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Can Your Context-Aware MT System Pass the DiP Benchmark Tests? :
  Evaluation Benchmarks for Discourse Phenomena in Machine Translation

Can Your Context-Aware MT System Pass the DiP Benchmark Tests? : Evaluation Benchmarks for Discourse Phenomena in Machine Translation

30 April 2020
Prathyusha Jwalapuram
Barbara Rychalska
Shafiq Joty
Dominika Basaj
ArXivPDFHTML

Papers citing "Can Your Context-Aware MT System Pass the DiP Benchmark Tests? : Evaluation Benchmarks for Discourse Phenomena in Machine Translation"

3 / 3 papers shown
Title
A baseline revisited: Pushing the limits of multi-segment models for
  context-aware translation
A baseline revisited: Pushing the limits of multi-segment models for context-aware translation
Suvodeep Majumde
Stanislas Lauly
Maria Nadejde
Marcello Federico
Georgiana Dinu
43
13
0
19 Oct 2022
Rethinking Document-level Neural Machine Translation
Rethinking Document-level Neural Machine Translation
Zewei Sun
Mingxuan Wang
Hao Zhou
Chengqi Zhao
Shujian Huang
Jiajun Chen
Lei Li
VLM
83
47
0
18 Oct 2020
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Zhehuai Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
718
6,750
0
26 Sep 2016
1