@InProceedings{temesgen-kurtyigit-fraser:2026:wmt,
  author    = {Temesgen, Tsedeniya Kinfe  and  Kurtyigit, Sinan  and  Fraser, Alexander},
  title     = {TUMHN@WMT2026: LLMs with Limited Resources for Slavic Languages},
  booktitle      = {Proceedings of the Eleventh Conference on Machine Translation},
  month          = {October},
  year           = {2026},
  address        = {Budapest, Hungary},
  publisher      = {Association for Computational Linguistics},
  pages     = {2681--2687},
  abstract  = {We describe the TUMHN team's systems for the WMT26 Shared Tasks on LLMs with Lim- ited Resources for Slavic Languages. We partic- ipated in the Ukrainian track, covering machine translation, question answering, spell checking, grammar checking, and math reasoning tasks. We restructured our training dataset into a chat-style format and fine-tuned the Qwen3.5-2B model for the Ukrainian track in a multitask learn- ing setting. Our model outperforms the base- line on three of the five tasks, with significant improvements on Question Answering, Spell Checking, and Grammar Checking. In Machine Translation, the model shows a slight improve- ment for the English–Ukrainian direction. For Spell Checking and Grammar Checking specif- ically, the largest gains were observed in spell or grammatical error detection as opposed to correction. In Math Reasoning, however, our model does not outperform the baseline. The fine-tuned model 1 and training dataset 2 are publicly available on Hugging Face.},
  url       = {https://aclanthology.org/2026.wmt-1.211}
}