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

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.

在本文中，我们分享了我们在2023年阿拉伯自然语言处理大会（ArabicNLP）的阿拉伯人工智能任务评估挑战赛（ArAIEval）中表现最佳的提交内容。我们专注于任务1，该任务涉及识别推文和新闻文章摘录中的说服技巧。通过使用XLM - RoBERTa（一种与语言无关的文本表示模型）进行训练循环，检测阿拉伯语文本中的说服技巧。这种方法被证明是有效的，它利用了多语言模型的微调。在对测试集的评估中，我们在比赛的子任务A中取得了0.64的微F1分数。