@inproceedings{fang-etal-2023-epicurus,
title = "Epicurus at {S}em{E}val-2023 Task 4: Improving Prediction of Human Values behind Arguments by Leveraging Their Definitions",
author = "Fang, Christian and
Fang, Qixiang and
Nguyen, Dong",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Da San Martino, Giovanni and
Tayyar Madabushi, Harish and
Kumar, Ritesh and
Sartori, Elisa},
booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.semeval-1.31",
doi = "10.18653/v1/2023.semeval-1.31",
pages = "221--229",
abstract = "We describe our experiments for SemEval-2023 Task 4 on the identification of human values behind arguments (ValueEval). Because human values are subjective concepts which require precise definitions, we hypothesize that incorporating the definitions of human values (in the form of annotation instructions and validated survey items) during model training can yield better prediction performance. We explore this idea and show that our proposed models perform better than the challenge organizers{'} baselines, with improvements in macro F1 scores of up to 18{\%}.",
}
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<abstract>We describe our experiments for SemEval-2023 Task 4 on the identification of human values behind arguments (ValueEval). Because human values are subjective concepts which require precise definitions, we hypothesize that incorporating the definitions of human values (in the form of annotation instructions and validated survey items) during model training can yield better prediction performance. We explore this idea and show that our proposed models perform better than the challenge organizers’ baselines, with improvements in macro F1 scores of up to 18%.</abstract>
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%0 Conference Proceedings
%T Epicurus at SemEval-2023 Task 4: Improving Prediction of Human Values behind Arguments by Leveraging Their Definitions
%A Fang, Christian
%A Fang, Qixiang
%A Nguyen, Dong
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F fang-etal-2023-epicurus
%X We describe our experiments for SemEval-2023 Task 4 on the identification of human values behind arguments (ValueEval). Because human values are subjective concepts which require precise definitions, we hypothesize that incorporating the definitions of human values (in the form of annotation instructions and validated survey items) during model training can yield better prediction performance. We explore this idea and show that our proposed models perform better than the challenge organizers’ baselines, with improvements in macro F1 scores of up to 18%.
%R 10.18653/v1/2023.semeval-1.31
%U https://aclanthology.org/2023.semeval-1.31
%U https://doi.org/10.18653/v1/2023.semeval-1.31
%P 221-229
Markdown (Informal)
[Epicurus at SemEval-2023 Task 4: Improving Prediction of Human Values behind Arguments by Leveraging Their Definitions](https://aclanthology.org/2023.semeval-1.31) (Fang et al., SemEval 2023)
ACL