33 citations · 62 across the 6 of their papers we have counts for
6 papers
BLEU Meets COMET: Combining Lexical and Neural Metrics Towards Robust Machine Translation Evaluation
Taisiya Glushkova, Chrysoula Zerva, André F. T. Martins
Although neural-based machine translation evaluation metrics, such as COMET or BLEURT, have achieved strong correlations with human judgements, they are sometimes unreliable in det…
CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task
Ricardo Rei, Marcos Treviso, Nuno M. Guerreiro +9
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-leve…
Disentangling Uncertainty in Machine Translation Evaluation
Chrysoula Zerva, Taisiya Glushkova, Ricardo Rei +1
Trainable evaluation metrics for machine translation (MT) exhibit strong correlation with human judgements, but they are often hard to interpret and might produce unreliable scores…
Uncertainty-Aware Machine Translation Evaluation
Taisiya Glushkova, Chrysoula Zerva, Ricardo Rei +1
Several neural-based metrics have been recently proposed to evaluate machine translation quality. However, all of them resort to point estimates, which provide limited information…
DaNetQA: a yes/no Question Answering Dataset for the Russian Language
Taisia Glushkova, Alexey Machnev, Alena Fenogenova +3
DaNetQA, a new question-answering corpus, follows (Clark et. al, 2019) design: it comprises natural yes/no questions. Each question is paired with a paragraph from Wikipedia and an…
Char-RNN and Active Learning for Hashtag Segmentation
Taisiya Glushkova, Ekaterina Artemova
We explore the abilities of character recurrent neural network (char-RNN) for hashtag segmentation. Our approach to the task is the following: we generate synthetic training datase…