Omri Asscher, Machine Translation and Translation Theory, Abingdon, Oxon; New York, NY: Routledge, 2025, 178 pp., ISBN 9781041000662

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DOI:

https://doi.org/10.60923/issn.2785-3233/25813

Riferimenti bibliografici

Chang, Yupeng, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, Xing Xie. 2024. “A survey on evaluation of large language models.” ACM Transactions on Intelligent Systems and Technology, 15(3), 1–45.

Hendy, Amr, Mohamed Abdelrehim, Amr Sharaf, Vikas Raunak, Mohamed Gabr, Hitokazu Matsushita, Young Jin Kim, Mohamed Afify, & Hany Hassan Awadalla. 2023. “How good are GPT models at machine translation? A comprehensive evaluation.” arXiv preprint, 2302.09210.

Lyu, Chenyang, Zefeng Du, Jitao Xu, Yitao Duan, Minghao Wu, Teresa Lynn, Alham Fikri Aji, Derek F. Wong, Siyou Liu, Longyue Wang. 2023. “A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models.” arXiv preprint, 2305.01181.

Moniz, Helena & Carla Parra Escartín. (eds.). 2023. Towards Responsible Machine Translation: Ethical and Legal Considerations in Machine Translation. Cham: Springer.

Moorkens, Joss. 2022. “Ethics and machine translation.” In Dorothy Kenny (ed.), Machine translation for everyone: Empowering users in the age of artificial intelligence (Translation and Multilingual Natural Language Processing 18), 121–140. Berlin: Language Science Press.

Moorkens, Joss, Andy Way, & Séamus Lankford. 2025. Automating Translation. London: Routledge.

Müller, Mathias, Annette Rios, & Rico Sennrich. 2020. “Domain Robustness in Neural Machine Translation.” In Denkowski, Michael & Christian Federman (eds.), Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), 151–164.

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Pubblicato

2026-07-09

Come citare

Gramellini, R. (2025). Omri Asscher, Machine Translation and Translation Theory, Abingdon, Oxon; New York, NY: Routledge, 2025, 178 pp., ISBN 9781041000662. DIVE-IN – An International Journal on Diversity and Inclusion, 5(2), 225–228. https://doi.org/10.60923/issn.2785-3233/25813