Italian Crossword Generator: Enhancing Education through Interactive Word Puzzles
Kamyar Zeinalipour, Tommaso laquinta, Asya Zanollo, Giovanni Angelini,, Leonardo Rigutini, Marco Maggini, Marco Gori

TL;DR
This paper presents an advanced system using state-of-the-art language models to generate and verify educational crossword puzzles, enhancing student engagement and learning outcomes.
Contribution
It introduces a novel approach combining fine-tuning and zero-shot learning of language models for high-quality crossword clue generation and verification.
Findings
Generated crosswords are engaging and educational.
High accuracy in clue quality assessment.
System outperforms previous methods in clue generation.
Abstract
Educational crosswords offer numerous benefits for students, including increased engagement, improved understanding, critical thinking, and memory retention. Creating high-quality educational crosswords can be challenging, but recent advances in natural language processing and machine learning have made it possible to use language models to generate nice wordplays. The exploitation of cutting-edge language models like GPT3-DaVinci, GPT3-Curie, GPT3-Babbage, GPT3-Ada, and BERT-uncased has led to the development of a comprehensive system for generating and verifying crossword clues. A large dataset of clue-answer pairs was compiled to fine-tune the models in a supervised manner to generate original and challenging clues from a given keyword. On the other hand, for generating crossword clues from a given text, Zero/Few-shot learning techniques were used to extract clues from the input…
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Text Readability and Simplification
