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Chulun Zhou (周楚伦)
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publications
Exploring Contextual Word-level Style Relevance for Unsupervised Style Transfer
Published in ACL, 2020
Unsupervised style transfer aims to change the style of an input sentence while preserving its original content without using parallel training data…
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Towards Making the Most of Dialogue Characteristics for Neural Chat Translation
Published in EMNLP, 2021
Neural Chat Translation (NCT) aims to translate conversational text between speakers of different languages…
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Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation
Published in ACL, 2022
Most dominant neural machine translation (NMT) models are restricted to make predictions only according to the local context of preceding words in a left-to-right manner…
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A Multi-Task Multi-Stage Transitional Training Framework for Neural Chat Translation.
Published in TPAMI, 2022
Neural chat translation (NCT) aims to translate a cross-lingual chat between speakers of different languages. Existing context-aware NMT models cannot…
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