CUFE at StanceEval2024: Arabic Stance Detection with Fine-Tuned Llama-3 Model

AbstractIn NLP, stance detection identifies a writer’s position or viewpoint on a particular topic or entity from their text and social media activity, which includes preferences and relationships.Researchers have been exploring techniques and approaches to develop effective stance detection systems.Large language models’ latest advancements offer a more effective solution to the stance detection problem. This paper proposes fine-tuning the newly released 8B-parameter Llama 3 model from Meta GenAI for Arabic text stance detection.The proposed method was ranked ninth in the StanceEval 2024 Task on stance detection in Arabic language achieving a Macro average F1 score of 0.7647.