“The results indicate that the attention-based models profoundly confuse hate speech with offensive and normal language. However, the pre-trained models outperform state-of-the-art results in terms of accurately predicting the hateful instances.” https://aclanthology.org/2020.alw-1.3.pdf Share this: Click to share on Facebook (Opens in new window) Facebook Click to share on X (Opens in new window) X Like this:Like Loading... Post navigation HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection (AAAI) Automatic Detection of Cyberbullying and Abusive Language in Arabic Content on Social Networks: A Survey (Elsevier)