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Titlebook: Machine Translation; 16th China Conferenc Junhui Li,Andy Way Conference proceedings 2020 Springer Nature Singapore Pte Ltd. 2020 artificial

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樓主: 貪吃的人
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Neural Machine Translation Based on Back-Translation for Multilingual Translation Evaluation Task,ion task, we need to build a Japanese-English translation system based on only Japanese-Chinese and English-Chinese data. Our method mainly relies on synthetic data generated by back translation. We implemented three different architectures, namely Transformer-big, Transformer-base and Dynamic-Conv.
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Conference proceedings 2020?.The 13 papers presented in this volume were carefully reviewed and selected from 78 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing..
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發(fā)表于 2025-3-28 13:27:30 | 只看該作者
Unsupervised Machine Translation Quality Estimation in Black-Box Setting, machine translation parallel dataset, and the data are used to fine-tune multilingual pre-trained language models to fit human evaluation. Experiment results show that our model surpasses the previous unsupervised methods by a large margin, and achieve state-of-the-art results on MLQE Dataset.
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