Abstract
Numerous languages exhibit shared characteristics, especially in morphological features. For instance, Arabic and Russian both belong to the fusional language category. The question arises: Do such common traits influence language comprehension across diverse linguistic backgrounds? This study explores the possibility of transferring comprehension skills across languages to Arabic in a zero-shot scenario. Specifically, we demonstrate that training language models on other languages can enhance comprehension of Arabic, as evidenced by our evaluations in three key tasks: natural language inference, question answering, and named entity recognition. Our experiments reveal that certain morphologically rich languages (MRLs), such as Russian, display similarities to Arabic when assessed in a zero-shot context, particularly in tasks like question answering and natural language inference. However, this similarity is less pronounced in tasks like named entity recognition.- Anthology ID:
- 2023.arabicnlp-1.26
- Volume:
- Proceedings of ArabicNLP 2023
- Month:
- December
- Year:
- 2023
- Address:
- Singapore (Hybrid)
- Editors:
- Hassan Sawaf, Samhaa El-Beltagy, Wajdi Zaghouani, Walid Magdy, Ahmed Abdelali, Nadi Tomeh, Ibrahim Abu Farha, Nizar Habash, Salam Khalifa, Amr Keleg, Hatem Haddad, Imed Zitouni, Khalil Mrini, Rawan Almatham
- Venues:
- ArabicNLP | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 324–334
- Language:
- URL:
- https://aclanthology.org/2023.arabicnlp-1.26
- DOI:
- 10.18653/v1/2023.arabicnlp-1.26
- Cite (ACL):
- Zaid Alyafeai and Moataz Ahmed. 2023. Investigating Zero-shot Cross-lingual Language Understanding for Arabic. In Proceedings of ArabicNLP 2023, pages 324–334, Singapore (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Investigating Zero-shot Cross-lingual Language Understanding for Arabic (Alyafeai & Ahmed, ArabicNLP-WS 2023)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2023.arabicnlp-1.26.pdf