How multilingual are multilingual LLMs? A case study in Northern Sámi-Finnish Translation

Jonne Sälevä; Constantine Lignos

How multilingual are multilingual LLMs? A case study in Northern Sámi-Finnish Translation

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Abstract

We use Finnish and Northern Sámi as a case study to investigate how suitable multilingual LLMs are for low-resource machine translation and how much performance can be improved using supervised finetuning with varying amounts of parallel data. Our experiments on zero-shot translation reveal that mainstream multilingual LLMs from a variety of model families are unsuitable for translation between our chosen languages as-is, regardless of the generation hyperparameters. On the other hand, our experiments on supervised finetuning reveal that even relatively small amounts of parallel data can be very useful for improving performance in both translation directions.

Anthology ID:: 2026.loreslm-1.42
Volume:: Proceedings of the Second Workshop on Language Models for Low-Resource Languages (LoResLM 2026)
Month:: March
Year:: 2026
Address:: Rabat, Morocco
Editors:: Hansi Hettiarachchi, Tharindu Ranasinghe, Alistair Plum, Paul Rayson, Ruslan Mitkov, Mohamed Gaber, Damith Premasiri, Fiona Anting Tan, Lasitha Uyangodage
Venue:: LoResLM
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 484–492
Language:
URL:: https://aclanthology.org/2026.loreslm-1.42/
DOI:
Bibkey:
Cite (ACL):: Jonne Sälevä and Constantine Lignos. 2026. How multilingual are multilingual LLMs? A case study in Northern Sámi-Finnish Translation. In Proceedings of the Second Workshop on Language Models for Low-Resource Languages (LoResLM 2026), pages 484–492, Rabat, Morocco. Association for Computational Linguistics.
Cite (Informal):: How multilingual are multilingual LLMs? A case study in Northern Sámi-Finnish Translation (Sälevä & Lignos, LoResLM 2026)
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PDF:: https://aclanthology.org/2026.loreslm-1.42.pdf

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@inproceedings{saleva-lignos-2026-multilingual,
    title = "How multilingual are multilingual {LLM}s? A case study in {N}orthern {S}{\'a}mi-{F}innish Translation",
    author = {S{\"a}lev{\"a}, Jonne  and
      Lignos, Constantine},
    editor = "Hettiarachchi, Hansi  and
      Ranasinghe, Tharindu  and
      Plum, Alistair  and
      Rayson, Paul  and
      Mitkov, Ruslan  and
      Gaber, Mohamed  and
      Premasiri, Damith  and
      Tan, Fiona Anting  and
      Uyangodage, Lasitha",
    booktitle = "Proceedings of the Second Workshop on Language Models for Low-Resource Languages ({L}o{R}es{LM} 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.loreslm-1.42/",
    pages = "484--492",
    ISBN = "979-8-89176-377-7",
    abstract = "We use Finnish and Northern S{\'a}mi as a case study to investigate how suitable multilingual LLMs are for low-resource machine translation and how much performance can be improved using supervised finetuning with varying amounts of parallel data. Our experiments on zero-shot translation reveal that mainstream multilingual LLMs from a variety of model families are unsuitable for translation between our chosen languages as-is, regardless of the generation hyperparameters. On the other hand, our experiments on supervised finetuning reveal that even relatively small amounts of parallel data can be very useful for improving performance in both translation directions."
}

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%0 Conference Proceedings
%T How multilingual are multilingual LLMs? A case study in Northern Sámi-Finnish Translation
%A Sälevä, Jonne
%A Lignos, Constantine
%Y Hettiarachchi, Hansi
%Y Ranasinghe, Tharindu
%Y Plum, Alistair
%Y Rayson, Paul
%Y Mitkov, Ruslan
%Y Gaber, Mohamed
%Y Premasiri, Damith
%Y Tan, Fiona Anting
%Y Uyangodage, Lasitha
%S Proceedings of the Second Workshop on Language Models for Low-Resource Languages (LoResLM 2026)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Morocco
%@ 979-8-89176-377-7
%F saleva-lignos-2026-multilingual
%X We use Finnish and Northern Sámi as a case study to investigate how suitable multilingual LLMs are for low-resource machine translation and how much performance can be improved using supervised finetuning with varying amounts of parallel data. Our experiments on zero-shot translation reveal that mainstream multilingual LLMs from a variety of model families are unsuitable for translation between our chosen languages as-is, regardless of the generation hyperparameters. On the other hand, our experiments on supervised finetuning reveal that even relatively small amounts of parallel data can be very useful for improving performance in both translation directions.
%U https://aclanthology.org/2026.loreslm-1.42/
%P 484-492

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Markdown (Informal)

[How multilingual are multilingual LLMs? A case study in Northern Sámi-Finnish Translation](https://aclanthology.org/2026.loreslm-1.42/) (Sälevä & Lignos, LoResLM 2026)

How multilingual are multilingual LLMs? A case study in Northern Sámi-Finnish Translation (Sälevä & Lignos, LoResLM 2026)

ACL

Jonne Sälevä and Constantine Lignos. 2026. How multilingual are multilingual LLMs? A case study in Northern Sámi-Finnish Translation. In Proceedings of the Second Workshop on Language Models for Low-Resource Languages (LoResLM 2026), pages 484–492, Rabat, Morocco. Association for Computational Linguistics.