@inproceedings{ingolfsdottir-etal-2025-midheind,
title = "Midheind at {WMT}25 General Machine Translation Task",
author = {Ing{\'o}lfsd{\'o}ttir, Svanhv{\'i}t Lilja and
J{\'o}nsson, Haukur and
Adhalsteinsson, K{\'a}ri Steinn and
Birkisson, R{\'o}bert Fj{\"o}lnir and
Th{\'o}rdharson, Sveinbj{\"o}rn and
Helgason, Thorvaldur P{\'a}ll},
editor = "Haddow, Barry and
Kocmi, Tom and
Koehn, Philipp and
Monz, Christof",
booktitle = "Proceedings of the Tenth Conference on Machine Translation",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.wmt-1.31/",
pages = "577--582",
ISBN = "979-8-89176-341-8",
abstract = "We present Midheind{'}s system contribution to two tasks at WMT25 {--} Tenth Conference on Machine Translation: The General Machine Translation Task and the WMT25 Terminology Shared Task. Erlendur is a multilingual LLM-based translation system that employs a multi-stage pipeline approach, with enhancements especially for translations from English to Icelandic. We address translation quality and grammatical accuracy challenges in current LLMs through a hybrid prompt-based approach that can benefit lower-resource language pairs. In a preparatory step, the LLM analyzes the source text and extracts key terms for lookup in an English-Icelandic dictionary. The findings of the analysis and the retrieved dictionary results are then incorporated into the translation prompt. When provided with a custom glossary, the system identifies relevant terms from the glossary and incorporates them into the translation, to ensure consistency in terminology. For longer inputs, the system maintains translation consistency by providing contextual information from preceding text chunks. Lastly, Icelandic target texts are passed through our custom-developed seq2seq language correction model (Ing{\'o}lfsd{\'o}ttir et al., 2023), where grammatical errors are corrected. Using this hybrid method, Erlendur delivers high-quality translations, without fine-tuning. Erlendur ranked 3rd-4th overall in the General Machine Translation Task for English-Icelandic translations, achieving the highest rank amongst all systems submitted by WMT25 participants (Kocmi et al., 2025a). Notably, in the WMT25 Terminology Shared Task, Erlendur placed 3rd in Track 1 and took first place in the more demanding Track 2 (Semenov et al., 2025)."
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<abstract>We present Midheind’s system contribution to two tasks at WMT25 – Tenth Conference on Machine Translation: The General Machine Translation Task and the WMT25 Terminology Shared Task. Erlendur is a multilingual LLM-based translation system that employs a multi-stage pipeline approach, with enhancements especially for translations from English to Icelandic. We address translation quality and grammatical accuracy challenges in current LLMs through a hybrid prompt-based approach that can benefit lower-resource language pairs. In a preparatory step, the LLM analyzes the source text and extracts key terms for lookup in an English-Icelandic dictionary. The findings of the analysis and the retrieved dictionary results are then incorporated into the translation prompt. When provided with a custom glossary, the system identifies relevant terms from the glossary and incorporates them into the translation, to ensure consistency in terminology. For longer inputs, the system maintains translation consistency by providing contextual information from preceding text chunks. Lastly, Icelandic target texts are passed through our custom-developed seq2seq language correction model (Ingólfsdóttir et al., 2023), where grammatical errors are corrected. Using this hybrid method, Erlendur delivers high-quality translations, without fine-tuning. Erlendur ranked 3rd-4th overall in the General Machine Translation Task for English-Icelandic translations, achieving the highest rank amongst all systems submitted by WMT25 participants (Kocmi et al., 2025a). Notably, in the WMT25 Terminology Shared Task, Erlendur placed 3rd in Track 1 and took first place in the more demanding Track 2 (Semenov et al., 2025).</abstract>
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%0 Conference Proceedings
%T Midheind at WMT25 General Machine Translation Task
%A Ingólfsdóttir, Svanhvít Lilja
%A Jónsson, Haukur
%A Adhalsteinsson, Kári Steinn
%A Birkisson, Róbert Fjölnir
%A Thórdharson, Sveinbjörn
%A Helgason, Thorvaldur Páll
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Tenth Conference on Machine Translation
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-341-8
%F ingolfsdottir-etal-2025-midheind
%X We present Midheind’s system contribution to two tasks at WMT25 – Tenth Conference on Machine Translation: The General Machine Translation Task and the WMT25 Terminology Shared Task. Erlendur is a multilingual LLM-based translation system that employs a multi-stage pipeline approach, with enhancements especially for translations from English to Icelandic. We address translation quality and grammatical accuracy challenges in current LLMs through a hybrid prompt-based approach that can benefit lower-resource language pairs. In a preparatory step, the LLM analyzes the source text and extracts key terms for lookup in an English-Icelandic dictionary. The findings of the analysis and the retrieved dictionary results are then incorporated into the translation prompt. When provided with a custom glossary, the system identifies relevant terms from the glossary and incorporates them into the translation, to ensure consistency in terminology. For longer inputs, the system maintains translation consistency by providing contextual information from preceding text chunks. Lastly, Icelandic target texts are passed through our custom-developed seq2seq language correction model (Ingólfsdóttir et al., 2023), where grammatical errors are corrected. Using this hybrid method, Erlendur delivers high-quality translations, without fine-tuning. Erlendur ranked 3rd-4th overall in the General Machine Translation Task for English-Icelandic translations, achieving the highest rank amongst all systems submitted by WMT25 participants (Kocmi et al., 2025a). Notably, in the WMT25 Terminology Shared Task, Erlendur placed 3rd in Track 1 and took first place in the more demanding Track 2 (Semenov et al., 2025).
%U https://aclanthology.org/2025.wmt-1.31/
%P 577-582
Markdown (Informal)
[Midheind at WMT25 General Machine Translation Task](https://aclanthology.org/2025.wmt-1.31/) (Ingólfsdóttir et al., WMT 2025)
ACL
- Svanhvít Lilja Ingólfsdóttir, Haukur Jónsson, Kári Steinn Adhalsteinsson, Róbert Fjölnir Birkisson, Sveinbjörn Thórdharson, and Thorvaldur Páll Helgason. 2025. Midheind at WMT25 General Machine Translation Task. In Proceedings of the Tenth Conference on Machine Translation, pages 577–582, Suzhou, China. Association for Computational Linguistics.