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Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2024,6,30]]},"abstract":"<jats:p>Machine translation\u2013the automatic transformation of one natural language (source language) into another (target language) through computational means\u2013occupies a central role in computational linguistics and stands as a cornerstone of research within the field of Natural Language Processing (NLP). In recent years, the prominence of Neural Machine Translation (NMT) has grown exponentially, offering an advanced framework for machine translation research. It is noted for its superior translation performance, especially when tackling the challenges posed by low-resource language pairs that suffer from a limited corpus of data resources. This article offers an exhaustive exploration of the historical trajectory and advancements in NMT, accompanied by an analysis of the underlying foundational concepts. It subsequently provides a concise demarcation of the unique characteristics associated with low-resource languages and presents a succinct review of pertinent translation models and their applications, specifically within the context of languages with low-resources. Moreover, this article delves deeply into machine translation techniques, highlighting approaches tailored for Chinese-centric low-resource languages. Ultimately, it anticipates upcoming research directions in the realm of low-resource language translation.<\/jats:p>","DOI":"10.1145\/3665244","type":"journal-article","created":{"date-parts":[[2024,5,16]],"date-time":"2024-05-16T11:25:29Z","timestamp":1715858729000},"page":"1-60","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Neural Machine Translation for Low-Resource Languages from a Chinese-centric Perspective: A Survey"],"prefix":"10.1145","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9813-217X","authenticated-orcid":false,"given":"Jinyi","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University, Shenyang, China"},{"name":"Faculty of Engineering, Gifu University, Gifu, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2968-2104","authenticated-orcid":false,"given":"Ke","family":"Su","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University, Shenyang, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4669-9120","authenticated-orcid":false,"given":"Haowei","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University, Shenyang, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5787-1613","authenticated-orcid":false,"given":"Jiannan","family":"Mao","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Gifu University, Gifu, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0981-6677","authenticated-orcid":false,"given":"Ye","family":"Tian","sequence":"additional","affiliation":[{"name":"Zhuzhou CRRC Times Electric Co., Ltd., Zhuzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2955-3771","authenticated-orcid":false,"given":"Feng","family":"Wen","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University, Shenyang, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7683-8972","authenticated-orcid":false,"given":"Chong","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University, Shenyang, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4106-1099","authenticated-orcid":false,"given":"Tadahiro","family":"Matsumoto","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Gifu University, Gifu, Japan"}]}],"member":"320","published-online":{"date-parts":[[2024,6,21]]},"reference":[{"issue":"6","key":"e_1_3_2_2_2","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1037\/h0042519","article-title":"The perceptron: A probabilistic model for information storage and organization in the brain","volume":"65","author":"Rosenblatt Frank","year":"1958","unstructured":"Frank Rosenblatt. 1958. 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Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, 5823\u20135840. DOI:10.18653\/V1\/2023.ACL-LONG.320"},{"key":"e_1_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.2305.06575"},{"key":"e_1_3_2_61_2","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.2305.01181"},{"key":"e_1_3_2_62_2","first-page":"375","volume-title":"Natural Language Processing and Chinese Computing - 12th National CCF Conference, NLPCC 2023, Foshan, China, October 12\u201315, 2023, Proceedings, Part I (Lecture Notes in Computer Science)","volume":"14302","author":"Huang Hui","year":"2023","unstructured":"Hui Huang, Shuangzhi Wu, Xinnian Liang, Bing Wang, Yanrui Shi, Peihao Wu, Muyun Yang, and Tiejun Zhao. 2023. Towards making the most of LLM for translation quality estimation. In Natural Language Processing and Chinese Computing - 12th National CCF Conference, NLPCC 2023, Foshan, China, October 12\u201315, 2023, Proceedings, Part I (Lecture Notes in Computer Science), Fei Liu, Nan Duan, Qingting Xu, and Yu Hong (Eds.), Vol. 14302. Springer, 375\u2013386. DOI:10.1007\/978-3-031-44693-1_30"},{"key":"e_1_3_2_63_2","volume-title":"International Conference on Learning Representations (ICLR\u201924)","author":"Fu Tingchen","year":"2024","unstructured":"Tingchen Fu, Lemao Liu, Deng Cai, Guoping Huang, Shuming Shi, and Rui Yan. 2024. The reasonableness behind unreasonable translation capability of large language model. In International Conference on Learning Representations (ICLR\u201924)."},{"key":"e_1_3_2_64_2","first-page":"157","volume-title":"Proceedings of the 24th Annual Conference of the European Association for Machine Translation, EAMT 2023, Tampere, Finland, 12\u201315 June 2023","author":"Bawden Rachel","year":"2023","unstructured":"Rachel Bawden and Fran\u00e7ois Yvon. 2023. Investigating the translation performance of a large multilingual language model: The case of BLOOM. In Proceedings of the 24th Annual Conference of the European Association for Machine Translation, EAMT 2023, Tampere, Finland, 12\u201315 June 2023, Mary Nurminen, Judith Brenner, Maarit Koponen, Sirkku Latomaa, Mikhail Mikhailov, Frederike Schierl, Tharindu Ranasinghe, Eva Vanmassenhove, Sergi Alvarez Vidal, Nora Aranberri, Mara Nunziatini, Carla Parra Escart\u00edn, Mikel L. Forcada, Maja Popovic, Carolina Scarton, and Helena Moniz (Eds.). 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Association for Computational Linguistics, 16646\u201316661. https:\/\/aclanthology.org\/2023.emnlp-main.1036"},{"key":"e_1_3_2_67_2","first-page":"311","volume-title":"Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, July 6\u201312, 2002, Philadelphia, PA, USA","author":"Papineni Kishore","year":"2002","unstructured":"Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. BLEU: A method for automatic evaluation of machine translation. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, July 6\u201312, 2002, Philadelphia, PA, USA. ACL, 311\u2013318. DOI:10.3115\/1073083.1073135"},{"key":"e_1_3_2_68_2","first-page":"74","volume-title":"Text Summarization Branches Out","author":"Lin Chin-Yew","year":"2004","unstructured":"Chin-Yew Lin. 2004. ROUGE: A package for automatic evaluation of summaries. In Text Summarization Branches Out. 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Association for Computational Linguistics, 10176\u201310184. https:\/\/aclanthology.org\/2023.findings-emnlp.682"},{"key":"e_1_3_2_71_2","first-page":"5622","volume-title":"Findings of the Association for Computational Linguistics: EMNLP 2023, Singapore, December 6\u201310, 2023","author":"Peng Keqin","year":"2023","unstructured":"Keqin Peng, Liang Ding, Qihuang Zhong, Li Shen, Xuebo Liu, Min Zhang, Yuanxin Ouyang, and Dacheng Tao. 2023. Towards making the most of ChatGPT for machine translation. In Findings of the Association for Computational Linguistics: EMNLP 2023, Singapore, December 6\u201310, 2023, Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). 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In Proceedings of the Eighth Conference on Machine Translation, WMT2023, Singapore, December 6\u20137, 2023, Philipp Koehn, Barry Haddon, Tom Kocmi, and Christof Monz (Eds.). Association for Computational Linguistics, 419\u2013451. https:\/\/aclanthology.org\/2023.wmt-1.41"},{"key":"e_1_3_2_76_2","first-page":"81","volume-title":"Proceedings of the 22nd Annual Conference of the European Association for Machine Translation","author":"Edman Lukas","year":"2020","unstructured":"Lukas Edman, Antonio Toral, and Gertjan van Noord. 2020. Low-resource unsupervised NMT: Diagnosing the problem and providing a linguistically motivated solution. In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation. 81\u201390."},{"key":"e_1_3_2_77_2","first-page":"2703","volume-title":"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16\u201320, 2020","author":"Chronopoulou Alexandra","year":"2020","unstructured":"Alexandra Chronopoulou, Dario Stojanovski, and Alexander M. Fraser. 2020. Reusing a pretrained language model on languages with limited corpora for unsupervised NMT. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16\u201320, 2020, Bonnie Webber, Trevor Cohn, Yulan He, and Yang Liu (Eds.). Association for Computational Linguistics, 2703\u20132711. 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In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, EAMT 2020, Lisboa, Portugal, November 3\u20135, 2020. European Association for Machine Translation, 35\u201344. https:\/\/aclanthology.org\/2020.eamt-1.5\/"},{"key":"e_1_3_2_95_2","unstructured":"Zhuoyuan Mao Fabien Cromier\u00e8s Raj Dabre Haiyue Song and Sadao Kurohashi. 2020. JASS: Japanese-specific sequence to sequence pre-training for neural machine translation. (2020) 3683\u20133691. https:\/\/aclanthology.org\/2020.lrec-1.454\/"},{"key":"e_1_3_2_96_2","first-page":"3977","volume-title":"Proceedings of the 28th International Conference on Computational Linguistics, COLING 2020, Barcelona, Spain (Online), December 8\u201313, 2020","author":"Xu Chen","year":"2020","unstructured":"Chen Xu, Bojie Hu, Yufan Jiang, Kai Feng, Zeyang Wang, Shen Huang, Qi Ju, Tong Xiao, and Jingbo Zhu. 2020. Dynamic curriculum learning for low-resource neural machine translation. In Proceedings of the 28th International Conference on Computational Linguistics, COLING 2020, Barcelona, Spain (Online), December 8\u201313, 2020. International Committee on Computational Linguistics, 3977\u20133989. DOI:10.18653\/V1\/2020.COLING-MAIN.352"},{"key":"e_1_3_2_97_2","doi-asserted-by":"publisher","DOI":"10.1162\/COLI_A_00446"},{"key":"e_1_3_2_98_2","article-title":"Neural machine translation for low-resource languages: A survey","volume":"2106","author":"Ranathunga Surangika","year":"2021","unstructured":"Surangika Ranathunga, En-Shiun Annie Lee, Marjana Prifti Skenduli, Ravi Shekhar, Mehreen Alam, and Rishemjit Kaur. 2021. Neural machine translation for low-resource languages: A survey. CoRR abs\/2106.15115 (2021). arXiv:2106.15115https:\/\/arxiv.org\/abs\/2106.15115","journal-title":"CoRR"},{"key":"e_1_3_2_99_2","first-page":"5894","volume-title":"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16\u201320, 2020","author":"Dou Zi-Yi","year":"2020","unstructured":"Zi-Yi Dou, Antonios Anastasopoulos, and Graham Neubig. 2020. Dynamic data selection and weighting for iterative back-translation. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16\u201320, 2020, Bonnie Webber, Trevor Cohn, Yulan He, and Yang Liu (Eds.). Association for Computational Linguistics, 5894\u20135904. 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DOI:10.18653\/V1\/2020.COLING-MAIN.304"},{"key":"e_1_3_2_101_2","article-title":"Improving multilingual neural machine translation for low-resource languages: French, English-Vietnamese","author":"Ngo Thi-Vinh","year":"2020","unstructured":"Thi-Vinh Ngo, Phuong-Thai Nguyen, Thanh-Le Ha, Khac-Quy Dinh, and Le-Minh Nguyen. 2020. Improving multilingual neural machine translation for low-resource languages: French, English-Vietnamese. arXiv preprint arXiv:2012.08743 (2020).","journal-title":"arXiv preprint arXiv:2012.08743"},{"key":"e_1_3_2_102_2","first-page":"5786","volume-title":"Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, Volume 1: Long Papers","author":"Xia Mengzhou","year":"2019","unstructured":"Mengzhou Xia, Xiang Kong, Antonios Anastasopoulos, and Graham Neubig. 2019. Generalized data augmentation for low-resource translation. In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, Volume 1: Long Papers, Anna Korhonen, David R. Traum, and Llu\u00eds M\u00e0rquez (Eds.). Association for Computational Linguistics, 5786\u20135796. DOI:10.18653\/V1\/P19-1579"},{"key":"e_1_3_2_103_2","first-page":"3853","volume-title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020","author":"Qin Libo","year":"2020","unstructured":"Libo Qin, Minheng Ni, Yue Zhang, and Wanxiang Che. 2020. CoSDA-ML: Multi-lingual code-switching data augmentation for zero-shot cross-lingual NLP. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020, Christian Bessiere (Ed.). ijcai.org, 3853\u20133860. DOI:10.24963\/IJCAI.2020\/533"},{"key":"e_1_3_2_104_2","unstructured":"Xuan-Phi Nguyen Shafiq R. Joty Kui Wu and Ai Ti Aw. 2020. Data diversification: A simple strategy for neural machine translation. (2020). https:\/\/proceedings.neurips.cc\/paper\/2020\/hash\/7221e5c8ec6b08ef6d3f9ff3ce6eb1d1-Abstract.html"},{"key":"e_1_3_2_105_2","first-page":"328","volume-title":"Proceedings of the 5th Workshop on Noisy User-generated Text, W-NUT@EMNLP 2019, Hong Kong, China, November 4, 2019","author":"Li Zhenhao","year":"2019","unstructured":"Zhenhao Li and Lucia Specia. 2019. Improving neural machine translation robustness via data augmentation: Beyond back-translation. In Proceedings of the 5th Workshop on Noisy User-generated Text, W-NUT@EMNLP 2019, Hong Kong, China, November 4, 2019, Wei Xu, Alan Ritter, Tim Baldwin, and Afshin Rahimi (Eds.). Association for Computational Linguistics, 328\u2013336. DOI:10.18653\/V1\/D19-5543"},{"key":"e_1_3_2_106_2","unstructured":"Min-Hyung Kang and Kais Kudrolli. 2019. VaLaR NMT: Vastly Lacking Resources Neural Machine Translation. (2019)."},{"key":"e_1_3_2_107_2","first-page":"3587","volume-title":"Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence","author":"Chen Guanhua","year":"2021","unstructured":"Guanhua Chen, Yun Chen, Yong Wang, and Victor O. K. Li. 2021. Lexical-constraint-aware neural machine translation via data augmentation. In Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence. 3587\u20133593."},{"key":"e_1_3_2_108_2","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2023.3301214"},{"key":"e_1_3_2_109_2","first-page":"355","volume-title":"Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, EMNLP 2011, 27\u201331 July 2011, John McIntyre Conference Centre, Edinburgh, UK, A Meeting of SIGDAT, a Special Interest Group of the ACL","author":"Axelrod Amittai","year":"2011","unstructured":"Amittai Axelrod, Xiaodong He, and Jianfeng Gao. 2011. Domain adaptation via pseudo in-domain data selection. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, EMNLP 2011, 27\u201331 July 2011, John McIntyre Conference Centre, Edinburgh, UK, A Meeting of SIGDAT, a Special Interest Group of the ACL. ACL, 355\u2013362. https:\/\/aclanthology.org\/D11-1033\/"},{"key":"e_1_3_2_110_2","first-page":"1400","volume-title":"Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017, Copenhagen, Denmark, September 9\u201311, 2017","author":"Wees Marlies van der","year":"2017","unstructured":"Marlies van der Wees, Arianna Bisazza, and Christof Monz. 2017. Dynamic data selection for neural machine translation. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017, Copenhagen, Denmark, September 9\u201311, 2017. Association for Computational Linguistics, 1400\u20131410. DOI:10.18653\/V1\/D17-1147"},{"key":"e_1_3_2_111_2","first-page":"153","volume-title":"2018 International Conference on Asian Language Processing, IALP 2018, Bandung, Indonesia, November 15\u201317, 2018","author":"Zhang Pei","year":"2018","unstructured":"Pei Zhang, Xueying Xu, and Deyi Xiong. 2018. Active learning for neural machine translation. In 2018 International Conference on Asian Language Processing, IALP 2018, Bandung, Indonesia, November 15\u201317, 2018, Minghui Dong, Moch Arif Bijaksana, Herry Sujaini, Ade Romadhony, Fariska Z. Ruskanda, Elvira Nurfadhilah, and Lyla Ruslana Aini (Eds.). IEEE, 153\u2013158. DOI:10.1109\/IALP.2018.8629116"},{"issue":"10","key":"e_1_3_2_112_2","doi-asserted-by":"crossref","first-page":"1727","DOI":"10.1109\/TASLP.2018.2837223","article-title":"Sentence selection and weighting for neural machine translation domain adaptation","volume":"26","author":"Wang Rui","year":"2018","unstructured":"Rui Wang, Masao Utiyama, Andrew Finch, Lemao Liu, Kehai Chen, and Eiichiro Sumita. 2018. Sentence selection and weighting for neural machine translation domain adaptation. 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DOI:10.18653\/V1\/N19-1044"},{"issue":"2","key":"e_1_3_2_114_2","first-page":"175","article-title":"The annotation technology of Japanese scientific language in the Sino Japanese bilingual parallel corpus","author":"Li Yipeng","year":"2015","unstructured":"Yipeng Li. 2015. The annotation technology of Japanese scientific language in the Sino Japanese bilingual parallel corpus. Guide to Business2 (2015), 175\u2013176.","journal-title":"Guide to Business"},{"key":"e_1_3_2_115_2","doi-asserted-by":"publisher","DOI":"10.3390\/info11050255"},{"key":"e_1_3_2_116_2","first-page":"856","volume-title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31\u2013November 4, 2018","author":"Wang Xinyi","year":"2018","unstructured":"Xinyi Wang, Hieu Pham, Zihang Dai, and Graham Neubig. 2018. SwitchOut: An efficient data augmentation algorithm for neural machine translation. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31\u2013November 4, 2018. Association for Computational Linguistics, 856\u2013861. DOI:10.18653\/V1\/D18-1100"},{"key":"e_1_3_2_117_2","first-page":"5539","volume-title":"Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, Volume 1: Long Papers","author":"Gao Fei","year":"2019","unstructured":"Fei Gao, Jinhua Zhu, Lijun Wu, Yingce Xia, Tao Qin, Xueqi Cheng, Wengang Zhou, and Tie-Yan Liu. 2019. Soft contextual data augmentation for neural machine translation. In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, Volume 1: Long Papers, Anna Korhonen, David R. Traum, and Llu\u00eds M\u00e0rquez (Eds.). Association for Computational Linguistics, 5539\u20135544. DOI:10.18653\/V1\/P19-1555"},{"key":"e_1_3_2_118_2","first-page":"45","volume-title":"Proceedings of the Fourth Conference on Machine Translation, WMT 2019, Florence, Italy, August 1\u20132, 2019 - Volume 1: Research Papers","author":"Gra\u00e7a Miguel","year":"2019","unstructured":"Miguel Gra\u00e7a, Yunsu Kim, Julian Schamper, Shahram Khadivi, and Hermann Ney. 2019. Generalizing back-translation in neural machine translation. In Proceedings of the Fourth Conference on Machine Translation, WMT 2019, Florence, Italy, August 1\u20132, 2019 - Volume 1: Research Papers. Association for Computational Linguistics, 45\u201352. DOI:10.18653\/V1\/W19-5205"},{"key":"e_1_3_2_119_2","first-page":"48","volume-title":"Proceedings of the 15th International Conference on Spoken Language Translation, IWSLT 2018, Bruges, Belgium, October 29\u201330, 2018","author":"Nishimura Yuta","year":"2018","unstructured":"Yuta Nishimura, Katsuhito Sudoh, Graham Neubig, and Satoshi Nakamura. 2018. Multi-source neural machine translation with data augmentation. In Proceedings of the 15th International Conference on Spoken Language Translation, IWSLT 2018, Bruges, Belgium, October 29\u201330, 2018. International Conference on Spoken Language Translation, 48\u201353. https:\/\/aclanthology.org\/2018.iwslt-1.7"},{"key":"e_1_3_2_120_2","first-page":"35","volume-title":"Proceedings of the Fourth Workshop on Discourse in Machine Translation, DiscoMT@EMNLP 2019, Hong Kong, China, November 3, 2019","author":"Sugiyama Amane","year":"2019","unstructured":"Amane Sugiyama and Naoki Yoshinaga. 2019. Data augmentation using back-translation for context-aware neural machine translation. In Proceedings of the Fourth Workshop on Discourse in Machine Translation, DiscoMT@EMNLP 2019, Hong Kong, China, November 3, 2019, Andrei Popescu-Belis, Sharid Lo\u00e1iciga, Christian Hardmeier, and Deyi Xiong (Eds.). Association for Computational Linguistics, 35\u201344. DOI:10.18653\/V1\/D19-6504"},{"key":"e_1_3_2_121_2","first-page":"53","volume-title":"Proceedings of the Fourth Conference on Machine Translation, WMT 2019, Florence, Italy, August 1\u20132, 2019 - Volume 1: Research Papers","author":"Caswell Isaac","year":"2019","unstructured":"Isaac Caswell, Ciprian Chelba, and David Grangier. 2019. Tagged back-translation. In Proceedings of the Fourth Conference on Machine Translation, WMT 2019, Florence, Italy, August 1\u20132, 2019 - Volume 1: Research Papers. Association for Computational Linguistics, 53\u201363. DOI:10.18653\/V1\/W19-5206"},{"key":"e_1_3_2_122_2","first-page":"4334","volume-title":"Proceedings of the 28th International Conference on Computational Linguistics, COLING 2020, Barcelona, Spain (Online), December 8\u201313, 2020","author":"Khatri Jyotsana","year":"2020","unstructured":"Jyotsana Khatri and Pushpak Bhattacharyya. 2020. Filtering back-translated data in unsupervised neural machine translation. In Proceedings of the 28th International Conference on Computational Linguistics, COLING 2020, Barcelona, Spain (Online), December 8\u201313, 2020, Donia Scott, N\u00faria Bel, and Chengqing Zong (Eds.). International Committee on Computational Linguistics, 4334\u20134339. DOI:10.18653\/V1\/2020.COLING-MAIN.383"},{"key":"e_1_3_2_123_2","first-page":"5884","volume-title":"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16\u201320, 2020","author":"Wei Hao-Ran","year":"2020","unstructured":"Hao-Ran Wei, Zhirui Zhang, Boxing Chen, and Weihua Luo. 2020. Iterative domain-repaired back-translation. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16\u201320, 2020. Association for Computational Linguistics, 5884\u20135893. DOI:10.18653\/V1\/2020.EMNLP-MAIN.474"},{"key":"e_1_3_2_124_2","article-title":"Iterative self-learning for enhanced back-translation in low resource neural machine translation","volume":"2011","author":"Abdulmumin Idris","year":"2020","unstructured":"Idris Abdulmumin, Bashir Shehu Galadanci, and Ismaila Idris Sinan. 2020. Iterative self-learning for enhanced back-translation in low resource neural machine translation. CoRR abs\/2011.07403 (2020). arXiv:2011.07403https:\/\/arxiv.org\/abs\/2011.07403","journal-title":"CoRR"},{"key":"e_1_3_2_125_2","volume-title":"9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3\u20137, 2021","author":"Pham Hieu","year":"2021","unstructured":"Hieu Pham, Xinyi Wang, Yiming Yang, and Graham Neubig. 2021. Meta back-translation. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3\u20137, 2021. OpenReview.net. https:\/\/openreview.net\/forum?id=3jjmdp7Hha"},{"issue":"08","key":"e_1_3_2_126_2","first-page":"1497","article-title":"A Chinese-Vietnamese neural machine translation method based on synonym data augmentation","volume":"43","author":"You Congcong","year":"2021","unstructured":"Congcong You, Shengxiang Gao, Zhengtao Yu, Cunli Mao, and Runhai Pan. 2021. A Chinese-Vietnamese neural machine translation method based on synonym data augmentation. Computer Engineering & Science 43, 08 (2021), 1497.","journal-title":"Computer Engineering & Science"},{"issue":"8","key":"e_1_3_2_127_2","first-page":"47","article-title":"Phrase substitution based pseudo-parallel sentence pair generation between Chinese and Vietnamese","volume":"35","author":"Jia Chengxun","year":"2021","unstructured":"Chengxun Jia, Hua Lai, Zhengtao Yu, Yonghua Wen, and Zhiqiang Yu. 2021. Phrase substitution based pseudo-parallel sentence pair generation between Chinese and Vietnamese. Journal of Chinese Information Processing 35, 8 (2021), 47\u201355.","journal-title":"Journal of Chinese Information Processing"},{"issue":"3","key":"e_1_3_2_128_2","first-page":"4","article-title":"Cooperative research on Chinese-Japanese machine translation for S&T documents","volume":"3","author":"Zhao Zhiyun","year":"2017","unstructured":"Zhiyun Zhao, Chongde Shi, Yanqing He, Yingfan Gao, and Changqing Yao. 2017. Cooperative research on Chinese-Japanese machine translation for S&T documents. Technology Intelligence Engineering 3, 3 (2017), 4\u20139.","journal-title":"Technology Intelligence Engineering"},{"key":"e_1_3_2_129_2","first-page":"109","volume-title":"Proceedings of the 17th International Conference on Spoken Language Translation, IWSLT 2020, Online, July 9\u201310, 2020","author":"Zhuang Yimeng","year":"2020","unstructured":"Yimeng Zhuang, Yuan Zhang, and Lijie Wang. 2020. LIT team\u2019s system description for Japanese-Chinese machine translation task in IWSLT 2020. In Proceedings of the 17th International Conference on Spoken Language Translation, IWSLT 2020, Online, July 9\u201310, 2020, Marcello Federico, Alex Waibel, Kevin Knight, Satoshi Nakamura, Hermann Ney, Jan Niehues, Sebastian St\u00fcker, Dekai Wu, Joseph Mariani, and Fran\u00e7ois Yvon (Eds.). Association for Computational Linguistics, 109\u2013113. DOI:10.18653\/V1\/2020.IWSLT-1.12"},{"key":"e_1_3_2_130_2","first-page":"166","volume-title":"Proceedings of the 17th International Conference on Spoken Language Translation, IWSLT 2020, Online, July 9\u201310, 2020","author":"Hagiwara Masato","year":"2020","unstructured":"Masato Hagiwara. 2020. Octanove labs\u2019 Japanese-Chinese open domain translation system. In Proceedings of the 17th International Conference on Spoken Language Translation, IWSLT 2020, Online, July 9\u201310, 2020, Marcello Federico, Alex Waibel, Kevin Knight, Satoshi Nakamura, Hermann Ney, Jan Niehues, Sebastian St\u00fcker, Dekai Wu, Joseph Mariani, and Fran\u00e7ois Yvon (Eds.). Association for Computational Linguistics, 166\u2013171. DOI:10.18653\/V1\/2020.IWSLT-1.20"},{"key":"e_1_3_2_131_2","first-page":"1916","volume-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, Minneapolis, MN, USA, June 2\u20137, 2019, Volume 1 (Long and Short Papers)","author":"Vaibhav Vaibhav","year":"2019","unstructured":"Vaibhav Vaibhav, Sumeet Singh, Craig Stewart, and Graham Neubig. 2019. Improving robustness of machine translation with synthetic noise. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, Minneapolis, MN, USA, June 2\u20137, 2019, Volume 1 (Long and Short Papers). Association for Computational Linguistics, 1916\u20131920. DOI:10.18653\/V1\/N19-1190"},{"key":"e_1_3_2_132_2","first-page":"82","volume-title":"Proceedings of the 14th International Conference on Spoken Language Translation, IWSLT 2017, Tokyo, Japan, December 14\u201315, 2017","author":"Hassan Hany","year":"2017","unstructured":"Hany Hassan, Mostafa Elaraby, and Ahmed Y. Tawfik. 2017. Synthetic data for neural machine translation of spoken-dialects. In Proceedings of the 14th International Conference on Spoken Language Translation, IWSLT 2017, Tokyo, Japan, December 14\u201315, 2017, Sakriani Sakti and Masao Utiyama (Eds.). International Workshop on Spoken Language Translation, 82\u201389. https:\/\/aclanthology.org\/2017.iwslt-1.12"},{"key":"e_1_3_2_133_2","first-page":"567","volume-title":"Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, July 30\u2013August 4, Volume 2: Short Papers","author":"Fadaee Marzieh","year":"2017","unstructured":"Marzieh Fadaee, Arianna Bisazza, and Christof Monz. 2017. Data augmentation for low-resource neural machine translation. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, July 30\u2013August 4, Volume 2: Short Papers. Association for Computational Linguistics, 567\u2013573. DOI:10.18653\/V1\/P17-2090"},{"key":"e_1_3_2_134_2","first-page":"1800","volume-title":"Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, Volume 1: Long Papers","author":"Bult\u00e9 Bram","year":"2019","unstructured":"Bram Bult\u00e9 and Arda Tezcan. 2019. Neural fuzzy repair: Integrating fuzzy matches into neural machine translation. In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, Volume 1: Long Papers, Anna Korhonen, David R. Traum, and Llu\u00eds M\u00e0rquez (Eds.). Association for Computational Linguistics, 1800\u20131809. DOI:10.18653\/V1\/P19-1175"},{"key":"e_1_3_2_135_2","article-title":"Dictionary-based data augmentation for cross-domain neural machine translation","volume":"2004","author":"Peng Wei","year":"2020","unstructured":"Wei Peng, Chongxuan Huang, Tianhao Li, Yun Chen, and Qun Liu. 2020. Dictionary-based data augmentation for cross-domain neural machine translation. CoRR abs\/2004.02577 (2020). arXiv:2004.02577https:\/\/arxiv.org\/abs\/2004.02577","journal-title":"CoRR"},{"key":"e_1_3_2_136_2","first-page":"7553","volume-title":"ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP\u201921)","author":"Li Daniel","year":"2021","unstructured":"Daniel Li, I Te, Naveen Arivazhagan, Colin Cherry, and Dirk Padfield. 2021. Sentence boundary augmentation for neural machine translation robustness. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP\u201921). IEEE, 7553\u20137557."},{"key":"e_1_3_2_137_2","first-page":"138","volume-title":"Proceedings of the Second Conference on Machine Translation, WMT 2017, Copenhagen, Denmark, September 7\u20138, 2017","author":"Chinea-Rios Mara","year":"2017","unstructured":"Mara Chinea-Rios, \u00c1lvaro Peris, and Francisco Casacuberta. 2017. Adapting neural machine translation with parallel synthetic data. In Proceedings of the Second Conference on Machine Translation, WMT 2017, Copenhagen, Denmark, September 7\u20138, 2017, Ondrej Bojar, Christian Buck, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno-Yepes, Philipp Koehn, and Julia Kreutzer (Eds.). Association for Computational Linguistics, 138\u2013147. DOI:10.18653\/V1\/W17-4714"},{"issue":"5","key":"e_1_3_2_138_2","doi-asserted-by":"crossref","first-page":"255","DOI":"10.3390\/info11050255","article-title":"A diverse data augmentation strategy for low-resource neural machine translation","volume":"11","author":"Li Yu","year":"2020","unstructured":"Yu Li, Xiao Li, Yating Yang, and Rui Dong. 2020. A diverse data augmentation strategy for low-resource neural machine translation. Information 11, 5 (2020), 255.","journal-title":"Information"},{"key":"e_1_3_2_139_2","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00065"},{"key":"e_1_3_2_140_2","first-page":"3974","volume-title":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17","author":"Cheng Yong","year":"2017","unstructured":"Yong Cheng, Qian Yang, Yang Liu, Maosong Sun, and Wei Xu. 2017. Joint training for pivot-based neural machine translation. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17. 3974\u20133980. DOI:10.24963\/ijcai.2017\/555"},{"key":"e_1_3_2_141_2","first-page":"84","volume-title":"Proceedings of the Third Conference on Machine Translation: Research Papers","author":"Lu Yichao","year":"2018","unstructured":"Yichao Lu, Phillip Keung, Faisal Ladhak, Vikas Bhardwaj, Shaonan Zhang, and Jason Sun. 2018. A neural interlingua for multilingual machine translation. In Proceedings of the Third Conference on Machine Translation: Research Papers. Association for Computational Linguistics, Brussels, Belgium, 84\u201392. DOI:10.18653\/v1\/W18-6309"},{"key":"e_1_3_2_142_2","first-page":"115","volume-title":"The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7\u201312, 2020","author":"Ji Baijun","year":"2020","unstructured":"Baijun Ji, Zhirui Zhang, Xiangyu Duan, Min Zhang, Boxing Chen, and Weihua Luo. 2020. Cross-lingual pre-training based transfer for zero-shot neural machine translation. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7\u201312, 2020. AAAI Press, 115\u2013122. https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/5341"},{"key":"e_1_3_2_143_2","first-page":"1259","volume-title":"Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)","author":"Liu Danni","year":"2021","unstructured":"Danni Liu, Jan Niehues, James Cross, Francisco Guzm\u00e1n, and Xian Li. 2021. Improving zero-shot translation by disentangling positional information. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics, Online, 1259\u20131273. 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DOI:10.18653\/v1\/2021.emnlp-main.2"},{"key":"e_1_3_2_145_2","article-title":"The missing ingredient in zero-shot neural machine translation","volume":"1903","author":"Arivazhagan Naveen","year":"2019","unstructured":"Naveen Arivazhagan, Ankur Bapna, Orhan Firat, Roee Aharoni, Melvin Johnson, and Wolfgang Macherey. 2019. The missing ingredient in zero-shot neural machine translation. CoRR abs\/1903.07091 (2019). arXiv:1903.07091http:\/\/arxiv.org\/abs\/1903.07091","journal-title":"CoRR"},{"key":"e_1_3_2_146_2","first-page":"1184","volume-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)","author":"Al-Shedivat Maruan","year":"2019","unstructured":"Maruan Al-Shedivat and Ankur Parikh. 2019. Consistency by agreement in zero-shot neural machine translation. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, Minneapolis, Minnesota, USA, 1184\u20131197. DOI:10.18653\/v1\/N19-1121"},{"key":"e_1_3_2_147_2","doi-asserted-by":"crossref","first-page":"13","DOI":"10.18653\/v1\/W19-5202","volume-title":"Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers)","author":"Pham Ngoc-Quan","year":"2019","unstructured":"Ngoc-Quan Pham, Jan Niehues, Thanh-Le Ha, and Alexander Waibel. 2019. Improving zero-shot translation with language-independent constraints. In Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers). Association for Computational Linguistics, Florence, Italy, 13\u201323. DOI:10.18653\/v1\/W19-5202"},{"key":"e_1_3_2_148_2","first-page":"244","volume-title":"Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)","author":"Pan Xiao","year":"2021","unstructured":"Xiao Pan, Mingxuan Wang, Liwei Wu, and Lei Li. 2021. Contrastive learning for many-to-many multilingual neural machine translation. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics, Online, 244\u2013258. DOI:10.18653\/v1\/2021.acl-long.21"},{"key":"e_1_3_2_149_2","first-page":"6492","volume-title":"Findings of the Association for Computational Linguistics: EMNLP 2022","author":"Gu Shuhao","year":"2022","unstructured":"Shuhao Gu and Yang Feng. 2022. Improving zero-shot multilingual translation with universal representations and cross-mapping. In Findings of the Association for Computational Linguistics: EMNLP 2022. Association for Computational Linguistics, Abu Dhabi, United Arab Emirates, 6492\u20136504. https:\/\/aclanthology.org\/2022.findings-emnlp.485"},{"key":"e_1_3_2_150_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.264"},{"key":"e_1_3_2_151_2","first-page":"1258","volume-title":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics","author":"Gu Jiatao","year":"2019","unstructured":"Jiatao Gu, Yong Wang, Kyunghyun Cho, and Victor O.K. Li. 2019. Improved zero-shot neural machine translation via ignoring spurious correlations. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, 1258\u20131268. DOI:10.18653\/v1\/P19-1121"},{"key":"e_1_3_2_152_2","first-page":"1650","volume-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics","author":"Zhu Changfeng","year":"2020","unstructured":"Changfeng Zhu, Heng Yu, Shanbo Cheng, and Weihua Luo. 2020. Language-aware interlingua for multilingual neural machine translation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 1650\u20131655. DOI:10.18653\/v1\/2020.acl-main.150"},{"key":"e_1_3_2_153_2","doi-asserted-by":"crossref","first-page":"1628","DOI":"10.18653\/v1\/2020.acl-main.148","volume-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics","author":"Zhang Biao","year":"2020","unstructured":"Biao Zhang, Philip Williams, Ivan Titov, and Rico Sennrich. 2020. Improving massively multilingual neural machine translation and zero-shot translation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 1628\u20131639. DOI:10.18653\/v1\/2020.acl-main.148"},{"key":"e_1_3_2_154_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.366"},{"issue":"4","key":"e_1_3_2_155_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3314945","article-title":"Multi-round transfer learning for low-resource NMT using multiple high-resource languages","volume":"18","author":"Maimaiti Mieradilijiang","year":"2019","unstructured":"Mieradilijiang Maimaiti, Yang Liu, Huanbo Luan, and Maosong Sun. 2019. Multi-round transfer learning for low-resource NMT using multiple high-resource languages. 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DOI:10.18653\/V1\/D19-1080"},{"key":"e_1_3_2_158_2","first-page":"7701","volume-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5\u201310, 2020","author":"Aji Alham Fikri","year":"2020","unstructured":"Alham Fikri Aji, Nikolay Bogoychev, Kenneth Heafield, and Rico Sennrich. 2020. In neural machine translation, what does transfer learning transfer?. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5\u201310, 2020. Association for Computational Linguistics, 7701\u20137710. DOI:10.18653\/V1\/2020.ACL-MAIN.688"},{"key":"e_1_3_2_159_2","doi-asserted-by":"crossref","first-page":"1410","DOI":"10.18653\/v1\/D19-1146","volume-title":"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP\u201919)","author":"Dabre Raj","year":"2019","unstructured":"Raj Dabre, Atsushi Fujita, and Chenhui Chu. 2019. Exploiting multilingualism through multistage fine-tuning for low-resource neural machine translation. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP\u201919). 1410\u20131416."},{"issue":"1","key":"e_1_3_2_160_2","doi-asserted-by":"crossref","first-page":"150","DOI":"10.26599\/TST.2020.9010029","article-title":"Enriching the transfer learning with pre-trained lexicon embedding for low-resource neural machine translation","volume":"27","author":"Maimaiti Mieradilijiang","year":"2021","unstructured":"Mieradilijiang Maimaiti, Yang Liu, Huanbo Luan, and Maosong Sun. 2021. Enriching the transfer learning with pre-trained lexicon embedding for low-resource neural machine translation. Tsinghua Science and Technology 27, 1 (2021), 150\u2013163.","journal-title":"Tsinghua Science and Technology"},{"key":"e_1_3_2_161_2","first-page":"128","volume-title":"Proceedings of Machine Translation Summit XVII Volume 1: Research Track, MTSummit 2019, Dublin, Ireland, August 19\u201323, 2019","author":"Imankulova Aizhan","year":"2019","unstructured":"Aizhan Imankulova, Raj Dabre, Atsushi Fujita, and Kenji Imamura. 2019. Exploiting out-of-domain parallel data through multilingual transfer learning for low-resource neural machine translation. In Proceedings of Machine Translation Summit XVII Volume 1: Research Track, MTSummit 2019, Dublin, Ireland, August 19\u201323, 2019. European Association for Machine Translation, 128\u2013139. https:\/\/aclanthology.org\/W19-6613\/"},{"key":"e_1_3_2_162_2","first-page":"4481","volume-title":"Proceedings of the 29th International Conference on Computational Linguistics","author":"Xing Xiaolin","year":"2022","unstructured":"Xiaolin Xing, Yu Hong, Minhan Xu, Jianmin Yao, and Guodong Zhou. 2022. Taking actions separately: A bidirectionally-adaptive transfer learning method for low-resource neural machine translation. In Proceedings of the 29th International Conference on Computational Linguistics. 4481\u20134491."},{"key":"e_1_3_2_163_2","doi-asserted-by":"publisher","unstructured":"Zhaocong Li Xuebo Liu Derek F. Wong Lidia S. Chao and Min Zhang. 2022. ConsistTL: Modeling consistency in transfer learning for low-resource neural machine translation. (2022) 8383\u20138394. DOI:10.18653\/V1\/2022.EMNLP-MAIN.574","DOI":"10.18653\/V1\/2022.EMNLP-MAIN.574"},{"key":"e_1_3_2_164_2","first-page":"1","article-title":"A joint back-translation and transfer learning method for low-resource neural machine translation","volume":"2020","author":"Luo Gong-Xu","year":"2020","unstructured":"Gong-Xu Luo, Ya-Ting Yang, Rui Dong, Yan-Hong Chen, and Wen-Bo Zhang. 2020. A joint back-translation and transfer learning method for low-resource neural machine translation. Mathematical Problems in Engineering 2020 (2020), 1\u201311.","journal-title":"Mathematical Problems in Engineering"},{"key":"e_1_3_2_165_2","doi-asserted-by":"crossref","first-page":"162","DOI":"10.18653\/v1\/2020.acl-srw.22","volume-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop","author":"Goyal Vikrant","year":"2020","unstructured":"Vikrant Goyal, Sourav Kumar, and Dipti Misra Sharma. 2020. Efficient neural machine translation for low-resource languages via exploiting related languages. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop. 162\u2013168."},{"key":"e_1_3_2_166_2","first-page":"2978","volume-title":"Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, Volume 1: Long Papers","author":"Dai Zihang","year":"2019","unstructured":"Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc Viet Le, and Ruslan Salakhutdinov. 2019. Transformer-XL: Attentive language models beyond a fixed-length context. In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, Volume 1: Long Papers. Association for Computational Linguistics, 2978\u20132988. DOI:10.18653\/V1\/P19-1285"},{"key":"e_1_3_2_167_2","article-title":"Explicit sparse transformer: Concentrated attention through explicit selection","volume":"1912","author":"Zhao Guangxiang","year":"2019","unstructured":"Guangxiang Zhao, Junyang Lin, Zhiyuan Zhang, Xuancheng Ren, Qi Su, and Xu Sun. 2019. Explicit sparse transformer: Concentrated attention through explicit selection. CoRR abs\/1912.11637 (2019). arXiv:1912.11637http:\/\/arxiv.org\/abs\/1912.11637","journal-title":"CoRR"},{"key":"e_1_3_2_168_2","article-title":"Longformer: The long-document transformer","volume":"2004","author":"Beltagy Iz","year":"2020","unstructured":"Iz Beltagy, Matthew E. Peters, and Arman Cohan. 2020. Longformer: The long-document transformer. CoRR abs\/2004.05150 (2020). arXiv:2004.05150https:\/\/arxiv.org\/abs\/2004.05150","journal-title":"CoRR"},{"key":"e_1_3_2_169_2","unstructured":"Manzil Zaheer Guru Guruganesh Kumar Avinava Dubey Joshua Ainslie Chris Alberti Santiago Onta\u00f1\u00f3n Philip Pham Anirudh Ravula Qifan Wang Li Yang and Amr Ahmed. 2020. Big bird: Transformers for longer sequences. (2020). https:\/\/proceedings.neurips.cc\/paper\/2020\/hash\/c8512d142a2d849725f31a9a7a361ab9-Abstract.html"},{"key":"e_1_3_2_170_2","first-page":"11106","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"35","author":"Zhou Haoyi","year":"2021","unstructured":"Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li, Hui Xiong, and Wancai Zhang. 2021. Informer: Beyond efficient transformer for long sequence time-series forecasting. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 35. 11106\u201311115."},{"key":"e_1_3_2_171_2","first-page":"410","volume-title":"Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2\u20137, 2018","author":"Song Kai","year":"2018","unstructured":"Kai Song, Yue Zhang, Min Zhang, and Weihua Luo. 2018. Improved English to Russian translation by neural suffix prediction. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2\u20137, 2018, Sheila A. McIlraith and Kilian Q. Weinberger (Eds.). AAAI Press, 410\u2013417. DOI:10.1609\/AAAI.V32I1.11250"},{"key":"e_1_3_2_172_2","doi-asserted-by":"crossref","first-page":"1958","DOI":"10.18653\/v1\/2022.acl-long.138","volume-title":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","author":"Xiao Yanling","year":"2022","unstructured":"Yanling Xiao, Lemao Liu, Guoping Huang, Qu Cui, Shujian Huang, Shuming Shi, and Jiajun Chen. 2022. BiTIIMT: A bilingual text-infilling method for interactive machine translation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 1958\u20131969."},{"key":"e_1_3_2_173_2","article-title":"DeepNet: Scaling transformers to 1,000 layers","author":"Wang Hongyu","year":"2022","unstructured":"Hongyu Wang, Shuming Ma, Li Dong, Shaohan Huang, Dongdong Zhang, and Furu Wei. 2022. DeepNet: Scaling transformers to 1,000 layers. arXiv preprint arXiv:2203.00555 (2022).","journal-title":"arXiv preprint arXiv:2203.00555"},{"key":"e_1_3_2_174_2","first-page":"11712","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"36","author":"Zhang Tong","year":"2022","unstructured":"Tong Zhang, Wei Ye, Baosong Yang, Long Zhang, Xingzhang Ren, Dayiheng Liu, Jinan Sun, Shikun Zhang, Haibo Zhang, and Wen Zhao. 2022. Frequency-aware contrastive learning for neural machine translation. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 36. 11712\u201311720."},{"key":"e_1_3_2_175_2","doi-asserted-by":"publisher","DOI":"10.1016\/J.CSL.2023.101566"},{"key":"e_1_3_2_176_2","first-page":"11431","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"36","author":"Wang Dongqi","year":"2022","unstructured":"Dongqi Wang, Haoran Wei, Zhirui Zhang, Shujian Huang, Jun Xie, and Jiajun Chen. 2022. Non-parametric online learning from human feedback for neural machine translation. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 36. 11431\u201311439."},{"key":"e_1_3_2_177_2","first-page":"3242","volume-title":"Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, Volume 1: Long Papers","author":"Li Xiaoya","year":"2019","unstructured":"Xiaoya Li, Yuxian Meng, Xiaofei Sun, Qinghong Han, Arianna Yuan, and Jiwei Li. 2019. Is word segmentation necessary for deep learning of Chinese representations?. In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, Volume 1: Long Papers. Association for Computational Linguistics, 3242\u20133252. DOI:10.18653\/V1\/P19-1314"},{"key":"e_1_3_2_178_2","first-page":"4295","volume-title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31\u2013November 4, 2018","author":"Cherry Colin","year":"2018","unstructured":"Colin Cherry, George F. Foster, Ankur Bapna, Orhan Firat, and Wolfgang Macherey. 2018. Revisiting character-based neural machine translation with capacity and compression. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31\u2013November 4, 2018. Association for Computational Linguistics, 4295\u20134305. https:\/\/aclanthology.org\/D18-1461\/"},{"key":"e_1_3_2_179_2","first-page":"187","volume-title":"Proceedings of the 3rd Workshop on Neural Generation and Translation@EMNLP-IJCNLP 2019, Hong Kong, November 4, 2019","author":"Ataman Duygu","year":"2019","unstructured":"Duygu Ataman, Orhan Firat, Mattia Antonino Di Gangi, Marcello Federico, and Alexandra Birch. 2019. On the importance of word boundaries in character-level neural machine translation. In Proceedings of the 3rd Workshop on Neural Generation and Translation@EMNLP-IJCNLP 2019, Hong Kong, November 4, 2019, Alexandra Birch, Andrew M. Finch, Hiroaki Hayashi, Ioannis Konstas, Thang Luong, Graham Neubig, Yusuke Oda, and Katsuhito Sudoh (Eds.). Association for Computational Linguistics, 187\u2013193. DOI:10.18653\/V1\/D19-5619"},{"key":"e_1_3_2_180_2","first-page":"1284","volume-title":"Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)","author":"Chen Huadong","year":"2018","unstructured":"Huadong Chen, Shujian Huang, David Chiang, Xinyu Dai, and Jiajun Chen. 2018. Combining character and word information in neural machine translation using a multi-level attention. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). 1284\u20131293."},{"key":"e_1_3_2_181_2","article-title":"Subcharacter Chinese-English neural machine translation with Wubi encoding","author":"Zhang Wei","year":"2019","unstructured":"Wei Zhang, Feifei Lin, Xiaodong Wang, Zhenshuang Liang, and Zhen Huang. 2019. Subcharacter Chinese-English neural machine translation with Wubi encoding. arXiv preprint arXiv:1911.02737 (2019).","journal-title":"arXiv preprint arXiv:1911.02737"},{"key":"e_1_3_2_182_2","doi-asserted-by":"crossref","first-page":"24","DOI":"10.18653\/v1\/W19-5203","volume-title":"Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers)","author":"Currey Anna","year":"2019","unstructured":"Anna Currey and Kenneth Heafield. 2019. Incorporating source syntax into transformer-based neural machine translation. In Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers). 24\u201333."},{"key":"e_1_3_2_183_2","first-page":"1591","volume-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5\u201310, 2020","author":"Gao Yingqiang","year":"2020","unstructured":"Yingqiang Gao, Nikola I. Nikolov, Yuhuang Hu, and Richard H. R. Hahnloser. 2020. Character-level translation with self-attention. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5\u201310, 2020. Association for Computational Linguistics, 1591\u20131604. DOI:10.18653\/V1\/2020.ACL-MAIN.145"},{"key":"e_1_3_2_184_2","first-page":"671","volume-title":"Proceedings of the Third Conference on Machine Translation: Shared Task Papers","author":"Ma Qingsong","year":"2018","unstructured":"Qingsong Ma, Ond\u0159ej Bojar, and Yvette Graham. 2018. Results of the WMT18 metrics shared task: Both characters and embeddings achieve good performance. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers. 671\u2013688."},{"issue":"3","key":"e_1_3_2_185_2","doi-asserted-by":"crossref","first-page":"387","DOI":"10.12677\/CSA.2020.103040","article-title":"Analyzing the problems of vocabulary in Japanese-Chinese neural network machine translation","volume":"10","author":"Luo Wentao","year":"2020","unstructured":"Wentao Luo. 2020. Analyzing the problems of vocabulary in Japanese-Chinese neural network machine translation. Computer Science and Application 10, 3 (2020), 387\u2013397.","journal-title":"Computer Science and Application"},{"key":"e_1_3_2_186_2","first-page":"1293","volume-title":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics","author":"Li Xintong","year":"2019","unstructured":"Xintong Li, Guanlin Li, Lemao Liu, Max Meng, and Shuming Shi. 2019. On the word alignment from neural machine translation. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 1293\u20131303."},{"issue":"7","key":"e_1_3_2_187_2","first-page":"1413","article-title":"Translation quality estimation of Chinese-Vietnamese neural machine translation incorporating linguistic differentiation features","volume":"43","author":"Zou Xiang","year":"2022","unstructured":"Xiang Zou, Junguo Zhu, Shengxiang Gao, Zhengtao Yu, and Fuan Yang. 2022. Translation quality estimation of Chinese-Vietnamese neural machine translation incorporating linguistic differentiation features. Journal of Chinese Computer Systems 43, 7 (2022), 1413\u20131418. 10.20009\/j.cnki.21-1106\/TP.2020-1084","journal-title":"Journal of Chinese Computer Systems"},{"key":"e_1_3_2_188_2","first-page":"8886","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"34","author":"Song Kai","year":"2020","unstructured":"Kai Song, Kun Wang, Heng Yu, Yue Zhang, Zhongqiang Huang, Weihua Luo, Xiangyu Duan, and Min Zhang. 2020. Alignment-enhanced transformer for constraining NMT with pre-specified translations. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 34. 8886\u20138893."},{"key":"e_1_3_2_189_2","first-page":"83","volume-title":"Proceedings of the First Conference on Machine Translation, WMT 2016, colocated with ACL 2016, August 11\u201312, Berlin, Germany","author":"Sennrich Rico","year":"2016","unstructured":"Rico Sennrich and Barry Haddow. 2016. Linguistic input features improve neural machine translation. In Proceedings of the First Conference on Machine Translation, WMT 2016, colocated with ACL 2016, August 11\u201312, Berlin, Germany. The Association for Computer Linguistics, 83\u201391. DOI:10.18653\/V1\/W16-2209"},{"key":"e_1_3_2_190_2","first-page":"2846","volume-title":"Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing","author":"Chen Kehai","year":"2017","unstructured":"Kehai Chen, Rui Wang, Masao Utiyama, Lemao Liu, Akihiro Tamura, Eiichiro Sumita, and Tiejun Zhao. 2017. Neural machine translation with source dependency representation. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. 2846\u20132852."},{"key":"e_1_3_2_191_2","volume-title":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016, August 7\u201312, 2016, Berlin, Germany, Volume 1: Long Papers","author":"Eriguchi Akiko","year":"2016","unstructured":"Akiko Eriguchi, Kazuma Hashimoto, and Yoshimasa Tsuruoka. 2016. Tree-to-sequence attentional neural machine translation. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016, August 7\u201312, 2016, Berlin, Germany, Volume 1: Long Papers. The Association for Computer Linguistics. DOI:10.18653\/V1\/P16-1078"},{"key":"e_1_3_2_192_2","first-page":"1936","volume-title":"Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, July 30\u2013August 4, Volume 1: Long Papers","author":"Chen Huadong","year":"2017","unstructured":"Huadong Chen, Shujian Huang, David Chiang, and Jiajun Chen. 2017. Improved neural machine translation with a syntax-aware encoder and decoder. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, July 30\u2013August 4, Volume 1: Long Papers. Association for Computational Linguistics, 1936\u20131945. DOI:10.18653\/V1\/P17-1177"},{"key":"e_1_3_2_193_2","first-page":"401","volume-title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31\u2013November 4, 2018","author":"Gu Jetic","year":"2018","unstructured":"Jetic Gu, Hassan S. Shavarani, and Anoop Sarkar. 2018. Top-down tree structured decoding with syntactic connections for neural machine translation and parsing. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31\u2013November 4, 2018. Association for Computational Linguistics, 401\u2013413. DOI:10.18653\/V1\/D18-1037"},{"issue":"3","key":"e_1_3_2_194_2","first-page":"923","article-title":"Promoting the knowledge of source syntax in transformer NMT is not needed","volume":"23","author":"Pham Thuong-Hai","year":"2019","unstructured":"Thuong-Hai Pham, Dominik Mach\u00e1\u010dek, and Ond\u0159ej Bojar. 2019. Promoting the knowledge of source syntax in transformer NMT is not needed. 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Springer Nature Singapore, Singapore, 94\u2013102."},{"issue":"4","key":"e_1_3_2_213_2","doi-asserted-by":"crossref","first-page":"175","DOI":"10.3390\/info13040175","article-title":"Chinese-Uyghur bilingual lexicon extraction based on weak supervision","volume":"13","author":"Aysa Anwar","year":"2022","unstructured":"Anwar Aysa, Mijit Ablimit, Hankiz Yilahun, and Askar Hamdulla. 2022. Chinese-Uyghur bilingual lexicon extraction based on weak supervision. Information 13, 4 (2022), 175.","journal-title":"Information"},{"issue":"3","key":"e_1_3_2_214_2","doi-asserted-by":"crossref","first-page":"133","DOI":"10.3390\/info12030133","article-title":"Pre-training on mixed data for low-resource neural machine translation","volume":"12","author":"Zhang Wenbo","year":"2021","unstructured":"Wenbo Zhang, Xiao Li, Yating Yang, and Rui Dong. 2021. Pre-training on mixed data for low-resource neural machine translation. 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Chinese Information Processing Society of China, Harbin, China, 64\u201377. https:\/\/aclanthology.org\/2023.ccl-1.6"},{"key":"e_1_3_2_223_2","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1007\/978-981-15-1721-1_11","volume-title":"Machine Translation","author":"Yang Muyun","year":"2019","unstructured":"Muyun Yang, Xixin Hu, Hao Xiong, Jiayi Wang, Yiliyaer Jiaermuhamaiti, Zhongjun He, Weihua Luo, and Shujian Huang. 2019. CCMT 2019 machine translation evaluation report. In Machine Translation, Shujian Huang and Kevin Knight (Eds.). 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Tibetan-Chinese neural machine translation based on syllable segmentation. In Proceedings of the AMTA 2018 Workshop on Technologies for MT of Low Resource Languages (LoResMT\u201918). 21\u201329."},{"key":"e_1_3_2_234_2","first-page":"1","volume-title":"2021 3rd International Conference on Advanced Information Science and System (AISS\u201921)","author":"Zhou Maoxian","year":"2021","unstructured":"Maoxian Zhou, Jia Secha, and Rangjia Cai. 2021. Research on Tibetan-Chinese neural machine translation integrating syntactic information. In 2021 3rd International Conference on Advanced Information Science and System (AISS\u201921). 1\u20134."},{"key":"e_1_3_2_235_2","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1007\/978-3-030-32381-3_34","volume-title":"Chinese Computational Linguistics: 18th China National Conference, CCL 2019, Kunming, China, October 18\u201320, 2019, Proceedings","author":"Duanzhu Sangjie","year":"2019","unstructured":"Sangjie Duanzhu, Cizhen Jiacuo, Rou Te, Sanzhi Jia, and Cairang Jia. 2019. An end-to-end method for data filtering on Tibetan-Chinese parallel corpus via negative sampling. In Chinese Computational Linguistics: 18th China National Conference, CCL 2019, Kunming, China, October 18\u201320, 2019, Proceedings. Springer, 414\u2013423."},{"key":"e_1_3_2_236_2","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1007\/978-981-99-7894-6_3","volume-title":"China Conference on Machine Translation","author":"Gyatso Kalzang","year":"2023","unstructured":"Kalzang Gyatso, Peizhuo Liu, Yi Jing, Yinqiao Li, Nyima Tashi, Tong Xiao, and Jingbo Zhu. 2023. CCMT2023 Tibetan-Chinese machine translation evaluation technical report. In China Conference on Machine Translation. Springer, 28\u201336."},{"key":"e_1_3_2_237_2","doi-asserted-by":"publisher","DOI":"10.1145\/3431727"},{"key":"e_1_3_2_238_2","article-title":"Chinese-Japanese unsupervised neural machine translation using sub-character level information","author":"Zhang Longtu","year":"2019","unstructured":"Longtu Zhang and Mamoru Komachi. 2019. 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Association for Computational Linguistics, 170\u2013177. https:\/\/aclanthology.org\/2020.wat-1.21\/"},{"key":"e_1_3_2_244_2","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1109\/IALP.2017.8300610","volume-title":"2017 International Conference on Asian Language Processing (IALP\u201917)","author":"Zhang Jinyi","year":"2017","unstructured":"Jinyi Zhang and Tadahiro Matsumoto. 2017. Japanese-Chinese machine translation for the Japanese case particle \u201cde\u201d. In 2017 International Conference on Asian Language Processing (IALP\u201917). 330\u2013333. DOI:10.1109\/IALP.2017.8300610"},{"key":"e_1_3_2_245_2","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1109\/IALP.2017.8300572","volume-title":"2017 International Conference on Asian Language Processing (IALP\u201917)","author":"Zhang Jinyi","year":"2017","unstructured":"Jinyi Zhang and Tadahiro Matsumoto. 2017. 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A Study on Japanese-Chinese Machine Translation \u2013 Centering on the Rules for TORITATE Expression and Negative Expression. Ph.D. Dissertation. Gifu University."},{"issue":"4","key":"e_1_3_2_248_2","article-title":"Cooperative research on Chinese-Japanese machine translation for S&T documents","volume":"3","author":"Zhao ZhiYun","year":"2017","unstructured":"ZhiYun Zhao, ChongDe Shi, YanQing He, YingFan Gao, and ChangQing Yao. 2017. Cooperative research on Chinese-Japanese machine translation for S&T documents. 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European Language Resources Association (ELRA), 642\u2013647. http:\/\/www.lrec-conf.org\/proceedings\/lrec2014\/summaries\/21.html"},{"issue":"10","key":"e_1_3_2_251_2","doi-asserted-by":"crossref","first-page":"2036","DOI":"10.3390\/app9102036","article-title":"Corpus augmentation for neural machine translation with Chinese-Japanese parallel corpora","volume":"9","author":"Zhang Jinyi","year":"2019","unstructured":"Jinyi Zhang and Tadahiro Matsumoto. 2019. Corpus augmentation for neural machine translation with Chinese-Japanese parallel corpora. Applied Sciences 9, 10 (2019), 2036.","journal-title":"Applied Sciences"},{"key":"e_1_3_2_252_2","doi-asserted-by":"publisher","unstructured":"Boliang Zhang Ajay Nagesh and Kevin Knight. 2020. Parallel Corpus filtering via pre-trained language models. (2020) 8545\u20138554. DOI:10.18653\/V1\/2020.ACL-MAIN.756","DOI":"10.18653\/V1\/2020.ACL-MAIN.756"},{"issue":"9","key":"e_1_3_2_253_2","first-page":"927","article-title":"Chinese-English-Burmese neural machine translation based on multilingual joint training","volume":"61","author":"Man Zhibo","year":"2021","unstructured":"Zhibo Man, Cunli Mao, Zhengtao Yu, Xunyu Li, Shengxiang Gao, and Junguo Zhu. 2021. Chinese-English-Burmese neural machine translation based on multilingual joint training. Journal of Tsinghua University (Science and Technology) 61, 9 (2021), 927\u2013935.","journal-title":"Journal of Tsinghua University (Science and Technology)"},{"key":"e_1_3_2_254_2","volume-title":"Research on the Construction Method of Chinese-Myanmar Parallel Corpus Based on Pivot Language","author":"Zhang Shaoning","year":"2019","unstructured":"Shaoning Zhang. 2019. Research on the Construction Method of Chinese-Myanmar Parallel Corpus Based on Pivot Language. Master\u2019s Thesis. 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Kunming University of Science and Technology."},{"issue":"1","key":"e_1_3_2_257_2","first-page":"118","article-title":"Chinese-Myanmar parallel sentence pairs generation method based on semantic difference","volume":"32","author":"Yu Zhiqiang","year":"2023","unstructured":"Zhiqiang Yu, Yonghua Wen, Minghu Gao, and Man Yang. 2023. Chinese-Myanmar parallel sentence pairs generation method based on semantic difference. Journal of Yunnan University of Nationalities: Natural Sciences Edition 32, 1 (2023), 118\u2013123.","journal-title":"Journal of Yunnan University of Nationalities: Natural Sciences Edition"},{"issue":"1","key":"e_1_3_2_258_2","first-page":"1","article-title":"Towards Burmese (Myanmar) morphological analysis: Syllable-based tokenization and part-of-speech tagging","volume":"19","author":"Ding Chenchen","year":"2019","unstructured":"Chenchen Ding, Hnin Thu Zar Aye, Win Pa Pa, Khin Thandar Nwet, Khin Mar Soe, Masao Utiyama, and Eiichiro Sumita. 2019. 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In Proceedings of the 20th Chinese National Conference on Computational Linguistics. 35\u201345."},{"key":"e_1_3_2_263_2","first-page":"1723","volume-title":"Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL 2015, July 26\u201331, 2015, Beijing, China, Volume 1: Long Papers","author":"Dong Daxiang","year":"2015","unstructured":"Daxiang Dong, Hua Wu, Wei He, Dianhai Yu, and Haifeng Wang. 2015. Multi-task learning for multiple language translation. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL 2015, July 26\u201331, 2015, Beijing, China, Volume 1: Long Papers. The Association for Computer Linguistics, 1723\u20131732. DOI:10.3115\/V1\/P15-1166"},{"key":"e_1_3_2_264_2","unstructured":"Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2015. Neural machine translation by jointly learning to align and translate. (2015). http:\/\/arxiv.org\/abs\/1409.0473"},{"issue":"990","key":"e_1_3_2_265_2","article-title":"Thai-Chinese neural machine translation method based on dependency distance penalty","volume":"55","author":"Zhang Hongtao","year":"2022","unstructured":"Hongtao Zhang, Yonghua Wen, and Jian Wang. 2022. Thai-Chinese neural machine translation method based on dependency distance penalty. Communications Technology 55, 990-997 (2022).","journal-title":"Communications Technology"},{"key":"e_1_3_2_266_2","volume-title":"Research on Thai-Chinese Machine Translation Optimization Method under Low Resource Conditions","author":"Zhang Yihan","year":"2021","unstructured":"Yihan Zhang. 2021. Research on Thai-Chinese Machine Translation Optimization Method under Low Resource Conditions. Master\u2019s Thesis. Yunnan University."},{"issue":"12","key":"e_1_3_2_267_2","first-page":"3679","article-title":"Neural machine translation integrating bidirectional-dependency self-attention mechanism","volume":"42","author":"Li Zhijin","year":"2022","unstructured":"Zhijin Li, Hua Lai, Yonghua Wen, and Shengxiang Gao. 2022. Neural machine translation integrating bidirectional-dependency self-attention mechanism. Journal of Computer Applications 42, 12 (2022), 3679.","journal-title":"Journal of Computer Applications"},{"key":"e_1_3_2_268_2","volume-title":"A Study on the Method of Computing Sentence Similarity between Chinese and Thai Languages Based on Word Embedding","author":"Feng Yinhan","year":"2019","unstructured":"Yinhan Feng. 2019. A Study on the Method of Computing Sentence Similarity between Chinese and Thai Languages Based on Word Embedding. Master\u2019s Thesis. Kunming University of Science and Technology."},{"issue":"2","key":"e_1_3_2_269_2","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1007\/s10579-021-09536-6","article-title":"A large English\u2013Thai parallel corpus from the web and machine-generated text","volume":"56","author":"Lowphansirikul Lalita","year":"2022","unstructured":"Lalita Lowphansirikul, Charin Polpanumas, Attapol T. Rutherford, and Sarana Nutanong. 2022. A large English\u2013Thai parallel corpus from the web and machine-generated text. Language Resources and Evaluation 56, 2 (2022), 477\u2013499.","journal-title":"Language Resources and Evaluation"},{"issue":"41","key":"e_1_3_2_270_2","article-title":"Construction method of parallel corpus for minority language machine translation","volume":"49","author":"Liu Yan","year":"2022","unstructured":"Yan Liu and Deyi Xiong. 2022. Construction method of parallel corpus for minority language machine translation. Computer Science 49, 41-46 (2022).","journal-title":"Computer Science"},{"key":"e_1_3_2_271_2","first-page":"1","volume-title":"Machine Translation: 16th China Conference, CCMT 2020, Hohhot, China, October 10\u201312, 2020, Revised Selected Papers 16","author":"Yu Zhiqiang","year":"2020","unstructured":"Zhiqiang Yu, Zhengtao Yu, Yuxin Huang, Junjun Guo, Zhenhan Wang, and Zhibo Man. 2020. Transfer learning for Chinese-Lao neural machine translation with linguistic similarity. In Machine Translation: 16th China Conference, CCMT 2020, Hohhot, China, October 10\u201312, 2020, Revised Selected Papers 16. Springer, 1\u201310."},{"key":"e_1_3_2_272_2","article-title":"TURJUMAN: A public toolkit for neural Arabic machine translation","author":"Nagoudi El Moatez Billah","year":"2022","unstructured":"El Moatez Billah Nagoudi, AbdelRahim Elmadany, and Muhammad Abdul-Mageed. 2022. TURJUMAN: A public toolkit for neural Arabic machine translation. arXiv preprint arXiv:2206.03933 (2022).","journal-title":"arXiv preprint arXiv:2206.03933"},{"key":"e_1_3_2_273_2","article-title":"Domain adaptation approach for low resource Russian-Chinese machine translation task","author":"Liu Huan","year":"2022","unstructured":"Huan Liu, Junpeng Liu, Kaiyu Huang, and Degen Huang. 2022. Domain adaptation approach for low resource Russian-Chinese machine translation task. Journal of Xiamen University (Natural Science) (2022).","journal-title":"Journal of Xiamen University (Natural Science)"},{"issue":"11","key":"e_1_3_2_274_2","first-page":"3145","article-title":"Neural machine translation corpus expansion method based on language similarity mining","volume":"41","year":"2021","unstructured":"Can Li, Yating Yang, Yupeng Ma, and Rui Dong. 2021. Neural machine translation corpus expansion method based on language similarity mining. Journal of Computer Applications 41, 11 (2021), 3145.","journal-title":"Journal of Computer Applications"},{"key":"e_1_3_2_275_2","first-page":"310","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Liu Guangfeng","year":"2022","unstructured":"Guangfeng Liu, Qinpei Zhu, Xingyu Chen, Renjie Feng, Jianxin Ren, Renshou Wu, Qingliang Miao, Rui Wang, and Kai Yu. 2022. The AISP-SJTU translation system for WMT 2022. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 310\u2013317."},{"key":"e_1_3_2_276_2","first-page":"233","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Alabi Jesujoba","year":"2022","unstructured":"Jesujoba Alabi, Lydia Nishimwe, Benjamin Muller, Camille Rey, Beno\u00eet Sagot, and Rachel Bawden. 2022. Inria-ALMAnaCH at WMT 2022: Does transcription help cross-script machine translation?. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 233\u2013243."},{"key":"e_1_3_2_277_2","first-page":"326","volume-title":"Proceedings of the Seventh Conference on Machine Translation, WMT 2022, Abu Dhabi, United Arab Emirates (Hybrid), December 7\u20138, 2022","author":"Nowakowski Artur","year":"2022","unstructured":"Artur Nowakowski, Gabriela Palka, Kamil Guttmann, and Mikolaj Pokrywka. 2022. Adam Mickiewicz University at WMT 2022: NER-assisted and quality-aware neural machine translation. In Proceedings of the Seventh Conference on Machine Translation, WMT 2022, Abu Dhabi, United Arab Emirates (Hybrid), December 7\u20138, 2022. Association for Computational Linguistics, 326\u2013334. https:\/\/aclanthology.org\/2022.wmt-1.26"},{"key":"e_1_3_2_278_2","first-page":"358","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Roussis Dimitrios","year":"2022","unstructured":"Dimitrios Roussis and Vassilis Papavassiliou. 2022. The ARC-NKUA submission for the English-Ukrainian general machine translation shared task at WMT22. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 358\u2013365."},{"key":"e_1_3_2_279_2","first-page":"280","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Jon Josef","year":"2022","unstructured":"Josef Jon, Martin Popel, and Ond\u0159ej Bojar. 2022. CUNI-Bergamot submission at WMT22 general translation task. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 280\u2013289."},{"key":"e_1_3_2_280_2","first-page":"352","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Popel Martin","year":"2022","unstructured":"Martin Popel, Jind\u0159ich Libovick\u00fd, and Jind\u0159ich Helcl. 2022. CUNI systems for the WMT 22 Czech-Ukrainian translation task. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (Hybrid), 352\u2013357. https:\/\/aclanthology.org\/2022.wmt-1.30"},{"key":"e_1_3_2_281_2","first-page":"428","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Zong Hao","year":"2022","unstructured":"Hao Zong and Chao Bei. 2022. GTCOM neural machine translation systems for WMT22. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 428\u2013431."},{"key":"e_1_3_2_282_2","first-page":"403","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Wei Daimeng","year":"2022","unstructured":"Daimeng Wei, Zhiqiang Rao, Zhanglin Wu, Shaojun Li, Yuanchang Luo, Yuhao Xie, Xiaoyu Chen, Hengchao Shang, Zongyao Li, Zhengzhe Yu, Jinlong Yang, Miaomiao Ma, Lizhi Lei, Hao Yang, and Ying Qin. 2022. HW-TSC\u2019s submissions to the WMT 2022 general machine translation shared task. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (Hybrid), 403\u2013410. https:\/\/aclanthology.org\/2022.wmt-1.36"},{"key":"e_1_3_2_283_2","first-page":"411","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Zan Changtong","year":"2022","unstructured":"Changtong Zan, Keqin Peng, Liang Ding, Baopu Qiu, Boan Liu, Shwai He, Qingyu Lu, Zheng Zhang, Chuang Liu, Weifeng Liu, Yibing Zhan, and Dacheng Tao. 2022. Vega-MT: The JD explore academy machine translation system for WMT22. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (Hybrid), 411\u2013422. https:\/\/aclanthology.org\/2022.wmt-1.37"},{"key":"e_1_3_2_284_2","first-page":"290","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Kalkar Shivam","year":"2022","unstructured":"Shivam Kalkar, Yoko Matsuzaki, and Ben Li. 2022. KYB general machine translation systems for WMT22. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 290\u2013294."},{"key":"e_1_3_2_285_2","first-page":"335","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Malli Marilena","year":"2022","unstructured":"Marilena Malli and George Tambouratzis. 2022. Evaluating corpus cleanup methods in the WMT\u201922 news translation task. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 335\u2013341."},{"key":"e_1_3_2_286_2","first-page":"268","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Han Bing","year":"2022","unstructured":"Bing Han, Yangjian Wu, Gang Hu, and Qiulin Chen. 2022. Lan-Bridge MT\u2019s participation in the WMT 2022 general translation shared task. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (Hybrid), 268\u2013274. https:\/\/aclanthology.org\/2022.wmt-1.19"},{"key":"e_1_3_2_287_2","first-page":"423","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Zeng Hui","year":"2022","unstructured":"Hui Zeng. 2022. No domain left behind. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (Hybrid), 423\u2013427. https:\/\/aclanthology.org\/2022.wmt-1.38"},{"key":"e_1_3_2_288_2","doi-asserted-by":"crossref","first-page":"508","DOI":"10.18653\/v1\/2022.acl-short.55","volume-title":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","author":"Rikters Mat\u012bss","year":"2022","unstructured":"Mat\u012bss Rikters, Marili Tomingas, Tuuli Tuisk, Valts Ern\u0161treits, and Mark Fishel. 2022. Machine translation for Livonian: Catering to 20 speakers. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). 508\u2013514."},{"key":"e_1_3_2_289_2","first-page":"244","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Deguchi Hiroyuki","year":"2022","unstructured":"Hiroyuki Deguchi, Kenji Imamura, Masahiro Kaneko, Yuto Nishida, Yusuke Sakai, Justin Vasselli, Huy-Hien Vu, and Taro Watanabe. 2022. NAIST-NICT-TIT WMT22 general MT task submission. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 244\u2013250."},{"key":"e_1_3_2_290_2","first-page":"318","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Morishita Makoto","year":"2022","unstructured":"Makoto Morishita, Keito Kudo, Yui Oka, Katsuki Chousa, Shun Kiyono, Sho Takase, and Jun Suzuki. 2022. NT5 at WMT 2022 general translation task. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 318\u2013325."},{"key":"e_1_3_2_291_2","unstructured":"Weiqiao Shan Zhiquan Cao Yuchen Han Siming Wu Yimin Hu Jie Wang Yi Zhang Baoyu Hou Hang Cao Chenghao Gao Xiaowen Liu Tong Xiao Anxiang Ma and Jingbo Zhu. 2022. The NiuTrans machine translation systems for WMT22. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922) 366\u2013374."},{"key":"e_1_3_2_292_2","first-page":"342","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Molchanov Alexander","year":"2022","unstructured":"Alexander Molchanov, Vladislav Kovalenko, and Natalia Makhamalkina. 2022. PROMT systems for WMT22 general translation task. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 342\u2013345."},{"key":"e_1_3_2_293_2","first-page":"251","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Dobrowolski Adam","year":"2022","unstructured":"Adam Dobrowolski, Mateusz Klimaszewski, Adam My\u015bliwy, Marcin Szyma\u0144ski, Jakub Kowalski, Kornelia Szypu\u0142a, Pawe\u0142 Przew\u0142ocki, and Pawe\u0142 Przybysz. 2022. Samsung R&D Institute Poland participation in WMT 2022. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 251\u2013259."},{"key":"e_1_3_2_294_2","first-page":"260","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"He Zhiwei","year":"2022","unstructured":"Zhiwei He, Xing Wang, Zhaopeng Tu, Shuming Shi, and Rui Wang. 2022. Tencent AI Lab - Shanghai Jiao Tong University low-resource translation system for the WMT22 translation task. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (Hybrid), 260\u2013267. https:\/\/aclanthology.org\/2022.wmt-1.18"},{"key":"e_1_3_2_295_2","first-page":"375","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Tars Maali","year":"2022","unstructured":"Maali Tars, Taido Purason, and Andre T\u00e4ttar. 2022. Teaching unseen low-resource languages to large translation models. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 375\u2013380."},{"key":"e_1_3_2_296_2","first-page":"346","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Oravecz Csaba","year":"2022","unstructured":"Csaba Oravecz, Katina Bontcheva, David Kolovratn\u00edk, Bogomil Kovachev, and Christopher Scott. 2022. eTranslation\u2019s submissions to the WMT22 general machine translation task. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). 346\u2013351."},{"key":"e_1_3_2_297_2","first-page":"275","volume-title":"Proceedings of the Seventh Conference on Machine Translation (WMT\u201922)","author":"Jin Chang","year":"2022","unstructured":"Chang Jin, Tingxun Shi, Zhengshan Xue, and Xiaodong Lin. 2022. Manifold\u2019s English-Chinese system at WMT22 general MT task. In Proceedings of the Seventh Conference on Machine Translation (WMT\u201922). Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (Hybrid), 275\u2013279. https:\/\/aclanthology.org\/2022.wmt-1.20"},{"key":"e_1_3_2_298_2","first-page":"166","volume-title":"Proceedings of the Eighth Conference on Machine Translation, WMT 2023, Singapore, December 6\u20137, 2023","author":"Wu Yangjian","year":"2023","unstructured":"Yangjian Wu and Gang Hu. 2023. Exploring prompt engineering with GPT language models for document-level machine translation: Insights and findings. In Proceedings of the Eighth Conference on Machine Translation, WMT 2023, Singapore, December 6\u20137, 2023, Philipp Koehn, Barry Haddon, Tom Kocmi, and Christof Monz (Eds.). Association for Computational Linguistics, 166\u2013169. DOI:10.18653\/V1\/2023.WMT-1.15"},{"key":"e_1_3_2_299_2","first-page":"170","volume-title":"Proceedings of the Eighth Conference on Machine Translation, WMT 2023, Singapore, December 6\u20137, 2023","author":"Wu Zhanglin","year":"2023","unstructured":"Zhanglin Wu, Daimeng Wei, Zongyao Li, Zhengzhe Yu, Shaojun Li, Xiaoyu Chen, Hengchao Shang, Jiaxin Guo, Yuhao Xie, Lizhi Lei, Hao Yang, and Yanfei Jiang. 2023. Treating general MT shared task as a multi-domain adaptation problem: HW-TSC\u2019s submission to the WMT23 general MT shared task. In Proceedings of the Eighth Conference on Machine Translation, WMT 2023, Singapore, December 6\u20137, 2023, Philipp Koehn, Barry Haddon, Tom Kocmi, and Christof Monz (Eds.). 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In Proceedings of the Eighth Conference on Machine Translation, WMT 2023, Singapore, December 6\u20137, 2023, Philipp Koehn, Barry Haddon, Tom Kocmi, and Christof Monz (Eds.). Association for Computational Linguistics, 143\u2013149. DOI:10.18653\/V1\/2023.WMT-1.11"},{"key":"e_1_3_2_302_2","first-page":"181","volume-title":"Proceedings of the Eighth Conference on Machine Translation, WMT 2023, Singapore, December 6\u20137, 2023","author":"Zeng Hui","year":"2023","unstructured":"Hui Zeng. 2023. Achieving state-of-the-art multilingual translation model with minimal data and parameters. In Proceedings of the Eighth Conference on Machine Translation, WMT 2023, Singapore, December 6\u20137, 2023, Philipp Koehn, Barry Haddon, Tom Kocmi, and Christof Monz (Eds.). Association for Computational Linguistics, 181\u2013186. 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WSA: A unified framework for word and sentence autocompletion in interactive machine translation. In Machine Translation, Yang Feng and Chong Feng (Eds.). Springer Nature Singapore, Singapore, 81\u201393."},{"key":"e_1_3_2_319_2","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/978-981-99-7894-6_6","volume-title":"Machine Translation","author":"Zhang Rui","year":"2023","unstructured":"Rui Zhang, Jinghao Yuan, Hui Huang, Muyun Yang, and Tiejun Zhao. 2023. HIT-MI &T Lab\u2019s submission to CCMT 2023 automatic post-editing task. In Machine Translation, Yang Feng and Chong Feng (Eds.). Springer Nature Singapore, Singapore, 57\u201368."},{"key":"e_1_3_2_320_2","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1007\/978-981-99-7894-6_10","volume-title":"Machine Translation","author":"Zhang Zhiyang","year":"2023","unstructured":"Zhiyang Zhang, Yaping Zhang, Lu Xiang, Yang Zhao, Yu Zhou, and Chengqing Zong. 2023. 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Association for Machine Translation in the Americas, Boston, MA, USA, 193\u2013199. https:\/\/aclanthology.org\/W18-1819"},{"key":"e_1_3_2_330_2","doi-asserted-by":"publisher","DOI":"10.1016\/J.AIOPEN.2021.06.001"},{"key":"e_1_3_2_331_2","first-page":"12719","volume-title":"Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2\u20139, 2021","author":"Cui Qu","year":"2021","unstructured":"Qu Cui, Shujian Huang, Jiahuan Li, Xiang Geng, Zaixiang Zheng, Guoping Huang, and Jiajun Chen. 2021. DirectQE: Direct pretraining for machine translation quality estimation. 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