[14] Melvin Johnson, Mike Schuster, Quoc V Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda Viégas, Martin Wattenberg, Greg Corrado, et al. Google's multilingual neural machine translation system: Enabling zero-shot translation. Transactions of the Association for Computational Linguistics, 5:339-351, 2017.
[15] Yunsu Kim, Yingbo Gao, and Hermann Ney. Effective cross-lingual transfer of neural machine translation models without shared vocabularies. arXiv preprint arXiv:1905.05475, 2019.
[16] Diederik P Kingma and Jimmy Ba. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980, 2014.
[17] Tom Kocmi and Ondrej Bojar. Trivial transfer learning for low-resource neural machine translation. arXiv preprint arXiv:1809.00357, 2018.
[18] Julia Kreutzer, David Vilar, and Artem Sokolov. Bandits don't follow rules: Balancing multi-facet machine translation with multi-armed bandits. arXiv preprint arXiv:2110.06997, 2021.
[19] Taku Kudo and John Richardson. Sentencepiece: A simple and language independent subword tokenizer and tokenizer for neural text processing. arXiv preprint arXiv:1808.06226, 2018.
[20] Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, and M Pawan Kumar. In defense of the unitary scalarization for deep multi-task learning. arXiv preprint arXiv:2201.04122, 2022.
[21] Surafel M Lakew, Alija Erofeeva, Matteo Negri, Marcello Federico, and Marco Turchi. Transfer learning in multilingual neural machine translation with dynamic vocabulary. arXiv preprint arXiv:1811.01137, 2018.
[22] Jason Phang, Iacer Calixto, Phu Mon Htut, Yada Pruksachatkun, Haokun Liu, Clara Vania, Katharina Kann, and Samuel Bowman. English intermediate-task training improves zero-shot cross-lingual transfer too. In Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, pages 557–575, 2020.
[23] Jason Phang, Thibault Févry, and Samuel R Bowman. Sentence encoders on stilts: Supplementary training on intermediate labeled-data tasks. arXiv preprint arXiv:1811.01088, 2018.
[24] Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J Liu, et al. Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res., 21(140):1-67, 2020.
[25] Adam Roberts, Hyung Won Chung, Anselm Levskaya, Gaurav Mishra, James Bradbury, Daniel Andor, Sharan Narang, Brian Lester, Colin Gaffney, Afroz Mohiuddin, Curtis Hawthorne, Aitor Lewkowycz, Alex Salcianu, Marc van Zee, Jacob Austin, Sebastian Goodman, Livio Baldini Soares, Haitang Hu, Sasha Tsvyashchenko, Aakanksha Chowdhery, Jasmijn Bastings, Jannis Bulian, Xavier Garcia, Jianmo Ni, Andrew Chen, Kathleen Kenealy, Jonathan H. Clark, Stephan Lee, Dan Garrette, James Lee-Thorp, Colin Raffel, Noam Shazeer, Marvin Ritter, Maarten Bosma, Alexandre Passos, Jeremy Maitin-Shepard, Noah Fiedel, Mark Omernick, Brennan Saeta, Ryan Sepassi, Alexander Spiridonov, Joshua Newlan, and Andrea Gesmundo. Scaling up models and data with t5x and seqio. arXiv preprint arXiv:2203.17189, 2022.
[26] Chenze Shao and Yang Feng. Overcoming catastrophic forgetting beyond continual learning: Balanced training for neural machine translation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2023-2036, 2022.
[27] Noam Shazeer and Mitchell Stern. Adafactor: Adaptive learning rates with sublinear memory cost. In International Conference on Machine Learning, pages 4596-4604. PMLR, 2018.
[28] Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. Attention is all you need. In I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 30. Curran Associates, Inc., 2017.