@inproceedings{egerton-idehen-2026-sentinelqa,
title = "{S}entinel{QA}: Task-Level Routing and Output Verification for Multilingual Instruction Following",
author = "Egerton-Idehen, Asher",
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.127/",
pages = "1917--1924",
ISBN = "979-8-89176-474-3",
abstract = "This submission presents Team Sentinel{'}s approach to the WMT26 MIST shared task on multilingual instruction following. Built on Gemma-3-4B-IT, the system allocates its parameter budget across base and fine-tuned models, using a fixed task-level lookup to select between them. A verification layer checks output language, length constraints, repetition, and chat-template artefacts, with retries and repairs to improve output compliance."
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<abstract>This submission presents Team Sentinel’s approach to the WMT26 MIST shared task on multilingual instruction following. Built on Gemma-3-4B-IT, the system allocates its parameter budget across base and fine-tuned models, using a fixed task-level lookup to select between them. A verification layer checks output language, length constraints, repetition, and chat-template artefacts, with retries and repairs to improve output compliance.</abstract>
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%0 Conference Proceedings
%T SentinelQA: Task-Level Routing and Output Verification for Multilingual Instruction Following
%A Egerton-Idehen, Asher
%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 egerton-idehen-2026-sentinelqa
%X This submission presents Team Sentinel’s approach to the WMT26 MIST shared task on multilingual instruction following. Built on Gemma-3-4B-IT, the system allocates its parameter budget across base and fine-tuned models, using a fixed task-level lookup to select between them. A verification layer checks output language, length constraints, repetition, and chat-template artefacts, with retries and repairs to improve output compliance.
%U https://aclanthology.org/2026.wmt-main.127/
%P 1917-1924
Markdown (Informal)
[SentinelQA: Task-Level Routing and Output Verification for Multilingual Instruction Following](https://aclanthology.org/2026.wmt-main.127/) (Egerton-Idehen, WMT 2026)
ACL