mlsanityData to 7 Oct 2026

ArabIcros: AI-Powered Arabic Crossword Puzzle Generation for Educational Applications

arXiv 2312.01339 ↗First posted 3 Dec 2023cs.CL cs.AIcited by 5

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Abstract (arXiv)

This paper presents the first Arabic crossword puzzle generator driven by advanced AI technology. Leveraging cutting-edge large language models including GPT4, GPT3-Davinci, GPT3-Curie, GPT3-Babbage, GPT3-Ada, and BERT, the system generates distinctive and challenging clues. Based on a dataset comprising over 50,000 clue-answer pairs, the generator employs fine-tuning, few/zero-shot learning strategies, and rigorous quality-checking protocols to enforce the generation of high-quality clue-answer pairs. Importantly, educational crosswords contribute to enhancing memory, expanding vocabulary, and promoting problem-solving skills, thereby augmenting the learning experience through a fun and engaging approach, reshaping the landscape of traditional learning methods. The overall system can be exploited as a powerful educational tool that amalgamates AI and innovative learning techniques, heralding a transformative era for Arabic crossword puzzles and the intersection of technology and education.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 4 of its 22 references that are in the map. First posted on arXiv 3 Dec 2023.

Builds on

4 of 22 references.

References · 4

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2020KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Mediacited by 84
  4. 2022Is GPT-3 all you need for Visual Question Answering in Cultural Heritage?cited by 6

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Citing papers per year: 2024: 4; 2025: 1.

5 papers.