@inproceedings{lavie-etal-2025-findings,
title = "Findings of the {WMT}25 Shared Task on Automated Translation Evaluation Systems: Linguistic Diversity is Challenging and References Still Help",
author = "Lavie, Alon and
Hanneman, Greg and
Agrawal, Sweta and
Kanojia, Diptesh and
Lo, Chi-Kiu and
Zouhar, Vil{\'e}m and
Blain, Frederic and
Zerva, Chrysoula and
Avramidis, Eleftherios and
Deoghare, Sourabh and
Sindhujan, Archchana and
Wang, Jiayi and
Adelani, David Ifeoluwa and
Thompson, Brian and
Kocmi, Tom and
Freitag, Markus and
Deutsch, Daniel",
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-1.24/",
doi = "10.18653/v1/2025.wmt-1.24",
pages = "436--483",
ISBN = "979-8-89176-341-8",
abstract = "The WMT25 Shared Task on Automated Translation Evaluation Systems evaluates metrics and quality estimation systems that assess the quality of language translation systems. This task unifies and consolidates the separate WMT shared tasks on Machine Translation Evaluation Metrics and Quality Estimation from previous years. Our primary goal is to encourage the development and assessment of new state-of-the-art translation quality evaluation systems. The shared task this year consisted of three subtasks: (1) segment-level quality score prediction, (2) span-level translation error annotation, and (3) quality-informed segment-level error correction. The evaluation data for the shared task were provided by the General MT shared task and were complemented by ``challenge sets'' from both the organizers and participants. Task 1 results indicate the strong performance of large LLMs at the system level, whilereference-based baseline metrics outperform LLMs at the segment level. Task 2 results indicate that accurate error detection and balancing precision and recall are persistent challenges. Task 3 results show that minimal editing is challenging even when informed by quality indicators. Robustness across the broad diversity of languages remains a major challenge across all three subtasks."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="lavie-etal-2025-findings">
<titleInfo>
<title>Findings of the WMT25 Shared Task on Automated Translation Evaluation Systems: Linguistic Diversity is Challenging and References Still Help</title>
</titleInfo>
<name type="personal">
<namePart type="given">Alon</namePart>
<namePart type="family">Lavie</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Greg</namePart>
<namePart type="family">Hanneman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sweta</namePart>
<namePart type="family">Agrawal</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Diptesh</namePart>
<namePart type="family">Kanojia</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Chi-Kiu</namePart>
<namePart type="family">Lo</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Vilém</namePart>
<namePart type="family">Zouhar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Frederic</namePart>
<namePart type="family">Blain</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Chrysoula</namePart>
<namePart type="family">Zerva</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Eleftherios</namePart>
<namePart type="family">Avramidis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sourabh</namePart>
<namePart type="family">Deoghare</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Archchana</namePart>
<namePart type="family">Sindhujan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jiayi</namePart>
<namePart type="family">Wang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">David</namePart>
<namePart type="given">Ifeoluwa</namePart>
<namePart type="family">Adelani</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Brian</namePart>
<namePart type="family">Thompson</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tom</namePart>
<namePart type="family">Kocmi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Markus</namePart>
<namePart type="family">Freitag</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Daniel</namePart>
<namePart type="family">Deutsch</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-11</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Tenth Conference on Machine Translation</title>
</titleInfo>
<name type="personal">
<namePart type="given">Barry</namePart>
<namePart type="family">Haddow</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tom</namePart>
<namePart type="family">Kocmi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Philipp</namePart>
<namePart type="family">Koehn</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Christof</namePart>
<namePart type="family">Monz</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Suzhou, China</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-341-8</identifier>
</relatedItem>
<abstract>The WMT25 Shared Task on Automated Translation Evaluation Systems evaluates metrics and quality estimation systems that assess the quality of language translation systems. This task unifies and consolidates the separate WMT shared tasks on Machine Translation Evaluation Metrics and Quality Estimation from previous years. Our primary goal is to encourage the development and assessment of new state-of-the-art translation quality evaluation systems. The shared task this year consisted of three subtasks: (1) segment-level quality score prediction, (2) span-level translation error annotation, and (3) quality-informed segment-level error correction. The evaluation data for the shared task were provided by the General MT shared task and were complemented by “challenge sets” from both the organizers and participants. Task 1 results indicate the strong performance of large LLMs at the system level, whilereference-based baseline metrics outperform LLMs at the segment level. Task 2 results indicate that accurate error detection and balancing precision and recall are persistent challenges. Task 3 results show that minimal editing is challenging even when informed by quality indicators. Robustness across the broad diversity of languages remains a major challenge across all three subtasks.</abstract>
<identifier type="citekey">lavie-etal-2025-findings</identifier>
<identifier type="doi">10.18653/v1/2025.wmt-1.24</identifier>
<location>
<url>https://aclanthology.org/2025.wmt-1.24/</url>
</location>
<part>
<date>2025-11</date>
<extent unit="page">
<start>436</start>
<end>483</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Findings of the WMT25 Shared Task on Automated Translation Evaluation Systems: Linguistic Diversity is Challenging and References Still Help
%A Lavie, Alon
%A Hanneman, Greg
%A Agrawal, Sweta
%A Kanojia, Diptesh
%A Lo, Chi-Kiu
%A Zouhar, Vilém
%A Blain, Frederic
%A Zerva, Chrysoula
%A Avramidis, Eleftherios
%A Deoghare, Sourabh
%A Sindhujan, Archchana
%A Wang, Jiayi
%A Adelani, David Ifeoluwa
%A Thompson, Brian
%A Kocmi, Tom
%A Freitag, Markus
%A Deutsch, Daniel
%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 lavie-etal-2025-findings
%X The WMT25 Shared Task on Automated Translation Evaluation Systems evaluates metrics and quality estimation systems that assess the quality of language translation systems. This task unifies and consolidates the separate WMT shared tasks on Machine Translation Evaluation Metrics and Quality Estimation from previous years. Our primary goal is to encourage the development and assessment of new state-of-the-art translation quality evaluation systems. The shared task this year consisted of three subtasks: (1) segment-level quality score prediction, (2) span-level translation error annotation, and (3) quality-informed segment-level error correction. The evaluation data for the shared task were provided by the General MT shared task and were complemented by “challenge sets” from both the organizers and participants. Task 1 results indicate the strong performance of large LLMs at the system level, whilereference-based baseline metrics outperform LLMs at the segment level. Task 2 results indicate that accurate error detection and balancing precision and recall are persistent challenges. Task 3 results show that minimal editing is challenging even when informed by quality indicators. Robustness across the broad diversity of languages remains a major challenge across all three subtasks.
%R 10.18653/v1/2025.wmt-1.24
%U https://aclanthology.org/2025.wmt-1.24/
%U https://doi.org/10.18653/v1/2025.wmt-1.24
%P 436-483
Markdown (Informal)
[Findings of the WMT25 Shared Task on Automated Translation Evaluation Systems: Linguistic Diversity is Challenging and References Still Help](https://aclanthology.org/2025.wmt-1.24/) (Lavie et al., WMT 2025)
ACL
- Alon Lavie, Greg Hanneman, Sweta Agrawal, Diptesh Kanojia, Chi-Kiu Lo, Vilém Zouhar, Frederic Blain, Chrysoula Zerva, Eleftherios Avramidis, Sourabh Deoghare, Archchana Sindhujan, Jiayi Wang, David Ifeoluwa Adelani, Brian Thompson, Tom Kocmi, Markus Freitag, and Daniel Deutsch. 2025. Findings of the WMT25 Shared Task on Automated Translation Evaluation Systems: Linguistic Diversity is Challenging and References Still Help. In Proceedings of the Tenth Conference on Machine Translation, pages 436–483, Suzhou, China. Association for Computational Linguistics.