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Llama 2: Open Foundation and Fine-Tuned Chat Models.  arXiv (Computation and Language), July 19, 2023, 2307.09288, ver. 2. DOI: 10.48550\/arXiv.2307.09288."},{"key":"ref40\/cit40","unstructured":"Gu, A.; Dao, T. Mamba: Linear-Time Sequence Modeling with Selective State Spaces.  arXiv (Machine Learning), May 31, 2024, 2312.00752, ver. 2. DOI: 10.48550\/arXiv.2312.00752."},{"key":"ref41\/cit41","first-page":"2323","volume":"80","author":"Jin W.","year":"2018","journal-title":"Proc. Int.l Conf. Machine Learning"},{"key":"ref42\/cit42","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-024-00861-w"},{"key":"ref43\/cit43","unstructured":"Menick, J.; Trebacz, M.; Mikulik, V.; Aslanides, J.; Song, F.; Chadwick, M.; Glaese, M.; Young, S.; Campbell-Gillingham, L.; Irving, G.  Teaching Language Models to Support Answers with Verified Quotes.  arXiv (Computation and Language), Mar. 21, 2022, 2203.11147. 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