no code implementations • WMT (EMNLP) 2021 • Markus Freitag, Ricardo Rei, Nitika Mathur, Chi-kiu Lo, Craig Stewart, George Foster, Alon Lavie, Ondřej Bojar
Contrary to previous years’ editions, this year we acquired our own human ratings based on expert-based human evaluation via Multidimensional Quality Metrics (MQM).
no code implementations • WMT (EMNLP) 2020 • Ricardo Rei, Craig Stewart, Ana C Farinha, Alon Lavie
We present the contribution of the Unbabel team to the WMT 2020 Shared Task on Metrics.
1 code implementation • WMT (EMNLP) 2021 • Ricardo Rei, Ana C Farinha, Chrysoula Zerva, Daan van Stigt, Craig Stewart, Pedro Ramos, Taisiya Glushkova, André F. T. Martins, Alon Lavie
In this paper, we present the joint contribution of Unbabel and IST to the WMT 2021 Metrics Shared Task.
no code implementations • WMT (EMNLP) 2021 • Chrysoula Zerva, Daan van Stigt, Ricardo Rei, Ana C Farinha, Pedro Ramos, José G. C. de Souza, Taisiya Glushkova, Miguel Vera, Fabio Kepler, André F. T. Martins
We present the joint contribution of IST and Unbabel to the WMT 2021 Shared Task on Quality Estimation.
1 code implementation • 2 May 2022 • Patrick Fernandes, António Farinhas, Ricardo Rei, José G. C. de Souza, Perez Ogayo, Graham Neubig, André F. T. Martins
Despite the progress in machine translation quality estimation and evaluation in the last years, decoding in neural machine translation (NMT) is mostly oblivious to this and centers around finding the most probable translation according to the model (MAP decoding), approximated with beam search.
1 code implementation • 13 Apr 2022 • Chrysoula Zerva, Taisiya Glushkova, Ricardo Rei, André F. T. Martins
Neural-based machine translation (MT) evaluation metrics are progressing fast.
1 code implementation • 9 Mar 2022 • Vânia Mendonça, Ricardo Rei, Luisa Coheur, Alberto Sardinha
Moreover, since we not know in advance which query strategy will be the most adequate for a certain language pair and set of Machine Translation models, we propose to dynamically combine multiple strategies using prediction with expert advice.
2 code implementations • Findings (EMNLP) 2021 • Taisiya Glushkova, Chrysoula Zerva, Ricardo Rei, André F. T. Martins
Several neural-based metrics have been recently proposed to evaluate machine translation quality.
no code implementations • ACL 2021 • Ricardo Rei, Ana C Farinha, Craig Stewart, Luisa Coheur, Alon Lavie
We present MT-Telescope, a visualization platform designed to facilitate comparative analysis of the output quality of two Machine Translation (MT) systems.
1 code implementation • ACL 2021 • Vânia Mendonça, Ricardo Rei, Luisa Coheur, Alberto Sardinha, Ana Lúcia Santos
In Machine Translation, assessing the quality of a large amount of automatic translations can be challenging.
1 code implementation • EACL 2021 • Bruno Jardim, Ricardo Rei, Mariana S. C. Almeida
The segmentation of emails into functional zones (also dubbed email zoning) is a relevant preprocessing step for most NLP tasks that deal with emails.
1 code implementation • 29 Oct 2020 • Ricardo Rei, Craig Stewart, Catarina Farinha, Alon Lavie
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.
1 code implementation • EMNLP 2020 • Ricardo Rei, Craig Stewart, Ana C Farinha, Alon Lavie
We present COMET, a neural framework for training multilingual machine translation evaluation models which obtains new state-of-the-art levels of correlation with human judgements.
1 code implementation • 27 Aug 2020 • Jose David Bermudez Castro, Ricardo Rei, Jose E. Ruiz, Pedro Achanccaray Diaz, Smith Arauco Canchumuni, Cristian Muñoz Villalobos, Felipe Borges Coelho, Leonardo Forero Mendoza, Marco Aurelio C. Pacheco
This work provides a fast detection system of COVID-19 characteristics in X-Ray images based on deep learning (DL) techniques.