most citedCode-switching pre-training for neural machine translation

4 citations · 8 across the 6 of their papers we have counts for

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cs.CL2022

Findings of the WMT 2022 Shared Task on Translation Suggestion

Zhen Yang, Fandong Meng, Yingxue Zhang +2

We report the result of the first edition of the WMT shared task on Translation Suggestion (TS). The task aims to provide alternatives for specific words or phrases given the entir…

cs.CL2022

Cross-Align: Modeling Deep Cross-lingual Interactions for Word Alignment

Siyu Lai, Zhen Yang, Fandong Meng +3

Word alignment which aims to extract lexicon translation equivalents between source and target sentences, serves as a fundamental tool for natural language processing. Recent studi…

cs.CL2022

Rethink about the Word-level Quality Estimation for Machine Translation from Human Judgement

Zhen Yang, Fandong Meng, Yuanmeng Yan +1

Word-level Quality Estimation (QE) of Machine Translation (MT) aims to find out potential translation errors in the translated sentence without reference. Typically, conventional w…

cs.CL2022

Generating Authentic Adversarial Examples beyond Meaning-preserving with Doubly Round-trip Translation

Siyu Lai, Zhen Yang, Fandong Meng +4

Generating adversarial examples for Neural Machine Translation (NMT) with single Round-Trip Translation (RTT) has achieved promising results by releasing the meaning-preserving res…

cs.CL20204 cited

Multiple Sclerosis Severity Classification From Clinical Text

Alister D Costa, Stefan Denkovski, Michal Malyska +5

Multiple Sclerosis (MS) is a chronic, inflammatory and degenerative neurological disease, which is monitored by a specialist using the Expanded Disability Status Scale (EDSS) and r…

cs.CL20204 cited

Code-switching pre-training for neural machine translation

Zhen Yang, Bojie Hu, Ambyera Han +2

This paper proposes a new pre-training method, called Code-Switching Pre-training (CSP for short) for Neural Machine Translation (NMT). Unlike traditional pre-training method which…