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Found 10 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.
Findings of the WMT 2021 Shared Task on Quality Estimation
We report the results of the WMT 2021 shared task on Quality Estimation, where the challenge is to predict the quality of the output of neural machine translation systems at the word and sentence levels.
Better Uncertainty Quantification for Machine Translation Evaluation
Neural-based machine translation (MT) evaluation metrics are progressing fast.
Learning Disentangled Representations of Negation and Uncertainty
Negation and uncertainty modeling are long-standing tasks in natural language processing.
Uncertainty-Aware Machine Translation Evaluation
Several neural-based metrics have been recently proposed to evaluate machine translation quality.
Semantic Enrichment of Pretrained Embedding Output for Unsupervised IR
The rapid growth of scientific literature in the biomedical and clinical domain has significantly com- plicated the identification of information of interest by researchers as well as other practitioners.
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MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset
We present MLQE-PE, a new dataset for Machine Translation (MT) Quality Estimation (QE) and Automatic Post-Editing (APE).
Paths for uncertainty: Exploring the intricacies of uncertainty identification for news
We compare the differences in the definition and expression of uncertainty between a scientific domain, i. e., biomedicine, and newswire.
