ArAIEval Shared Task: Propagandistic Techniques Detection in Unimodal and Multimodal Arabic Content
<|reference_start|>ArAIEval Shared Task: Propagandistic Techniques Detection in Unimodal and Multimodal Arabic Content: We present an overview of the second edition of the ArAIEval shared task, organized as part of the ArabicNLP 2024 conference co-located with ACL 2024. In this edition, ArAIEval offers two tasks: (i) detection of propagandistic textual spans with persuasion techniques identification in tweets and news articles, and (ii) distinguishing between propagandistic and non-propagandistic memes. A total of 14 teams participated in the final evaluation phase, with 6 and 9 teams participating in Tasks 1 and 2, respectively. Finally, 11 teams submitted system description papers. Across both tasks, we observed that fine-tuning transformer models such as AraBERT was at the core of the majority of the participating systems. We provide a description of the task setup, including a description of the dataset construction and the evaluation setup. We further provide a brief overview of the participating systems. All datasets and evaluation scripts are released to the research community (https://araieval.gitlab.io/). We hope this will enable further research on these important tasks in Arabic.<|reference_end|>
@article{hasanain2024araieval,
    title={ArAIEval Shared Task: Propagandistic Techniques Detection in Unimodal
  and Multimodal Arabic Content},
    author={Maram Hasanain, Md. Arid Hasan, Fatema Ahmed, Reem Suwaileh, Md.
  Rafiul Biswas, Wajdi Zaghouani, Firoj Alam},
    journal={arXiv preprint arXiv:2407.04247},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.04247},
    primaryClass={cs.CL cs.AI cs.CV}
}