@inproceedings{maimaitituoheti-etal-2022-prompt,
title = "A Prompt Based Approach for Euphemism Detection",
author = "Maimaitituoheti, Abulimiti and
Yong, Yang and
Xiaochao, Fan",
editor = "Ghosh, Debanjan and
Beigman Klebanov, Beata and
Muresan, Smaranda and
Feldman, Anna and
Poria, Soujanya and
Chakrabarty, Tuhin",
booktitle = "Proceedings of the 3rd Workshop on Figurative Language Processing (FLP)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.flp-1.2",
doi = "10.18653/v1/2022.flp-1.2",
pages = "8--12",
abstract = "Euphemism is an indirect way to express sensitive topics. People can comfortably communicate with each other about sensitive topics or taboos by using euphemisms. The Euphemism Detection Shared Task in the Third Workshop on Figurative Language Processing co-located with EMNLP 2022 provided a euphemism detection dataset that was divided into the train set and the test set. We made euphemism detection experiments by prompt tuning pre-trained language models on the dataset. We used RoBERTa as the pre-trained language model and created suitable templates and verbalizers for the euphemism detection task. Our approach achieved the third-best score in the euphemism detection shared task. This paper describes our model participating in the task.",
}
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<abstract>Euphemism is an indirect way to express sensitive topics. People can comfortably communicate with each other about sensitive topics or taboos by using euphemisms. The Euphemism Detection Shared Task in the Third Workshop on Figurative Language Processing co-located with EMNLP 2022 provided a euphemism detection dataset that was divided into the train set and the test set. We made euphemism detection experiments by prompt tuning pre-trained language models on the dataset. We used RoBERTa as the pre-trained language model and created suitable templates and verbalizers for the euphemism detection task. Our approach achieved the third-best score in the euphemism detection shared task. This paper describes our model participating in the task.</abstract>
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%0 Conference Proceedings
%T A Prompt Based Approach for Euphemism Detection
%A Maimaitituoheti, Abulimiti
%A Yong, Yang
%A Xiaochao, Fan
%Y Ghosh, Debanjan
%Y Beigman Klebanov, Beata
%Y Muresan, Smaranda
%Y Feldman, Anna
%Y Poria, Soujanya
%Y Chakrabarty, Tuhin
%S Proceedings of the 3rd Workshop on Figurative Language Processing (FLP)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Hybrid)
%F maimaitituoheti-etal-2022-prompt
%X Euphemism is an indirect way to express sensitive topics. People can comfortably communicate with each other about sensitive topics or taboos by using euphemisms. The Euphemism Detection Shared Task in the Third Workshop on Figurative Language Processing co-located with EMNLP 2022 provided a euphemism detection dataset that was divided into the train set and the test set. We made euphemism detection experiments by prompt tuning pre-trained language models on the dataset. We used RoBERTa as the pre-trained language model and created suitable templates and verbalizers for the euphemism detection task. Our approach achieved the third-best score in the euphemism detection shared task. This paper describes our model participating in the task.
%R 10.18653/v1/2022.flp-1.2
%U https://aclanthology.org/2022.flp-1.2
%U https://doi.org/10.18653/v1/2022.flp-1.2
%P 8-12
Markdown (Informal)
[A Prompt Based Approach for Euphemism Detection](https://aclanthology.org/2022.flp-1.2) (Maimaitituoheti et al., Fig-Lang 2022)
ACL
- Abulimiti Maimaitituoheti, Yang Yong, and Fan Xiaochao. 2022. A Prompt Based Approach for Euphemism Detection. In Proceedings of the 3rd Workshop on Figurative Language Processing (FLP), pages 8–12, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.