Abstract
This paper introduces our machine transla- tion system (team sakura), developed for the 2024 WMT Patent Translation Task. Our sys- tem focuses on translations between Japanese- English, Japanese-Korean, and Japanese- Chinese. As large language models have shown good results for various natural language pro- cessing tasks, we have adopted the RakutenAI- 7B-chat model, which has demonstrated effec- tiveness in English and Japanese. We fine-tune this model with patent-domain parallel texts and translate using multiple prompts.- Anthology ID:
- 2024.wmt-1.52
- Volume:
- Proceedings of the Ninth Conference on Machine Translation
- Month:
- November
- Year:
- 2024
- Address:
- Miami, Florida, USA
- Editors:
- Barry Haddow, Tom Kocmi, Philipp Koehn, Christof Monz
- Venue:
- WMT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 643–646
- Language:
- URL:
- https://aclanthology.org/2024.wmt-1.52
- DOI:
- 10.18653/v1/2024.wmt-1.52
- Cite (ACL):
- Ohnmar Htun and Alberto Poncelas. 2024. Rakuten’s Participation in WMT 2024 Patent Translation Task. In Proceedings of the Ninth Conference on Machine Translation, pages 643–646, Miami, Florida, USA. Association for Computational Linguistics.
- Cite (Informal):
- Rakuten’s Participation in WMT 2024 Patent Translation Task (Htun & Poncelas, WMT 2024)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2024.wmt-1.52.pdf