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Found 7 papers, 5 papers with code
IST-Unbabel 2021 Submission for the Quality Estimation Shared Task
We present the joint contribution of IST and Unbabel to the WMT 2021 Shared Task on Quality Estimation.
Are References Really Needed? Unbabel-IST 2021 Submission for the Metrics Shared Task
In this paper, we present the joint contribution of Unbabel and IST to the WMT 2021 Metrics Shared Task.
BLEU Meets COMET: Combining Lexical and Neural Metrics Towards Robust Machine Translation Evaluation
Although neural-based machine translation evaluation metrics, such as COMET or BLEURT, have achieved strong correlations with human judgements, they are sometimes unreliable in detecting certain phenomena that can be considered as critical errors, such as deviations in entities and numbers.
CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task
We present the joint contribution of IST and Unbabel to the WMT 2022 Shared Task on Quality Estimation (QE).
Disentangling Uncertainty in Machine Translation Evaluation
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 under noisy or out-of-domain data.
Uncertainty-Aware Machine Translation Evaluation
Several neural-based metrics have been recently proposed to evaluate machine translation quality.
Char-RNN and Active Learning for Hashtag Segmentation
We explore the abilities of character recurrent neural network (char-RNN) for hashtag segmentation.
