LoResMT 2026 Shared Task System Description

Vladimir Panov

LoResMT 2026 Shared Task System Description

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Abstract

We describe our submission to the shared task LoResMT 2026, which involved translating from low-resource Turkic languages Bashkir, Chuvash, Kazakh, Kyrgyz, and Tatar from English or Russian. We submitted runs for the English-Chuvash language pair using Neural machine translation (NMT). Our approach focused on systematic experimentation with diverse model architectures and an emphasis on optimizing inference-time parameters. The key findings indicate that a large-scale, specialized multilingual translation model, combined with targeted data preprocessing and careful generation tuning, yielded the best performance, achieving a chrF++ score of 29.67 on the public test set.

Anthology ID:: 2026.loresmt-1.23
Volume:: Proceedings for the Ninth Workshop on Technologies for Machine Translation of Low Resource Languages (LoResMT 2026)
Month:: March
Year:: 2026
Address:: Rabat, Morocco
Editors:: Atul Kr. Ojha, Chao-hong Liu, Ekaterina Vylomova, Flammie Pirinen, Jonathan Washington, Nathaniel Oco, Xiaobing Zhao
Venues:: LoResMT | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 231–234
Language:
URL:: https://aclanthology.org/2026.loresmt-1.23/
DOI:
Bibkey:
Cite (ACL):: Vladimir Panov. 2026. LoResMT 2026 Shared Task System Description. In Proceedings for the Ninth Workshop on Technologies for Machine Translation of Low Resource Languages (LoResMT 2026), pages 231–234, Rabat, Morocco. Association for Computational Linguistics.
Cite (Informal):: LoResMT 2026 Shared Task System Description (Panov, LoResMT 2026)
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PDF:: https://aclanthology.org/2026.loresmt-1.23.pdf

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@inproceedings{panov-2026-loresmt,
    title = "{L}o{R}es{MT} 2026 Shared Task System Description",
    author = "Panov, Vladimir",
    editor = "Ojha, Atul Kr.  and
      Liu, Chao-hong  and
      Vylomova, Ekaterina  and
      Pirinen, Flammie  and
      Washington, Jonathan  and
      Oco, Nathaniel  and
      Zhao, Xiaobing",
    booktitle = "Proceedings for the Ninth Workshop on Technologies for Machine Translation of Low Resource Languages ({L}o{R}es{MT} 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.loresmt-1.23/",
    pages = "231--234",
    ISBN = "979-8-89176-366-1",
    abstract = "We describe our submission to the shared task LoResMT 2026, which involved translating from low-resource Turkic languages Bashkir, Chuvash, Kazakh, Kyrgyz, and Tatar from English or Russian. We submitted runs for the English-Chuvash language pair using Neural machine translation (NMT). Our approach focused on systematic experimentation with diverse model architectures and an emphasis on optimizing inference-time parameters. The key findings indicate that a large-scale, specialized multilingual translation model, combined with targeted data preprocessing and careful generation tuning, yielded the best performance, achieving a chrF++ score of 29.67 on the public test set."
}

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        <name type="personal">
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    <abstract>We describe our submission to the shared task LoResMT 2026, which involved translating from low-resource Turkic languages Bashkir, Chuvash, Kazakh, Kyrgyz, and Tatar from English or Russian. We submitted runs for the English-Chuvash language pair using Neural machine translation (NMT). Our approach focused on systematic experimentation with diverse model architectures and an emphasis on optimizing inference-time parameters. The key findings indicate that a large-scale, specialized multilingual translation model, combined with targeted data preprocessing and careful generation tuning, yielded the best performance, achieving a chrF++ score of 29.67 on the public test set.</abstract>
    <identifier type="citekey">panov-2026-loresmt</identifier>
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            <start>231</start>
            <end>234</end>
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%0 Conference Proceedings
%T LoResMT 2026 Shared Task System Description
%A Panov, Vladimir
%Y Ojha, Atul Kr.
%Y Liu, Chao-hong
%Y Vylomova, Ekaterina
%Y Pirinen, Flammie
%Y Washington, Jonathan
%Y Oco, Nathaniel
%Y Zhao, Xiaobing
%S Proceedings for the Ninth Workshop on Technologies for Machine Translation of Low Resource Languages (LoResMT 2026)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Morocco
%@ 979-8-89176-366-1
%F panov-2026-loresmt
%X We describe our submission to the shared task LoResMT 2026, which involved translating from low-resource Turkic languages Bashkir, Chuvash, Kazakh, Kyrgyz, and Tatar from English or Russian. We submitted runs for the English-Chuvash language pair using Neural machine translation (NMT). Our approach focused on systematic experimentation with diverse model architectures and an emphasis on optimizing inference-time parameters. The key findings indicate that a large-scale, specialized multilingual translation model, combined with targeted data preprocessing and careful generation tuning, yielded the best performance, achieving a chrF++ score of 29.67 on the public test set.
%U https://aclanthology.org/2026.loresmt-1.23/
%P 231-234

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Markdown (Informal)

[LoResMT 2026 Shared Task System Description](https://aclanthology.org/2026.loresmt-1.23/) (Panov, LoResMT 2026)

LoResMT 2026 Shared Task System Description (Panov, LoResMT 2026)

ACL

Vladimir Panov. 2026. LoResMT 2026 Shared Task System Description. In Proceedings for the Ninth Workshop on Technologies for Machine Translation of Low Resource Languages (LoResMT 2026), pages 231–234, Rabat, Morocco. Association for Computational Linguistics.