OZemi at SemEval-2024 Task 1: A Simplistic Approach to Textual Relatedness Evaluation Using Transformers and Machine Translation

Hidetsune Takahashi, Xingru Lu, Sean Ishijima, Deokgyu Seo, Yongju Kim, Sehoon Park, Min Song, Kathylene Marante, Keitaro-luke Iso, Hirotaka Tokura, Emily Ohman


Abstract
In this system paper for SemEval-2024 Task 1 subtask A, we present our approach to evaluating the semantic relatedness of sentence pairs in nine languages. We use a mix of statistical methods combined with fine-tuned BERT transformer models for English and use the same model and machine-translated data for the other languages. This simplistic approach shows consistently reliable scores and achieves above-average rank in all languages.
Anthology ID:
2024.semeval-1.2
Volume:
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
7–12
Language:
URL:
https://aclanthology.org/2024.semeval-1.2
DOI:
10.18653/v1/2024.semeval-1.2
Bibkey:
Cite (ACL):
Hidetsune Takahashi, Xingru Lu, Sean Ishijima, Deokgyu Seo, Yongju Kim, Sehoon Park, Min Song, Kathylene Marante, Keitaro-luke Iso, Hirotaka Tokura, and Emily Ohman. 2024. OZemi at SemEval-2024 Task 1: A Simplistic Approach to Textual Relatedness Evaluation Using Transformers and Machine Translation. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 7–12, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
OZemi at SemEval-2024 Task 1: A Simplistic Approach to Textual Relatedness Evaluation Using Transformers and Machine Translation (Takahashi et al., SemEval 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.semeval-1.2.pdf
Supplementary material:
 2024.semeval-1.2.SupplementaryMaterial.txt
Supplementary material:
 2024.semeval-1.2.SupplementaryMaterial.zip