Deokgyu Seo


2024

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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
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)

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.