@inproceedings{wang-markov-2024-cltl-araieval,
title = "{CLTL} at {A}r{AIE}val Shared Task: Multimodal Propagandistic Memes Classification Using Transformer Models",
author = "Wang, Yeshan and
Markov, Ilia",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha, Ibrahim and
Abdelali, Ahmed and
Touileb, Samia and
Hamed, Injy and
Onaizan, Yaser and
Alhafni, Bashar and
Antoun, Wissam and
Khalifa, Salam and
Haddad, Hatem and
Zitouni, Imed and
AlKhamissi, Badr and
Almatham, Rawan and
Mrini, Khalil",
booktitle = "Proceedings of The Second Arabic Natural Language Processing Conference",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.arabicnlp-1.51",
doi = "10.18653/v1/2024.arabicnlp-1.51",
pages = "501--506",
abstract = "We present the CLTL system designed for the ArAIEval Shared Task 2024 on multimodal propagandistic memes classification in Arabic. The challenge was divided into three subtasks: identifying propagandistic content from textual modality of memes (subtask 2A), from visual modality of memes (subtask 2B), and in a multimodal scenario when both modalities are combined (subtask 2C). We explored various unimodal transformer models for Arabic language processing (subtask 2A), visual models for image processing (subtask 2B), and concatenated text and image embeddings using the Multilayer Perceptron fusion module for multimodal propagandistic memes classification (subtask 2C). Our system achieved 77.96{\%} for subtask 2A, 71.04{\%} for subtask 2B, and 79.80{\%} for subtask 2C, ranking 2nd, 1st, and 3rd on the leaderboard.",
}
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%0 Conference Proceedings
%T CLTL at ArAIEval Shared Task: Multimodal Propagandistic Memes Classification Using Transformer Models
%A Wang, Yeshan
%A Markov, Ilia
%Y Habash, Nizar
%Y Bouamor, Houda
%Y Eskander, Ramy
%Y Tomeh, Nadi
%Y Abu Farha, Ibrahim
%Y Abdelali, Ahmed
%Y Touileb, Samia
%Y Hamed, Injy
%Y Onaizan, Yaser
%Y Alhafni, Bashar
%Y Antoun, Wissam
%Y Khalifa, Salam
%Y Haddad, Hatem
%Y Zitouni, Imed
%Y AlKhamissi, Badr
%Y Almatham, Rawan
%Y Mrini, Khalil
%S Proceedings of The Second Arabic Natural Language Processing Conference
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F wang-markov-2024-cltl-araieval
%X We present the CLTL system designed for the ArAIEval Shared Task 2024 on multimodal propagandistic memes classification in Arabic. The challenge was divided into three subtasks: identifying propagandistic content from textual modality of memes (subtask 2A), from visual modality of memes (subtask 2B), and in a multimodal scenario when both modalities are combined (subtask 2C). We explored various unimodal transformer models for Arabic language processing (subtask 2A), visual models for image processing (subtask 2B), and concatenated text and image embeddings using the Multilayer Perceptron fusion module for multimodal propagandistic memes classification (subtask 2C). Our system achieved 77.96% for subtask 2A, 71.04% for subtask 2B, and 79.80% for subtask 2C, ranking 2nd, 1st, and 3rd on the leaderboard.
%R 10.18653/v1/2024.arabicnlp-1.51
%U https://aclanthology.org/2024.arabicnlp-1.51
%U https://doi.org/10.18653/v1/2024.arabicnlp-1.51
%P 501-506
Markdown (Informal)
[CLTL at ArAIEval Shared Task: Multimodal Propagandistic Memes Classification Using Transformer Models](https://aclanthology.org/2024.arabicnlp-1.51) (Wang & Markov, ArabicNLP-WS 2024)
ACL