@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{\%}.",
}

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{\%}.
Fang, Christian Fang, Qixiang Nguyen, Dong
Epicurus at SemEval-2023 Task 4: Improving Prediction of Human Values behind Arguments by Leveraging Their Definitions