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Automatic Post-Editing
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Automatic post-editing (APE) is used to correct errors in the translation made by the machine translation systems.
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BhashaVerse : Translation Ecosystem for Indian Subcontinent Languages
Together We Can: Multilingual Automatic Post-Editing for Low-Resource Languages
HW-TSC's Submission to the CCMT 2024 Machine Translation Tasks
MQM-APE: Toward High-Quality Error Annotation Predictors with Automatic Post-Editing in LLM Translation Evaluators
APE-then-QE: Correcting then Filtering Pseudo Parallel Corpora for MT Training Data Creation
Domain Terminology Integration into Machine Translation: Leveraging Large Language Models
PePe: Personalized Post-editing Model utilizing User-generated Post-edits
An Empirical Study of Automatic Post-Editing
Automatic Correction of Human Translations
Advancing Semi-Supervised Learning for Automatic Post-Editing: Data-Synthesis by Mask-Infilling with Erroneous Terms
Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study
A Self-Supervised Automatic Post-Editing Data Generation Tool
Netmarble AI Center's WMT21 Automatic Post-Editing Shared Task Submission
Transfer Learning for Sequence Generation: from Single-source to Multi-source
Automatic Post-Editing for Vietnamese
Incorporating Terminology Constraints in Automatic Post-Editing
MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset
Can Automatic Post-Editing Improve NMT?
Computer Assisted Translation with Neural Quality Estimation and Automatic Post-Editing
DynE: Dynamic Ensemble Decoding for Multi-Document Summarization
Learning Non-Monotonic Automatic Post-Editing of Translations from Human Orderings
Felix: Flexible Text Editing Through Tagging and Insertion
Learning to Copy for Automatic Post-Editing
Automatic Post-Editing for Machine Translation
Context-Aware Monolingual Repair for Neural Machine Translation
Improving CAT Tools in the Translation Workflow: New Approaches and Evaluation
The Transference Architecture for Automatic Post-Editing
Transformer-based Automatic Post-Editing with a Context-Aware Encoding Approach for Multi-Source Inputs
UdS Submission for the WMT 19 Automatic Post-Editing Task
Simple Automatic Post-editing for Arabic-Japanese Machine Translation
A Simple and Effective Approach to Automatic Post-Editing with Transfer Learning
Unbabel's Submission to the WMT2019 APE Shared Task: BERT-based Encoder-Decoder for Automatic Post-Editing
Levenshtein Transformer
APE at Scale and its Implications on MT Evaluation Biases
MS-UEdin Submission to the WMT2018 APE Shared Task: Dual-Source Transformer for Automatic Post-Editing
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