doi = "10.18653/v1/2021.naacl-main.439",
pages = "5542--5553",
abstract = "Human innovation in language, such as inventing new words, is a challenge for pretrained language models. We assess the ability of one large model, GPT-3, to process new words and decide on their meaning. We create a set of nonce words and prompt GPT-3 to generate their dictionary definitions. We find GPT-3 produces plausible definitions that align with human judgments. Moreover, GPT-3{'}s definitions are sometimes preferred to those invented by humans, signaling its intriguing ability not just to adapt, but to add to the evolving vocabulary of the English language.",
}
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<abstract>Human innovation in language, such as inventing new words, is a challenge for pretrained language models. We assess the ability of one large model, GPT-3, to process new words and decide on their meaning. We create a set of nonce words and prompt GPT-3 to generate their dictionary definitions. We find GPT-3 produces plausible definitions that align with human judgments. Moreover, GPT-3’s definitions are sometimes preferred to those invented by humans, signaling its intriguing ability not just to adapt, but to add to the evolving vocabulary of the English language.</abstract>
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%0 Conference Proceedings
%T GPT Perdetry Test: Generating new meanings for new words
%A Malkin, Nikolay
%A Lanka, Sameera
%A Goel, Pranav
%A Rao, Sudha
%A Jojic, Nebojsa
%Y Toutanova, Kristina
%Y Rumshisky, Anna
%Y Zettlemoyer, Luke
%Y Hakkani-Tur, Dilek
%Y Beltagy, Iz
%Y Bethard, Steven
%Y Cotterell, Ryan
%Y Chakraborty, Tanmoy
%Y Zhou, Yichao
%S Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F malkin-etal-2021-gpt
%X Human innovation in language, such as inventing new words, is a challenge for pretrained language models. We assess the ability of one large model, GPT-3, to process new words and decide on their meaning. We create a set of nonce words and prompt GPT-3 to generate their dictionary definitions. We find GPT-3 produces plausible definitions that align with human judgments. Moreover, GPT-3’s definitions are sometimes preferred to those invented by humans, signaling its intriguing ability not just to adapt, but to add to the evolving vocabulary of the English language.
%R 10.18653/v1/2021.naacl-main.439
%U https://aclanthology.org/2021.naacl-main.439
%U https://doi.org/10.18653/v1/2021.naacl-main.439
%P 5542-5553
Markdown (Informal)
[GPT Perdetry Test: Generating new meanings for new words](https://aclanthology.org/2021.naacl-main.439) (Malkin et al., NAACL 2021)
ACL
- Nikolay Malkin, Sameera Lanka, Pranav Goel, Sudha Rao, and Nebojsa Jojic. 2021. GPT Perdetry Test: Generating new meanings for new words. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 5542–5553, Online. Association for Computational Linguistics.