@inproceedings{jin-etal-2020-duluth,
title = "{D}uluth at {S}em{E}val-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines",
author = "Jin, Shuning and
Yin, Yue and
Tang, XianE and
Pedersen, Ted",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.128",
doi = "10.18653/v1/2020.semeval-1.128",
pages = "986--994",
abstract = "We use pretrained transformer-based language models in SemEval-2020 Task 7: Assessing the Funniness of Edited News Headlines. Inspired by the incongruity theory of humor, we use a contrastive approach to capture the surprise in the edited headlines. In the official evaluation, our system gets 0.531 RMSE in Subtask 1, 11th among 49 submissions. In Subtask 2, our system gets 0.632 accuracy, 9th among 32 submissions.",
}
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<abstract>We use pretrained transformer-based language models in SemEval-2020 Task 7: Assessing the Funniness of Edited News Headlines. Inspired by the incongruity theory of humor, we use a contrastive approach to capture the surprise in the edited headlines. In the official evaluation, our system gets 0.531 RMSE in Subtask 1, 11th among 49 submissions. In Subtask 2, our system gets 0.632 accuracy, 9th among 32 submissions.</abstract>
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%0 Conference Proceedings
%T Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines
%A Jin, Shuning
%A Yin, Yue
%A Tang, XianE
%A Pedersen, Ted
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F jin-etal-2020-duluth
%X We use pretrained transformer-based language models in SemEval-2020 Task 7: Assessing the Funniness of Edited News Headlines. Inspired by the incongruity theory of humor, we use a contrastive approach to capture the surprise in the edited headlines. In the official evaluation, our system gets 0.531 RMSE in Subtask 1, 11th among 49 submissions. In Subtask 2, our system gets 0.632 accuracy, 9th among 32 submissions.
%R 10.18653/v1/2020.semeval-1.128
%U https://aclanthology.org/2020.semeval-1.128
%U https://doi.org/10.18653/v1/2020.semeval-1.128
%P 986-994
Markdown (Informal)
[Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines](https://aclanthology.org/2020.semeval-1.128) (Jin et al., SemEval 2020)
ACL