@inproceedings{khasykov-2026-heybusan,
title = "{H}ey{B}usan at {WMT}26: A System for the Sorbian Track",
author = "Khasykov, Mikhail",
editor = "Haddow, Barry and
Kocmi, Tom and
Koehn, Philipp and
Monz, Christof",
booktitle = "Proceedings of the Eleventh Conference on Machine Translation",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.wmt-main.210/",
pages = "2662--2667",
ISBN = "979-8-89176-474-3",
abstract = "We describe our submission (team HeyBusan) to the Sorbian track of the WMT26 Multitask LLMs with Limited Resources shared task. A single Qwen3.5-2B model handles machine translation, question answering, spell checking, grammar checking, and mathematical reasoning in Upper Sorbian, Lower Sorbian, and German. We fine-tuned all model parameters on public data (the official task data plus external corpora) for approximately 55 GPU-hours on one 24 GB consumer GPU. Task-specific decoding then improved the results further without changing the model{'}s weights. Team HeyBusan placed first in machine translation, spell checking, and grammar checking, and tied with team LT3 for the overall track win."
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<abstract>We describe our submission (team HeyBusan) to the Sorbian track of the WMT26 Multitask LLMs with Limited Resources shared task. A single Qwen3.5-2B model handles machine translation, question answering, spell checking, grammar checking, and mathematical reasoning in Upper Sorbian, Lower Sorbian, and German. We fine-tuned all model parameters on public data (the official task data plus external corpora) for approximately 55 GPU-hours on one 24 GB consumer GPU. Task-specific decoding then improved the results further without changing the model’s weights. Team HeyBusan placed first in machine translation, spell checking, and grammar checking, and tied with team LT3 for the overall track win.</abstract>
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%0 Conference Proceedings
%T HeyBusan at WMT26: A System for the Sorbian Track
%A Khasykov, Mikhail
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Eleventh Conference on Machine Translation
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-474-3
%F khasykov-2026-heybusan
%X We describe our submission (team HeyBusan) to the Sorbian track of the WMT26 Multitask LLMs with Limited Resources shared task. A single Qwen3.5-2B model handles machine translation, question answering, spell checking, grammar checking, and mathematical reasoning in Upper Sorbian, Lower Sorbian, and German. We fine-tuned all model parameters on public data (the official task data plus external corpora) for approximately 55 GPU-hours on one 24 GB consumer GPU. Task-specific decoding then improved the results further without changing the model’s weights. Team HeyBusan placed first in machine translation, spell checking, and grammar checking, and tied with team LT3 for the overall track win.
%U https://aclanthology.org/2026.wmt-main.210/
%P 2662-2667
Markdown (Informal)
[HeyBusan at WMT26: A System for the Sorbian Track](https://aclanthology.org/2026.wmt-main.210/) (Khasykov, WMT 2026)
ACL