arXiv Computation and Language By Mandar Marathe, Manar Ali, Sara Nabhani, Raia Abu Ahmad, Ibrahim Baroud, Omar Momen

AraMIP: Extending MIPVU Towards Metaphor Identification in Arabic

Read the original on arXiv Computation and Language →

AraMIP introduces a new guideline for annotating metaphors in Arabic, building upon the established MIPVU framework and tailoring it to Arabic’s linguistic features. The authors distinguish three figurative types—Isti'ara (metaphor), kinaya (metonymy/indirect expression), and tashbih (simile)—and apply the procedure to a pilot dataset of 300 sentences (5,277 words). Their analysis highlights Arabic‑specific challenges such as morphological complexity, inconsistent dictionary sense ordering, and a lack of standardized contextual materials for annotators.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

arXiv Computation and Language
Aug 28

Why Current XAI Is Not Enough for Arabic NLP: A Critical Survey of the Explainability Gap

The paper surveys the state of Explainable AI (XAI) in Arabic NLP, highlighting three gaps: a method gap where Arabic XAI relies mainly on limited post‑hoc techniques; a task gap with most work focused on classification tasks and little on generation, retrieval, or dialogue; and a linguistic gap where explanations rarely address Arabic‑specific phenomena such as morphology, dialects, and diglossia. It proposes a taxonomy of tasks, methods, linguistic units, and evaluation practices, and outlines a research agenda for linguistically grounded Arabic XAI.

By Salima Lamsiyah, Ruslan Mitkov
arXiv AI
3d ago

Beyond Poetry: Can Large Language Models Generate Classical Arabic Maqamat?

arXiv:2609. 28245v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong performance in creative text generation, yet their ability to produce culturally grounded and stylistically constrained literary forms remains underexplored.

By AbdulRahman A. Morsy (Department of Computer Science, School of Engineering and Applied Sciences, George Washington University, Washington DC, United States), Aya Zirikly (Department of Computer Science, School of Engineering and Applied Sciences, George Washington University, Washington DC, United States, Center for Speech and Language Processing, Whiting School of Engineering, Johns Hopkins University, Baltimore MD, United States)