Findings of the WAT 2025 Shared Task on Japanese-English Article-level News Translation

Naoto Shirai, Kazutaka Kinugawa, Hitoshi Ito, Hideya Mino, Yoshihiko Kawai


Abstract
We present the preliminary findings of the WAT 2025 shared task on document-level translation from Japanese to English in the news domain. This task focuses on translating full articles with particular attention to whether translation models can learn to produce expressions and stylistic features typical of English news writing, with the aim to generate outputs that resemble original English news articles. The task consists of three translation styles: (1) literal translation, (2) news-style translation, based on English articles edited to match Japanese content, and (3) finalized translation, the primary goal of this shared task. Only one team participated and submitted a system to a single subtask. All tasks were evaluated automatically, and one task was also evaluated manually to compare the submission with the baseline.
Anthology ID:
2025.wat-1.8
Volume:
Proceedings of the Twelfth Workshop on Asian Translation (WAT 2025)
Month:
December
Year:
2025
Address:
Mumbai, India
Editors:
Toshiaki Nakazawa, Isao Goto
Venues:
WAT | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
93–97
Language:
URL:
https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.wat-1.8/
DOI:
Bibkey:
Cite (ACL):
Naoto Shirai, Kazutaka Kinugawa, Hitoshi Ito, Hideya Mino, and Yoshihiko Kawai. 2025. Findings of the WAT 2025 Shared Task on Japanese-English Article-level News Translation. In Proceedings of the Twelfth Workshop on Asian Translation (WAT 2025), pages 93–97, Mumbai, India. Association for Computational Linguistics.
Cite (Informal):
Findings of the WAT 2025 Shared Task on Japanese-English Article-level News Translation (Shirai et al., WAT 2025)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.wat-1.8.pdf