@inproceedings{martindale-carpuat-2025-improving,
title = "Improving {MT}-enabled Triage Performance with Multiple {MT} Outputs",
author = "Martindale, Marianna J. and
Carpuat, Marine",
editor = "Bouillon, Pierrette and
Gerlach, Johanna and
Girletti, Sabrina and
Volkart, Lise and
Rubino, Raphael and
Sennrich, Rico and
Farinha, Ana C. and
Gaido, Marco and
Daems, Joke and
Kenny, Dorothy and
Moniz, Helena and
Szoc, Sara",
booktitle = "Proceedings of Machine Translation Summit XX: Volume 1",
month = jun,
year = "2025",
address = "Geneva, Switzerland",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2025.mtsummit-1.45/",
pages = "592--607",
ISBN = "978-2-9701897-0-1",
abstract = "Recent advances in Machine Translation (MT) quality may motivate adoption in a variety of use cases, but the success of MT deployment depends not only on intrinsic model quality but on how well the model, as deployed, helps users meet the objectives of their use case. This work focuses on a specific triage use case, MT-enabled scanning in intelligence analysis. After describing the use case with its objectives and failure modes, we present a user study to establish a baseline performance level and measure the mitigating effects of a simple intervention, providing additional MT outputs. We find significant improvements in relevance judgment accuracy with outputs from two distinct neural MT models and significant improvements in relevant entity identification with the addition of a rule-based MT. Users also like seeing multiple MT outputs, making it an appealing way to improve MT-enabled scanning performance."
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%0 Conference Proceedings
%T Improving MT-enabled Triage Performance with Multiple MT Outputs
%A Martindale, Marianna J.
%A Carpuat, Marine
%Y Bouillon, Pierrette
%Y Gerlach, Johanna
%Y Girletti, Sabrina
%Y Volkart, Lise
%Y Rubino, Raphael
%Y Sennrich, Rico
%Y Farinha, Ana C.
%Y Gaido, Marco
%Y Daems, Joke
%Y Kenny, Dorothy
%Y Moniz, Helena
%Y Szoc, Sara
%S Proceedings of Machine Translation Summit XX: Volume 1
%D 2025
%8 June
%I European Association for Machine Translation
%C Geneva, Switzerland
%@ 978-2-9701897-0-1
%F martindale-carpuat-2025-improving
%X Recent advances in Machine Translation (MT) quality may motivate adoption in a variety of use cases, but the success of MT deployment depends not only on intrinsic model quality but on how well the model, as deployed, helps users meet the objectives of their use case. This work focuses on a specific triage use case, MT-enabled scanning in intelligence analysis. After describing the use case with its objectives and failure modes, we present a user study to establish a baseline performance level and measure the mitigating effects of a simple intervention, providing additional MT outputs. We find significant improvements in relevance judgment accuracy with outputs from two distinct neural MT models and significant improvements in relevant entity identification with the addition of a rule-based MT. Users also like seeing multiple MT outputs, making it an appealing way to improve MT-enabled scanning performance.
%U https://aclanthology.org/2025.mtsummit-1.45/
%P 592-607
Markdown (Informal)
[Improving MT-enabled Triage Performance with Multiple MT Outputs](https://aclanthology.org/2025.mtsummit-1.45/) (Martindale & Carpuat, MTSummit 2025)
ACL