@inproceedings{junczys-dowmunt-grundkiewicz-2018-ms,
title = "{MS}-{UE}din Submission to the {WMT}2018 {APE} Shared Task: Dual-Source Transformer for Automatic Post-Editing",
author = "Junczys-Dowmunt, Marcin and
Grundkiewicz, Roman",
booktitle = "Proceedings of the Third Conference on Machine Translation: Shared Task Papers",
month = oct,
year = "2018",
address = "Belgium, Brussels",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6467",
doi = "10.18653/v1/W18-6467",
pages = "822--826",
abstract = "This paper describes the Microsoft and University of Edinburgh submission to the Automatic Post-editing shared task at WMT2018. Based on training data and systems from the WMT2017 shared task, we re-implement our own models from the last shared task and introduce improvements based on extensive parameter sharing. Next we experiment with our implementation of dual-source transformer models and data selection for the IT domain. Our submissions decisively wins the SMT post-editing sub-task establishing the new state-of-the-art and is a very close second (or equal, 16.46 vs 16.50 TER) in the NMT sub-task. Based on the rather weak results in the NMT sub-task, we hypothesize that neural-on-neural APE might not be actually useful.",
}
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%0 Conference Proceedings
%T MS-UEdin Submission to the WMT2018 APE Shared Task: Dual-Source Transformer for Automatic Post-Editing
%A Junczys-Dowmunt, Marcin
%A Grundkiewicz, Roman
%S Proceedings of the Third Conference on Machine Translation: Shared Task Papers
%D 2018
%8 oct
%I Association for Computational Linguistics
%C Belgium, Brussels
%F junczys-dowmunt-grundkiewicz-2018-ms
%X This paper describes the Microsoft and University of Edinburgh submission to the Automatic Post-editing shared task at WMT2018. Based on training data and systems from the WMT2017 shared task, we re-implement our own models from the last shared task and introduce improvements based on extensive parameter sharing. Next we experiment with our implementation of dual-source transformer models and data selection for the IT domain. Our submissions decisively wins the SMT post-editing sub-task establishing the new state-of-the-art and is a very close second (or equal, 16.46 vs 16.50 TER) in the NMT sub-task. Based on the rather weak results in the NMT sub-task, we hypothesize that neural-on-neural APE might not be actually useful.
%R 10.18653/v1/W18-6467
%U https://aclanthology.org/W18-6467
%U https://doi.org/10.18653/v1/W18-6467
%P 822-826
Markdown (Informal)
[MS-UEdin Submission to the WMT2018 APE Shared Task: Dual-Source Transformer for Automatic Post-Editing](https://aclanthology.org/W18-6467) (Junczys-Dowmunt & Grundkiewicz, 2018)
ACL