@inproceedings{zerva-etal-2021-ist,
title = "{IST}-Unbabel 2021 Submission for the Quality Estimation Shared Task",
author = "Zerva, Chrysoula and
van Stigt, Daan and
Rei, Ricardo and
Farinha, Ana C and
Ramos, Pedro and
C. de Souza, Jos{\'e} G. and
Glushkova, Taisiya and
Vera, Miguel and
Kepler, Fabio and
Martins, Andr{\'e} F. T.",
booktitle = "Proceedings of the Sixth Conference on Machine Translation",
month = nov,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wmt-1.102",
pages = "961--972",
abstract = "We present the joint contribution of IST and Unbabel to the WMT 2021 Shared Task on Quality Estimation. Our team participated on two tasks: Direct Assessment and Post-Editing Effort, encompassing a total of 35 submissions. For all submissions, our efforts focused on training multilingual models on top of OpenKiwi predictor-estimator architecture, using pre-trained multilingual encoders combined with adapters. We further experiment with and uncertainty-related objectives and features as well as training on out-of-domain direct assessment data.",
}
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<abstract>We present the joint contribution of IST and Unbabel to the WMT 2021 Shared Task on Quality Estimation. Our team participated on two tasks: Direct Assessment and Post-Editing Effort, encompassing a total of 35 submissions. For all submissions, our efforts focused on training multilingual models on top of OpenKiwi predictor-estimator architecture, using pre-trained multilingual encoders combined with adapters. We further experiment with and uncertainty-related objectives and features as well as training on out-of-domain direct assessment data.</abstract>
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%0 Conference Proceedings
%T IST-Unbabel 2021 Submission for the Quality Estimation Shared Task
%A Zerva, Chrysoula
%A van Stigt, Daan
%A Rei, Ricardo
%A Farinha, Ana C.
%A Ramos, Pedro
%A C. de Souza, José G.
%A Glushkova, Taisiya
%A Vera, Miguel
%A Kepler, Fabio
%A Martins, André F. T.
%S Proceedings of the Sixth Conference on Machine Translation
%D 2021
%8 November
%I Association for Computational Linguistics
%C Online
%F zerva-etal-2021-ist
%X We present the joint contribution of IST and Unbabel to the WMT 2021 Shared Task on Quality Estimation. Our team participated on two tasks: Direct Assessment and Post-Editing Effort, encompassing a total of 35 submissions. For all submissions, our efforts focused on training multilingual models on top of OpenKiwi predictor-estimator architecture, using pre-trained multilingual encoders combined with adapters. We further experiment with and uncertainty-related objectives and features as well as training on out-of-domain direct assessment data.
%U https://aclanthology.org/2021.wmt-1.102
%P 961-972
Markdown (Informal)
[IST-Unbabel 2021 Submission for the Quality Estimation Shared Task](https://aclanthology.org/2021.wmt-1.102) (Zerva et al., WMT 2021)
ACL
- Chrysoula Zerva, Daan van Stigt, Ricardo Rei, Ana C Farinha, Pedro Ramos, José G. C. de Souza, Taisiya Glushkova, Miguel Vera, Fabio Kepler, and André F. T. Martins. 2021. IST-Unbabel 2021 Submission for the Quality Estimation Shared Task. In Proceedings of the Sixth Conference on Machine Translation, pages 961–972, Online. Association for Computational Linguistics.