Noam Chomsky at SemEval-2023 Task 4: Hierarchical Similarity-aware Model for Human Value Detection

Sumire Honda, Sebastian Wilharm


Abstract
This paper presents a hierarchical similarity-aware approach for the SemEval-2023 task 4 human value detection behind arguments using SBERT. The approach takes similarity score as an additional source of information between the input arguments and the lower level of labels in a human value hierarchical dataset. Our similarity-aware model improved the similarity-agnostic baseline model, especially showing a significant increase in or the value categories with lowest scores by the baseline model.
Anthology ID:
2023.semeval-1.188
Volume:
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1359–1364
Language:
URL:
https://aclanthology.org/2023.semeval-1.188
DOI:
10.18653/v1/2023.semeval-1.188
Bibkey:
Cite (ACL):
Sumire Honda and Sebastian Wilharm. 2023. Noam Chomsky at SemEval-2023 Task 4: Hierarchical Similarity-aware Model for Human Value Detection. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1359–1364, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Noam Chomsky at SemEval-2023 Task 4: Hierarchical Similarity-aware Model for Human Value Detection (Honda & Wilharm, SemEval 2023)
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PDF:
https://aclanthology.org/2023.semeval-1.188.pdf