Hadi Alizadeh


2024

pdf bib
Sharif-STR at SemEval-2024 Task 1: Transformer as a Regression Model for Fine-Grained Scoring of Textual Semantic Relations
Seyedeh Fatemeh Ebrahimi | Karim Akhavan Azari | Amirmasoud Iravani | Hadi Alizadeh | Zeinab Taghavi | Hossein Sameti
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)

This paper explores semantic textual relatedness (STR) using fine-tuning techniques on the RoBERTa transformer model, focusing on sentence-level STR within Track A (Supervised). The study evaluates the effectiveness of this approach across different languages, with promising results in English and Spanish but encountering challenges in Arabic.