Rakuten’s Participation in WMT 2024 Patent Translation Task

Ohnmar Htun, Alberto Poncelas


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:
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2024.wmt-1.52.pdf