@inproceedings{ebrahimi-etal-2024-sharif-str,
title = "Sharif-{STR} at {S}em{E}val-2024 Task 1: Transformer as a Regression Model for Fine-Grained Scoring of Textual Semantic Relations",
author = "Ebrahimi, Seyedeh Fatemeh and
Akhavan Azari, Karim and
Iravani, Amirmasoud and
Alizadeh, Hadi and
Taghavi, Zeinab and
Sameti, Hossein",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Tayyar Madabushi, Harish and
Da San Martino, Giovanni and
Rosenthal, Sara and
Ros{\'a}, Aiala},
booktitle = "Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.semeval-1.151",
doi = "10.18653/v1/2024.semeval-1.151",
pages = "1043--1052",
abstract = "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.",
}
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%0 Conference Proceedings
%T Sharif-STR at SemEval-2024 Task 1: Transformer as a Regression Model for Fine-Grained Scoring of Textual Semantic Relations
%A Ebrahimi, Seyedeh Fatemeh
%A Akhavan Azari, Karim
%A Iravani, Amirmasoud
%A Alizadeh, Hadi
%A Taghavi, Zeinab
%A Sameti, Hossein
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Tayyar Madabushi, Harish
%Y Da San Martino, Giovanni
%Y Rosenthal, Sara
%Y Rosá, Aiala
%S Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F ebrahimi-etal-2024-sharif-str
%X 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.
%R 10.18653/v1/2024.semeval-1.151
%U https://aclanthology.org/2024.semeval-1.151
%U https://doi.org/10.18653/v1/2024.semeval-1.151
%P 1043-1052
Markdown (Informal)
[Sharif-STR at SemEval-2024 Task 1: Transformer as a Regression Model for Fine-Grained Scoring of Textual Semantic Relations](https://aclanthology.org/2024.semeval-1.151) (Ebrahimi et al., SemEval 2024)
ACL