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Found 15 papers, 11 papers with code
Results of the WMT21 Metrics Shared Task: Evaluating Metrics with Expert-based Human Evaluations on TED and News Domain
Contrary to previous years’ editions, this year we acquired our own human ratings based on expert-based human evaluation via Multidimensional Quality Metrics (MQM).
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.
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.
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.
Quality-Aware Decoding for Neural Machine Translation
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.
Better Uncertainty Quantification for Machine Translation Evaluation
Neural-based machine translation (MT) evaluation metrics are progressing fast.
Onception: Active Learning with Expert Advice for Real World Machine Translation
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.
Uncertainty-Aware Machine Translation Evaluation
Several neural-based metrics have been recently proposed to evaluate machine translation quality.
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.
Online Learning Meets Machine Translation Evaluation: Finding the Best Systems with the Least Human Effort
In Machine Translation, assessing the quality of a large amount of automatic translations can be challenging.
Multilingual Email Zoning
The segmentation of emails into functional zones (also dubbed email zoning) is a relevant preprocessing step for most NLP tasks that deal with emails.
Unbabel's Participation in the WMT20 Metrics Shared Task
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.
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.
A free web service for fast COVID-19 classification of chest X-Ray images
This work provides a fast detection system of COVID-19 characteristics in X-Ray images based on deep learning (DL) techniques.
