Arabic Automatic Story Generation with Large Language Models
Ahmed El-Shangiti, Fakhraddin Alwajih, Muhammad Abdul-Mageed
Abstract
Large language models (LLMs) have recently emerged as a powerful tool for a wide range of language generation tasks. Nevertheless, this progress has been slower in Arabic. In this work, we focus on the task of generating stories from LLMs. For our training, we use stories acquired through machine translation (MT) as well as GPT-4. For the MT data, we develop a careful pipeline that ensures we acquire high-quality stories. For our GPT-4 data, we introduce crafted prompts that allow us to generate data well-suited to the Arabic context in both Modern Standard Arabic (MSA) and two Arabic dialects (Egyptian and Moroccan). For example, we generate stories tailored to various Arab countries on a wide host of topics. Our manual evaluation shows that our model fine-tuned on these training datasets can generate coherent stories that adhere to our instructions. We also conduct an extensive automatic and human evaluation comparing our models against state-of-the-art proprietary and open-source models. Our datasets and models will be made publicly available at https://github.com/UBC-NLP/arastories.- Anthology ID:
- 2024.arabicnlp-1.13
- Volume:
- Proceedings of The Second Arabic Natural Language Processing Conference
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Nizar Habash, Houda Bouamor, Ramy Eskander, Nadi Tomeh, Ibrahim Abu Farha, Ahmed Abdelali, Samia Touileb, Injy Hamed, Yaser Onaizan, Bashar Alhafni, Wissam Antoun, Salam Khalifa, Hatem Haddad, Imed Zitouni, Badr AlKhamissi, Rawan Almatham, Khalil Mrini
- Venues:
- ArabicNLP | WS
- SIG:
- SIGARAB
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 140–152
- Language:
- URL:
- https://aclanthology.org/2024.arabicnlp-1.13
- DOI:
- 10.18653/v1/2024.arabicnlp-1.13
- Cite (ACL):
- Ahmed El-Shangiti, Fakhraddin Alwajih, and Muhammad Abdul-Mageed. 2024. Arabic Automatic Story Generation with Large Language Models. In Proceedings of The Second Arabic Natural Language Processing Conference, pages 140–152, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Arabic Automatic Story Generation with Large Language Models (El-Shangiti et al., ArabicNLP-WS 2024)
- PDF:
- https://preview.aclanthology.org/autopr/2024.arabicnlp-1.13.pdf