Search Results for author:
Found 6 papers, 2 papers with code
COMET: A Neural Framework for MT Evaluation
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.
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.
MT-Telescope: An interactive platform for contrastive evaluation of MT systems
We present MT-Telescope, a visualization platform designed to facilitate comparative analysis of the output quality of two Machine Translation (MT) systems.
Unbabel’s Participation in the WMT20 Metrics Shared Task
We present the contribution of the Unbabel team to the WMT 2020 Shared Task on Metrics.
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.
Searching for COMETINHO: The Little Metric That Could
In recent years, several neural fine-tuned machine translation evaluation metrics such as COMET and BLEURT have been proposed.
