Legend at ArAIEval Shared Task: Persuasion Technique Detection using a Language-Agnostic Text Representation Model

Olumide E. Ojo, Olaronke O. Adebanji, Hiram Calvo, Damian O. Dieke, Olumuyiwa E. Ojo +3 more
10/14/2023
cs.CL

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Abstract

In this paper, we share our best performing submission to the Arabic AI Tasks Evaluation Challenge (ArAIEval) at ArabicNLP 2023. Our focus was on Task 1, which involves identifying persuasion techniques in excerpts from tweets and news articles. The persuasion technique in Arabic texts was detected using a training loop with XLM-RoBERTa, a language-agnostic text representation model. This approach proved to be potent, leveraging fine-tuning of a multilingual language model. In our evaluation of the test set, we achieved a micro F1 score of 0.64 for subtask A of the competition.

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Cite this paper

@article{ojo2023legend,
  title  = {Legend at ArAIEval Shared Task: Persuasion Technique Detection using a Language-Agnostic Text Representation Model},
  author = {Olumide E. Ojo and Olaronke O. Adebanji and Hiram Calvo and Damian O. Dieke and Olumuyiwa E. Ojo and Seye E. Akinsanya and Tolulope O. Abiola and Anna Feldman},
  year   = {2023},
  eprint = {2310.09661},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.09661v1}
}

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