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%.
@article{arxiv.2302.13925,
title = {Epicurus at SemEval-2023 Task 4: Improving Prediction of Human Values behind Arguments by Leveraging Their Definitions},
author = {Christian Fang and Qixiang Fang and Dong Nguyen},
journal= {arXiv preprint arXiv:2302.13925},
year = {2023}
}
Comments
Accepted to appear at the SemEval-2023 workshop, co-located with ACL 2023