@inproceedings{takahashi-2024-hidetsune-semeval,
title = "Hidetsune at {S}em{E}val-2024 Task 4: An Application of Machine Learning to Multilingual Propagandistic Memes Identification Using Machine Translation",
author = "Takahashi, Hidetsune",
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-1.57/",
doi = "10.18653/v1/2024.semeval-1.57",
pages = "370--373",
abstract = "In this system paper for SemEval-2024 Task4 subtask 2b, I present my approach to identifying propagandistic memes in multiple languages. I firstly establish a baseline for English and then implement the model into other languages (Bulgarian, North Macedonian and Arabic) by using machine translation. Data from other subtasks (subtask 1, subtask 2a) are also used in addition to data for this subtask, and additional data from Kaggle are concatenated to these in order to enhance the model. The results show a high reliability of my English baseline and a room for improvement of its implementation."
}
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%0 Conference Proceedings
%T Hidetsune at SemEval-2024 Task 4: An Application of Machine Learning to Multilingual Propagandistic Memes Identification Using Machine Translation
%A Takahashi, Hidetsune
%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 takahashi-2024-hidetsune-semeval
%X In this system paper for SemEval-2024 Task4 subtask 2b, I present my approach to identifying propagandistic memes in multiple languages. I firstly establish a baseline for English and then implement the model into other languages (Bulgarian, North Macedonian and Arabic) by using machine translation. Data from other subtasks (subtask 1, subtask 2a) are also used in addition to data for this subtask, and additional data from Kaggle are concatenated to these in order to enhance the model. The results show a high reliability of my English baseline and a room for improvement of its implementation.
%R 10.18653/v1/2024.semeval-1.57
%U https://aclanthology.org/2024.semeval-1.57/
%U https://doi.org/10.18653/v1/2024.semeval-1.57
%P 370-373
Markdown (Informal)
[Hidetsune at SemEval-2024 Task 4: An Application of Machine Learning to Multilingual Propagandistic Memes Identification Using Machine Translation](https://aclanthology.org/2024.semeval-1.57/) (Takahashi, SemEval 2024)
ACL