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Automatic Post-Editing

Automatic post-editing (APE) is used to correct errors in the translation made by the machine translation systems.

Papers

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Showing 101–124 of 124 papers

TitleStatusHype
Online Automatic Post-editing for MT in a Multi-Domain Translation Environment—0
PePe: Personalized Post-editing Model utilizing User-generated Post-edits—0
POSTECH-ETRI’s Submission to the WMT2020 APE Shared Task: Automatic Post-Editing with Cross-lingual Language Model—0
Proceedings of the AMTA 2018 Workshop on Translation Quality Estimation and Automatic Post-Editing—0
Pushing the Limits of Translation Quality Estimation—0
Simple Automatic Post-editing for Arabic-Japanese Machine Translation—0
APE at Scale and its Implications on MT Evaluation Biases—0
The AMU-UEdin Submission to the WMT 2017 Shared Task on Automatic Post-Editing—0
The FBK Participation in the WMT15 Automatic Post-editing Shared Task—0
The FBK Participation in the WMT 2016 Automatic Post-editing Shared Task—0
Ensembling Factored Neural Machine Translation Models for Automatic Post-Editing and Quality EstimationCode0
Learning to Copy for Automatic Post-EditingCode0
Exploring the Importance of Source Text in Automatic Post-Editing for Context-Aware Machine TranslationCode0
Automatic Post-Editing of Machine Translation: A Neural Programmer-Interpreter ApproachCode0
Deep Copycat Networks for Text-to-Text GenerationCode0
A Shared Attention Mechanism for Interpretation of Neural Automatic Post-Editing SystemsCode0
Phrasal Substitution of Idiomatic ExpressionsCode0
Adaptation of Back-translation to Automatic Post-Editing for Synthetic Data GenerationCode0
Together We Can: Multilingual Automatic Post-Editing for Low-Resource LanguagesCode0
A Workbench for Rapid Generation of Cross-Lingual SummariesCode0
Neural Machine Translation Techniques for Named Entity TransliterationCode0
Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative StudyCode0
Attention Strategies for Multi-Source Sequence-to-Sequence LearningCode0
Learning Non-Monotonic Automatic Post-Editing of Translations from Human OrderingsCode0
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