{"ID":2844873,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.05114","arxiv_id":"2511.05114","title":"Usando LLMs para Programar Jogos de Tabuleiro e Variações","abstract":"Creating programs to represent board games can be a time-consuming task. Large Language Models (LLMs) arise as appealing tools to expedite this process, given their capacity to efficiently generate code from simple contextual information. In this work, we propose a method to test how capable three LLMs (Claude, DeepSeek and ChatGPT) are at creating code for board games, as well as new variants of existing games.","short_abstract":"Creating programs to represent board games can be a time-consuming task. Large Language Models (LLMs) arise as appealing tools to expedite this process, given their capacity to efficiently generate code from simple contextual information. In this work, we propose a method to test how capable three LLMs (Claude, DeepSee...","url_abs":"https://arxiv.org/abs/2511.05114","url_pdf":"https://arxiv.org/pdf/2511.05114v1","authors":"[\"Álvaro Guglielmin Becker\",\"Lana Bertoldo Rossato\",\"Anderson Rocha Tavares\"]","published":"2025-11-07T09:58:01Z","proceeding":"cs.LG","tasks":"[\"cs.LG\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}