Page 122 - AIH-1-2
P. 122

Artificial Intelligence in Health                                Medical instruction-tuning for Japanese LLMs



               Proceedings of the 2019 Conference on Empirical Methods   Processing: System Demonstrations; 2020. p. 38-45.
               in Natural Language Processing and the 9  International   34.  Gao L, Tow J, Biderman S, et al. A framework for few-shot
                                               th
               Joint Conference on Natural Language Processing (EMNLP-  language model evaluation. Zenodo. 2023;v0.0.1.
               IJCNLP); 2019. p. 2567–2577.
                                                                  doi: 10.5281/zenodo.5371629
               doi: 10.18653/v1/D19-1259
                                                               35.  Kurihara K, Kawahara D, Shibata T. JGLUE: Japanese General
            31.  Kasai J, Kasai Y, Sakaguchi K, Yamada Y, Radev D. Evaluating   Language Understanding Evaluation. In: Proceedings of the
               GPT-4 and ChatGPT on Japanese Medical Licensing    Thirteenth Language Resources and Evaluation Conference;
               Examinations. arXiv:2303.18027 [arXiv Preprint], 2023.  2022. p. 2957-2966.
               doi: 10.48550/arXiv.2303.18027                  36.  Pezeshkpour P, Hruschka E. Large Language Models
                                                                  Sensitivity to the Order of Options in Multiple-choice
            32.  Taori  R,  Gulrajani  I, Zhang  T,  et al.  Stanford Alpaca: An   Questions. arXiv:2308.11483 [arXiv Preprint], 2023.
               Instruction-following Llama  Model; 2023. Available from:
               https://github.com/tatsu-lab/stanford_alpaca [Last accessed      doi: 10.48550/arXiv.2308.11483
               on 2024 Apr 04].                                37.  Zheng  C,  Zhou  H,  Meng  F,  Zhou  J,  Huang M.  Large

            33.  Wolf T, Debut L, Sanh V, et al. Transformers: State-of-the-  Language Models are not Robust Multiple Choice Selectors.
               Art Natural Language Processing. In:  Proceedings of the   arXiv:2309.03882 [arXiv Preprint], 2023.
               2020 Conference on Empirical Methods in Natural Language      doi: 10.48550/arXiv.2309.03882























































            Volume 1 Issue 2 (2024)                        116                               doi: 10.36922/aih.2695
   117   118   119   120   121   122   123   124   125   126   127