The rise of memes as a tool for spreading propaganda presents a significant challenge in the current digital environment. In this paper, we outline our work for the ArAIEval Shared Task2 in ArabicNLP 2024. This study introduces a method for identifying propaganda in Arabic memes using a multimodal system that combines textual and visual indicators to enhance the result. Our approach achieves the first place in text classification with Macro-F1 of 78.69%, the third place in image classification with Macro-F1 of 65.92%, and the first place in multimodal classification with Macro-F1 of 80.51%

AlexUNLP-MZ at ArAIEval Shared Task: Contrastive Learning, LLM Features Extraction and Multi-Objective Optimization for Arabic Multi-Modal Meme Propaganda Detection

*Coffee Breaks will be provided between 10:30 and 11:00 and 15:30 and 16:00.* To view the workshop program in detail, click [here](https://arabicnlp2024.sigarab.org) [![](https://assets.underline.io/markdown_image/1/image/12613369ab2f6dd75393ffa8794ccdd3.png)](https://app.gather.town/app/7Rf2IGR6LODvPyOx/ACL2024Workshops?spawnToken=Lcj5Wbq4QE2hykuB5Jg0)

W18: The Second Arabic Natural Language Processing Conference (ArabicNLP)

workshop paper

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ACL 2024

The 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024) will take place in Bangkok, Thailand from August 11th to 16th, 2024. More information will be announced soon.

Mohamed Zaytoon

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AlexUNLP-MZ at ArAIEval Shared Task: Contrastive Learning, LLM Features Extraction and Multi-Objective Optimization for Arabic Multi-Modal Meme Propaganda Detection

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