论文标题
阿拉伯仇恨言论的元AI 2022：多任务学习与仇恨言语分类的自我纠正
Meta AI at Arabic Hate Speech 2022: MultiTask Learning with Self-Correction for Hate Speech Classification
论文作者
论文摘要
在本文中，我们解决了阿拉伯细粒度仇恨言论检测共同的任务，并证明了对其三个子任务的基本线的显着改善。任务是预测一条推文是否包含（1）进攻语言；以及是否被考虑（2）仇恨言论，如果是这样，则可以预测（3）六个类别之一的（3）细粒度的仇恨言论标签。我们的最终解决方案是一种模型的合奏，该模型采用多任务学习和一种自通校正方法，在仇恨言语子任务中产生了82.7％的措施 - 与以前的工作相比，相对改善3.4％。
In this paper, we tackle the Arabic Fine-Grained Hate Speech Detection shared task and demonstrate significant improvements over reported baselines for its three subtasks. The tasks are to predict if a tweet contains (1) Offensive language; and whether it is considered (2) Hate Speech or not and if so, then predict the (3) Fine-Grained Hate Speech label from one of six categories. Our final solution is an ensemble of models that employs multitask learning and a self-consistency correction method yielding 82.7% on the hate speech subtask -- reflecting a 3.4% relative improvement compared to previous work.
