Scaling up CometKiwi: Unbabel-IST 2023 Submission for the Quality Estimation Shared Task

Ricardo Rei, Nuno M. Guerreiro, José Pombal, Daan van Stigt, Marcos Treviso, Luisa Coheur, José G. C. de Souza, André Martins


Abstract
We present the joint contribution of Unbabel and Instituto Superior Técnico to the WMT 2023 Shared Task on Quality Estimation (QE). Our team participated on all tasks: Sentence- and Word-level Quality Prediction and Fine-grained error span detection. For all tasks we build on the CometKiwi model (rei et al. 2022). Our multilingual approaches are ranked first for all tasks, reaching state-of-the-art performance for quality estimation at word-, span- and sentence-level granularity. Compared to the previous state-of-the-art, CometKiwi, we show large improvements in correlation with human judgements (up to 10 Spearman points) and surpassing the second-best multilingual submission with up to 3.8 absolute points.
Anthology ID:
2023.wmt-1.73
Volume:
Proceedings of the Eighth Conference on Machine Translation
Month:
December
Year:
2023
Address:
Singapore
Editors:
Philipp Koehn, Barry Haddow, Tom Kocmi, Christof Monz
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
841–848
Language:
URL:
https://aclanthology.org/2023.wmt-1.73
DOI:
10.18653/v1/2023.wmt-1.73
Bibkey:
Cite (ACL):
Ricardo Rei, Nuno M. Guerreiro, José Pombal, Daan van Stigt, Marcos Treviso, Luisa Coheur, José G. C. de Souza, and André Martins. 2023. Scaling up CometKiwi: Unbabel-IST 2023 Submission for the Quality Estimation Shared Task. In Proceedings of the Eighth Conference on Machine Translation, pages 841–848, Singapore. Association for Computational Linguistics.
Cite (Informal):
Scaling up CometKiwi: Unbabel-IST 2023 Submission for the Quality Estimation Shared Task (Rei et al., WMT 2023)
Copy Citation:
PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2023.wmt-1.73.pdf