CUNI-MH and CUNI-EdUKate at the WMT26 General MT Shared Task

Miroslav Hrabal, Josef Jon, Ondřej Bojar


Abstract
We describe our constrained CUNI-MH-v3 (based on Qwen3-14B) and unconstrained CUNI-EdUKate (based on Granite 4.1 8B) submissions for the WMT26 General MT shared task. Both submissions use a three-stage training procedure: QLoRA supervised fine-tuning on synthetic sentence pairs, continued supervised fine-tuning on a smaller mixture of paragraph-level and instruction-oriented examples, and iterative preference optimization with automatically generated and scored preference pairs. We document the data construction, training setup, checkpoint selection, and evaluation. We also share the training data and model checkpoints for our constrained system.
Anthology ID:
2026.wmt-main.67
Volume:
Proceedings of the Eleventh Conference on Machine Translation
Month:
October
Year:
2026
Address:
Budapest, Hungary
Editors:
Barry Haddow, Tom Kocmi, Philipp Koehn, Christof Monz
Venues:
WMT | WS
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
1264–1270
Language:
URL:
https://aclanthology.org/2026.wmt-main.67/
DOI:
Bibkey:
Cite (ACL):
Miroslav Hrabal, Josef Jon, and Ondřej Bojar. 2026. CUNI-MH and CUNI-EdUKate at the WMT26 General MT Shared Task. In Proceedings of the Eleventh Conference on Machine Translation, pages 1264–1270, Budapest, Hungary. Association for Computational Linguistics.
Cite (Informal):
CUNI-MH and CUNI-EdUKate at the WMT26 General MT Shared Task (Hrabal et al., WMT 2026)
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PDF:
https://aclanthology.org/2026.wmt-main.67.pdf