@inproceedings{tomasulo-etal-2020-ynu,
title = "{YNU}-{HPCC} at {S}em{E}val-2020 Task 7: Using an Ensemble {B}i{GRU} Model to Evaluate the Humor of Edited News Titles",
author = "Tomasulo, Joseph and
Wang, Jin and
Zhang, Xuejie",
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-1.110",
doi = "10.18653/v1/2020.semeval-1.110",
pages = "871--875",
abstract = "This paper describes an ensemble model designed for Semeval-2020 Task 7. The task is based on the Humicroedit dataset that is comprised of news titles and one-word substitutions designed to make them humorous. We use BERT, FastText, Elmo, and Word2Vec to encode these titles then pass them to a bidirectional gated recurrent unit (BiGRU) with attention. Finally, we used XGBoost on the concatenation of the results of the different models to make predictions.",
}
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<abstract>This paper describes an ensemble model designed for Semeval-2020 Task 7. The task is based on the Humicroedit dataset that is comprised of news titles and one-word substitutions designed to make them humorous. We use BERT, FastText, Elmo, and Word2Vec to encode these titles then pass them to a bidirectional gated recurrent unit (BiGRU) with attention. Finally, we used XGBoost on the concatenation of the results of the different models to make predictions.</abstract>
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%0 Conference Proceedings
%T YNU-HPCC at SemEval-2020 Task 7: Using an Ensemble BiGRU Model to Evaluate the Humor of Edited News Titles
%A Tomasulo, Joseph
%A Wang, Jin
%A Zhang, Xuejie
%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 tomasulo-etal-2020-ynu
%X This paper describes an ensemble model designed for Semeval-2020 Task 7. The task is based on the Humicroedit dataset that is comprised of news titles and one-word substitutions designed to make them humorous. We use BERT, FastText, Elmo, and Word2Vec to encode these titles then pass them to a bidirectional gated recurrent unit (BiGRU) with attention. Finally, we used XGBoost on the concatenation of the results of the different models to make predictions.
%R 10.18653/v1/2020.semeval-1.110
%U https://aclanthology.org/2020.semeval-1.110
%U https://doi.org/10.18653/v1/2020.semeval-1.110
%P 871-875
Markdown (Informal)
[YNU-HPCC at SemEval-2020 Task 7: Using an Ensemble BiGRU Model to Evaluate the Humor of Edited News Titles](https://aclanthology.org/2020.semeval-1.110) (Tomasulo et al., SemEval 2020)
ACL