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New Arabic dataset Mawqif-v2 released for stance detection research

Researchers have introduced Mawqif-v2, an extended Arabic dataset designed to evaluate cross-target generalization in stance detection. This new dataset includes 996 manually annotated Arabic tweets from three distinct targets: Women Driving, E-Cars, and the Trimester System. It serves as a held-out evaluation set, complementing the original Mawqif dataset used for training. The paper also provides baseline results using various transformer models and large language models to enable reproducible research. AI

IMPACT Enhances evaluation capabilities for Arabic NLP models, particularly in understanding nuanced public opinion across different topics.

RANK_REASON The cluster contains a research paper detailing a new benchmark dataset for NLP tasks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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New Arabic dataset Mawqif-v2 released for stance detection research

COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Rasha Albalawi, Nuha Albadi, Hamzah Luqman, Maram Kurdi, Saad Ezzini, Asma Yamani, Ahmed Ashraf ·

    Mawqif-v2: An Arabic Benchmark Dataset for Cross-Target Stance Detection

    arXiv:2608.09539v1 Announce Type: new Abstract: Publicly available Arabic datasets for target-specific stance detection remain limited, particularly for evaluating cross-target generalization. This paper presents the Mawqif-v2 Extension, consisting of 996 manually annotated Arabi…