Web: http://arxiv.org/abs/2209.06243

Sept. 15, 2022, 1:14 a.m. | Ricardo Rei, Marcos Treviso, Nuno M. Guerreiro, Chrysoula Zerva, Ana C. Farinha, Christine Maroti, José G. C. de Souza, Taisiya Glushkova, Duarte

cs.CL updates on arXiv.org arxiv.org

We present the joint contribution of IST and Unbabel to the WMT 2022 Shared
Task on Quality Estimation (QE). Our team participated on all three subtasks:
(i) Sentence and Word-level Quality Prediction; (ii) Explainable QE; and (iii)
Critical Error Detection. For all tasks we build on top of the COMET framework,
connecting it with the predictor-estimator architecture of OpenKiwi, and
equipping it with a word-level sequence tagger and an explanation extractor.
Our results suggest that incorporating references during pretraining improves …

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