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Autocorrect in the Process of Translation - Multi-task Learning Improves Dialogue Machine Translation.

, , , , and . NAACL-HLT (Industry Papers), page 105-112. Association for Computational Linguistics, (2021)

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Refinements in BTG-based Statistical Machine Translation., , , , , and . IJCNLP, page 505-512. The Association for Computer Linguistics, (2008)FineMath: A Fine-Grained Mathematical Evaluation Benchmark for Chinese Large Language Models., , , , and . CoRR, (2024)Integrating Pre-trained Model into Rule-based Dialogue Management., , , , , , , , , and 2 other author(s). AAAI, page 16097-16099. AAAI Press, (2021)A Topic-Based Coherence Model for Statistical Machine Translation., and . AAAI, page 977-983. AAAI Press, (2013)CoDoNMT: Modeling Cohesion Devices for Document-Level Neural Machine Translation., , and . COLING, page 5205-5216. International Committee on Computational Linguistics, (2022)Convolution-Enhanced Bilingual Recursive Neural Network for Bilingual Semantic Modeling., , , , and . COLING, page 3071-3081. ACL, (2016)A Source Dependency Model for Statistical Machine Translation., , , and . MTSummit, (2009)Generating Highly Relevant Questions., and . EMNLP/IJCNLP (1), page 5982-5986. Association for Computational Linguistics, (2019)Hierarchical Modeling of Global Context for Document-Level Neural Machine Translation., , , and . EMNLP/IJCNLP (1), page 1576-1585. Association for Computational Linguistics, (2019)Chinese WPLC: A Chinese Dataset for Evaluating Pretrained Language Models on Word Prediction Given Long-Range Context., , , and . EMNLP (1), page 3770-3778. Association for Computational Linguistics, (2021)