WMT18
Related Papers
APE at Scale and Its Implications on MT Evaluation Biases
AbstractIn this work, we train an Automatic Post-Editing (APE) model and use it to reveal biases in standard MT evaluation procedures. The goal of our APE model is to correct …...
Exploiting Monolingual Data at Scale for Neural Machine Translation
AbstractWhile target-side monolingual data has been proven to be very useful to improve neural machine translation (briefly, NMT) through back translation, source-side monolingual data is not well investigated. In this …...
Counterfactual Data Augmentation for Neural Machine Translation
AbstractWe propose a data augmentation method for neural machine translation. It works by interpreting language models and phrasal alignment causally. Specifically, it creates augmented parallel translation corpora by generating (path-specific) …...
REUSE: REference-free UnSupervised Quality Estimation Metric
AbstractThis paper describes our submission to the WMT2022 shared metrics task. Our unsupervised metric estimates the translation quality at chunk-level and sentence-level. Source and target sentence chunks are retrieved by …...