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        <title>Unbabel’s Participation in the WMT20 Metrics Shared Task</title>
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    <name type="personal">
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    <abstract>We present the contribution of the Unbabel team to the WMT 2020 Shared Task on Metrics. We intend to participate on the segmentlevel, document-level and system-level tracks on all language pairs, as well as the “QE as a Metric” track. Accordingly, we illustrate results of our models in these tracks with reference to test sets from the previous year. Our submissions build upon the recently proposed COMET framework: we train several estimator models to regress on different humangenerated quality scores and a novel ranking model trained on relative ranks obtained from Direct Assessments. We also propose a simple technique for converting segment-level predictions into a document-level score. Overall, our systems achieve strong results for all language pairs on previous test sets and in many cases set a new state-of-the-art.</abstract>
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%0 Conference Proceedings
%T Unbabel’s Participation in the WMT20 Metrics Shared Task
%A Rei, Ricardo
%A Stewart, Craig
%A Farinha, Ana C.
%A Lavie, Alon
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F rei-etal-2020-unbabels
%X We present the contribution of the Unbabel team to the WMT 2020 Shared Task on Metrics. We intend to participate on the segmentlevel, document-level and system-level tracks on all language pairs, as well as the “QE as a Metric” track. Accordingly, we illustrate results of our models in these tracks with reference to test sets from the previous year. Our submissions build upon the recently proposed COMET framework: we train several estimator models to regress on different humangenerated quality scores and a novel ranking model trained on relative ranks obtained from Direct Assessments. We also propose a simple technique for converting segment-level predictions into a document-level score. Overall, our systems achieve strong results for all language pairs on previous test sets and in many cases set a new state-of-the-art.
%U https://aclanthology.org/2020.wmt-1.101
%P 911-920

Markdown (Informal)

[Unbabel’s Participation in the WMT20 Metrics Shared Task](https://aclanthology.org/2020.wmt-1.101) (Rei et al., WMT 2020)

• Unbabel’s Participation in the WMT20 Metrics Shared Task (Rei et al., WMT 2020)

ACL

• Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020. Unbabel’s Participation in the WMT20 Metrics Shared Task. In Proceedings of the Fifth Conference on Machine Translation, pages 911–920, Online. Association for Computational Linguistics.