This paper introduces the first Turkish crossword puzzle generator designed to leverage the capabilities of large language models (LLMs) for educational purposes. In this work, we introduced two specially created datasets: one with over 180,000 unique answer-clue pairs for generating relevant clues from the given answer, and another with over 35,000 samples containing text, answer, category, and clue data, aimed at producing clues for specific texts and keywords within certain categories. Beyond entertainment, this generator emerges as an interactive educational tool that enhances memory, vocabulary, and problem-solving skills.

Crossword puzzles are popular linguistic games often used as tools to engage students in learning. Educational crosswords are characterized by less cryptic and more factual clues that distinguish them from traditional crossword puzzles. Despite there exist several publicly available clue-answer pair databases for traditional crosswords, educational clue-answer pairs datasets are missing. In this article, we propose a methodology to build educational clue generation datasets that can be used to instruct Large Language Models (LLMs). By gathering from Wikipedia pages informative content associated with relevant keywords, we use Large Language Models to automatically generate pedagogical clues related to the given input keyword and its context. With such an approach, we created clue-instruct, a dataset containing 44,075 unique examples with text-keyword pairs associated with three distinct crossword clues. We used clue-instruct to instruct different LLMs to generate educational clues from a given input content and keyword. Both human and automatic evaluations confirmed the quality of the generated clues, thus validating the effectiveness of our approach.

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.

Crossword puzzles have traditionally served not only as entertainment but also as an educational tool that can be used to acquire vocabulary and language proficiency. One strategy to enhance the educational purpose is personalization, such as including more words on a particular topic. This paper focuses on the case of encouraging people's interest in news and proposes a framework for automatically generating news-centric crossword puzzles. We designed possible scenarios and built a prototype as a constraint satisfaction and optimization problem, that is, containing as many news-derived words as possible. Our experiments reported the generation probabilities and time required under several conditions. The results showed that news-centric crossword puzzles can be generated even with few news-derived words. We summarize the current issues and future research directions through a qualitative evaluation of the prototype. This is the first proposal that a formulation of a constraint satisfaction and optimization problem can be beneficial as an educational application.

Note: The AI-made puzzle is near the end of this story. We don't need to wax poetic about ChatGPT's skills -- the world's already seeing it in action, as it churns out essays, 'inspirational' LinkedIn posts, even phishing emails that'd sucker the best of us. The AI chatbot is poised to replace the entire content writing industry, so there's a nagging question on every writer's mind: what can't it do? One of the answers, it turns out, is making a good word game. Now crosswords aren't easy things to build--apart from the actual'crossing' (interconnecting) of words, setters have to keep'product thinking' in mind.

An unconstrained crossword puzzle is a generalization of the constrained crossword problem. In this problem, only the word vocabulary, and optionally the grid dimensions are known. Hence, it not only requires the algorithm to determine the word locations, but it also needs to come up with the grid geometry. This paper discusses algorithmic strategies for automatic crossword puzzle generation in such an unconstrained setting. The strategies proposed cover the tasks of selection of words from a given vocabulary, selection of grid sizes, grid resizing and adjustments, metrics for word fitting, back-tracking techniques, and also clue generation. The strategies have been formulated based on a study of the effect of word sequence permutation order on grid fitting. An end-to-end algorithm that combines these strategies is presented, and its performance is analyzed. The techniques have been found to be successful in quickly producing well-packed puzzles of even large sizes. Finally, a few example puzzles generated by our algorithm are also provided.

Most, but not all, of the clues and answers relate to AI. An answer may be an acronym or an abbreviation even though not noted in the clue. Some liberties have been taken, but only because the puzzle is meant to be fun and interesting. If you'd like a few answers, check out the "AI in the news" column on page 120. And for all of the answers, see the solution on page 116.

Now there's a better way to cheat at crossword puzzles--with artificial intelligence. Researchers from three universities designed a system that uses a type of AI known as deep learning to help computers understand language more quickly and effectively. As a bonus, the researchers built a web-based tool that's handy when a particularly baffling crossword clue comes around. The crossword assistant is just a demo of how deep learning is improving machines' ability to understand language, said Felix Hill, a Ph.D. candidate at the University of Cambridge and lead author of a paper describing the research. Learning language is challenging for computers because it's difficult to recreate the rich and diverse information sources available to humans when they learn to speak and read, he said.

Struggling to think of a synonym? A new crossword-solving system could be the end of your lexicological lamentations. The web-based system, developed by researchers from the UK, US and Canada, makes use of artificial neural networks, which are based on the brain's own learning systems. The freely-available software was found to be better at solving standard crossword clues than commercial products. It can cope with single words (e.g.

Most, but not all, of the clues and answers relate to AI. An answer may be an acronym or an abbreviation even though not noted in the clue. Some liberties have been taken, but only because the puzzle is meant to be fun and interesting.