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            <title>Proceedings of the Eleventh Conference on Machine Translation</title>
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    <abstract>We describe PTT-MULTITAN, our submission to the WMT26 MT Evaluation shared task, Task 3 (error-free segment detection). The task requires a binary decision — does a machine translation contain any error? — without ac- cess to reference translations, and is scored with the Matthews Correlation Coefficient (MCC). Our system combines a supervised classifier fitted on WMT25 human error-span annotations with three families of reference- free indicators: structural and phraseological cues, corpus-linguistic association measures computed over an LLM-as-judge model, and format/locale conformity checks. We have im- proved our system submissions, whose MCC rises from 0.159 to 0.168. We submitted six language pairs from the official WMT26 test set. The pairs were from English into Belaru- sian, German, Russian, Ukrainian, Simplified Chinese, and Traditional Chinese.</abstract>
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%0 Conference Proceedings
%T Beyond Rankings: Insights from ALTAE’s PTT-MULTITAN Submission to the WMT 2026 Shared Task on Automated Translation Quality Evaluation Systems
%A Zhu, Lichao
%A Zimina-Poirot, Maria
%A Froeliger, Nicolas
%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 zhu-etal-2026-beyond-rankings
%X We describe PTT-MULTITAN, our submission to the WMT26 MT Evaluation shared task, Task 3 (error-free segment detection). The task requires a binary decision — does a machine translation contain any error? — without ac- cess to reference translations, and is scored with the Matthews Correlation Coefficient (MCC). Our system combines a supervised classifier fitted on WMT25 human error-span annotations with three families of reference- free indicators: structural and phraseological cues, corpus-linguistic association measures computed over an LLM-as-judge model, and format/locale conformity checks. We have im- proved our system submissions, whose MCC rises from 0.159 to 0.168. We submitted six language pairs from the official WMT26 test set. The pairs were from English into Belaru- sian, German, Russian, Ukrainian, Simplified Chinese, and Traditional Chinese.
%U https://aclanthology.org/2026.wmt-main.111/
%P 1763-1771

Markdown (Informal)

[Beyond Rankings: Insights from ALTAE’s PTT-MULTITAN Submission to the WMT 2026 Shared Task on Automated Translation Quality Evaluation Systems](https://aclanthology.org/2026.wmt-main.111/) (Zhu et al., WMT 2026)

• Beyond Rankings: Insights from ALTAE’s PTT-MULTITAN Submission to the WMT 2026 Shared Task on Automated Translation Quality Evaluation Systems (Zhu et al., WMT 2026)

ACL

• Lichao Zhu, Maria Zimina-Poirot, and Nicolas Froeliger. 2026. Beyond Rankings: Insights from ALTAE’s PTT-MULTITAN Submission to the WMT 2026 Shared Task on Automated Translation Quality Evaluation Systems. In Proceedings of the Eleventh Conference on Machine Translation, pages 1763–1771, Budapest, Hungary. Association for Computational Linguistics.