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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 26–50 of 124 papers

TitleStatusHype
HW-TSC’s Participation at WMT 2020 Automatic Post Editing Shared Task—0
Alibaba’s Submission for the WMT 2020 APE Shared Task: Improving Automatic Post-Editing with Pre-trained Conditional Cross-Lingual BERT—0
Noising Scheme for Data Augmentation in Automatic Post-Editing—0
Findings of the WMT 2020 Shared Task on Automatic Post-Editing—0
Cross-Lingual Transformers for Neural Automatic Post-Editing—0
Incorporating Terminology Constraints in Automatic Post-EditingCode1
MLQE-PE: A Multilingual Quality Estimation and Post-Editing DatasetCode1
Can Automatic Post-Editing Improve NMT?Code1
Computer Assisted Translation with Neural Quality Estimation and Automatic Post-Editing—0
DynE: Dynamic Ensemble Decoding for Multi-Document SummarizationCode1
A Post-Editing Dataset in the Legal Domain: Do we Underestimate Neural Machine Translation Quality?—0
NMT and PBSMT Error Analyses in English to Brazilian Portuguese Automatic Translations—0
Learning Non-Monotonic Automatic Post-Editing of Translations from Human OrderingsCode0
Felix: Flexible Text Editing Through Tagging and InsertionCode1
Learning to Copy for Automatic Post-EditingCode0
Deep Copycat Networks for Text-to-Text GenerationCode0
Automatic Post-Editing for Machine Translation—0
Context-Aware Monolingual Repair for Neural Machine TranslationCode1
The Transference Architecture for Automatic Post-Editing—0
Improving CAT Tools in the Translation Workflow: New Approaches and Evaluation—0
Transformer-based Automatic Post-Editing with a Context-Aware Encoding Approach for Multi-Source Inputs—0
UdS Submission for the WMT 19 Automatic Post-Editing Task—0
Improving Translations by Combining Fuzzy-Match Repair with Automatic Post-Editing—0
Findings of the WMT 2019 Shared Task on Automatic Post-Editing—0
Effort-Aware Neural Automatic Post-Editing—0
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