Paper Info
Title
POSTECH-ETRI's Submission to the WMT2020 APE Shared Task - Automatic Post-Editing with Cross-lingual Language Model.
Abstract
This paper describes POSTECH-ETRI’s submission to WMT2020 for the shared task on automatic post-editing (APE) for 2 language pairs: English-German (En-De) and English-Chinese (En-Zh). We propose APE systems based on a cross-lingual language model, which jointly adopts translation language modeling (TLM) and masked language modeling (MLM) training objectives in the pre-training stage; the APE models then utilize jointly learned language representations between the source language and the target language. In addition, we created 19 million new sythetic triplets as additional training data for our final ensemble model. According to experimental results on the WMT2020 APE development data set, our models showed an improvement over the baseline by TER of -3.58 and a BLEU score of +5.3 for the En-De subtask; and TER of -5.29 and a BLEU score of +7.32 for the En-Zh subtask.
Year
Venue
DocType
2020
WMT@EMNLP
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Jihyung Lee101.01
WonKee Lee202.03
Jaehun Shin301.01
Baikjin Jung401.35
Young-Kil Kim523.39
Jong-Hyeok Lee674097.88