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Sequence to sequence learning with neural networks [Internet]. [cited 2025 Jan 1]. Available from: http:\/\/arxiv.org\/abs\/1409.3215."},{"key":"ref22","first-page":"5999","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref23","first-page":"9","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"Radford","year":"2019","journal-title":"OpenAI Blog"},{"key":"ref24","unstructured":"Devlin J, Chang MW, Lee K, Toutanova K. BERT: pre-training of deep bidirectional transformers for language understanding [Online]. [cited 2025 Jan 1]. Available from: http:\/\/arxiv.org\/abs\/1810.04805."},{"key":"ref25","first-page":"1","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer [Internet]","volume":"21","author":"Raffel","year":"2019","journal-title":"J Mach Learn Res"},{"key":"ref26","series-title":"Proceedings of the 3rd Workshop on Noisy User-generated Text","article-title":"Crowdsourcing multiple choice science questions","author":"Welbl","year":"2017 Sep 7"},{"key":"ref27","series-title":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","article-title":"Glove: global vectors for word representation","author":"Pennington","year":"2014 Oct 25\u201329"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"100158","DOI":"10.1016\/j.caeai.2023.100158","article-title":"English grammar multiple-choice question generation using text-to-text transfer transformer","volume":"5","author":"Chomphooyod","year":"2023","journal-title":"Comput Educ Artif Intell"},{"key":"ref29","unstructured":"Sanh V, Debut L, Chaumond J, Wolf T. DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. arXiv:1910.01108. 2019."},{"key":"ref30","unstructured":"Clark P, Cowhey I, Etzioni O, Khot T, Sabharwal A, Schoenick C, et al. Think you have solved question answering? Try ARC, the AI2 reasoning challenge. arXiv:1803.05457. 2018."},{"key":"ref31","series-title":"NAACL HLT 2019\u20142019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","article-title":"CommonSenseqa: a question answering challenge targeting com-monsense knowledge","author":"Talmor","year":"2019 Jun 2\u20137"},{"key":"ref32","series-title":"Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing","article-title":"MCTest: a challenge dataset for the open-domain machine comprehension of text","author":"Richardson","year":"2013 Oct 18\u201321"},{"key":"ref33","series-title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","article-title":"Can a suit of armor conduct electricity? 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Multiple-choice question generation: towards an automated assessment framework. arXiv:2209.11830. 2022."},{"key":"ref38","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.aiopen.2022.10.001","article-title":"A survey of transformers","volume":"3","author":"Lin","year":"2022","journal-title":"AI Open"},{"key":"ref39","author":"Mangrulkar","year":"2022","journal-title":"PEFT: state-of-the-art parameter-efficient fine-tuning methods"},{"key":"ref40","unstructured":"Wolf T, Debut L, Sanh V, Chaumond J, Delangue C, Moi A, et al. Transformers: state-of-the-art natural language processing [Internet]. [cited 2025 Jan 1]. 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