{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T13:20:16Z","timestamp":1768569616125,"version":"3.49.0"},"reference-count":116,"publisher":"Association for Computing Machinery (ACM)","issue":"5","license":[{"start":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T00:00:00Z","timestamp":1664496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61671064, 61732005"],"award-info":[{"award-number":["61671064, 61732005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2022,9,30]]},"abstract":"<jats:p>Neural Machine Translation (NMT) brings promising improvements in translation quality, but until recently, these models rely on large-scale parallel corpora. As such corpora only exist on a handful of language pairs, the translation performance is far from the desired effect in the majority of low-resource languages. Thus, developing low-resource language translation techniques is crucial and it has become a popular research field in neural machine translation. In this article, we make an overall review of existing deep learning techniques in low-resource NMT. We first show the research status as well as some widely used low-resource datasets. Then, we categorize the existing methods and show some representative works detailedly. Finally, we summarize the common characters among them and outline the future directions in this field.<\/jats:p>","DOI":"10.1145\/3524300","type":"journal-article","created":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T21:26:58Z","timestamp":1647379618000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":17,"title":["Low-resource Neural Machine Translation: Methods and Trends"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3436-7575","authenticated-orcid":false,"given":"Shumin","family":"Shi","sequence":"first","affiliation":[{"name":"School of Computer Scienceand Technology, Beijing Institute of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6413-5180","authenticated-orcid":false,"given":"Xing","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Scienceand Technology, Beijing Institute of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3437-0099","authenticated-orcid":false,"given":"Rihai","family":"Su","sequence":"additional","affiliation":[{"name":"School of Computer Scienceand Technology, Beijing Institute of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0320-7520","authenticated-orcid":false,"given":"Heyan","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Scienceand Technology, Beijing Institute of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,11,15]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1042"},{"key":"e_1_3_2_3_2","article-title":"An effective approach to unsupervised machine translation","author":"Artetxe Mikel","year":"2019","unstructured":"Mikel Artetxe, Gorka Labaka, and Eneko Agirre. 2019. An effective approach to unsupervised machine translation. arXiv preprint arXiv:1902.01313 (2019).","journal-title":"arXiv preprint arXiv:1902.01313"},{"key":"e_1_3_2_4_2","article-title":"Translation artifacts in cross-lingual transfer learning","author":"Artetxe Mikel","year":"2020","unstructured":"Mikel Artetxe, Gorka Labaka, and Eneko Agirre. 2020. Translation artifacts in cross-lingual transfer learning. arXiv preprint arXiv:2004.04721 (2020).","journal-title":"arXiv preprint arXiv:2004.04721"},{"key":"e_1_3_2_5_2","article-title":"Unsupervised neural machine translation","author":"Artetxe Mikel","year":"2017","unstructured":"Mikel Artetxe, Gorka Labaka, Eneko Agirre, and Kyunghyun Cho. 2017. Unsupervised neural machine translation. arXiv preprint arXiv:1710.11041 (2017).","journal-title":"arXiv preprint arXiv:1710.11041"},{"key":"e_1_3_2_6_2","article-title":"Neural machine translation by jointly learning to align and translate","author":"Bahdanau Dzmitry","year":"2014","unstructured":"Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014).","journal-title":"arXiv preprint arXiv:1409.0473"},{"key":"e_1_3_2_7_2","first-page":"65","volume-title":"Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and\/or Summarization","author":"Banerjee Satanjeev","year":"2005","unstructured":"Satanjeev Banerjee and Alon Lavie. 2005. METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and\/or Summarization. 65\u201372."},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.5555\/1626431.1626468"},{"key":"e_1_3_2_9_2","first-page":"330","volume-title":"Proceedings of the 6th Workshop on Statistical Machine Translation","author":"Bojar Ond\u0159ej","year":"2011","unstructured":"Ond\u0159ej Bojar and Ale\u0161 Tamchyna. 2011. Improving translation model by monolingual data. In Proceedings of the 6th Workshop on Statistical Machine Translation. 330\u2013336."},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.5555\/972470.972474"},{"key":"e_1_3_2_11_2","article-title":"Enhancing machine translation with dependency-aware self-attention","author":"Bugliarello Emanuele","year":"2019","unstructured":"Emanuele Bugliarello and Naoaki Okazaki. 2019. Enhancing machine translation with dependency-aware self-attention. arXiv preprint arXiv:1909.03149 (2019).","journal-title":"arXiv preprint arXiv:1909.03149"},{"key":"e_1_3_2_12_2","unstructured":"Jaime G. Carbonell Steve Klein David Miller Mike Steinbaum Tomer Grassiany and Jochen Frey. 2006. Context-based machine translation. In Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers 19\u201328."},{"key":"e_1_3_2_13_2","article-title":"Tagged back-translation","author":"Caswell Isaac","year":"2019","unstructured":"Isaac Caswell, Ciprian Chelba, and David Grangier. 2019. Tagged back-translation. arXiv preprint arXiv:1906.06442 (2019).","journal-title":"arXiv preprint arXiv:1906.06442"},{"key":"e_1_3_2_14_2","article-title":"A teacher-student framework for zero-resource neural machine translation","author":"Chen Yun","year":"2017","unstructured":"Yun Chen, Yang Liu, Yong Cheng, and Victor O. K. Li. 2017. A teacher-student framework for zero-resource neural machine translation. arXiv preprint arXiv:1705.00753 (2017).","journal-title":"arXiv preprint arXiv:1705.00753"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11976"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-32-9748-7_4"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-32-9748-7_3"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.3115\/1219840.1219873"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3390298"},{"key":"e_1_3_2_20_2","article-title":"Reusing a pretrained language model on languages with limited corpora for unsupervised NMT","author":"Chronopoulou Alexandra","year":"2020","unstructured":"Alexandra Chronopoulou, Dario Stojanovski, and Alexander Fraser. 2020. Reusing a pretrained language model on languages with limited corpora for unsupervised NMT. arXiv preprint arXiv:2009.07610 (2020).","journal-title":"arXiv preprint arXiv:2009.07610"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.3115\/1219840.1219906"},{"key":"e_1_3_2_22_2","article-title":"Explaining and generalizing back-translation through wake-sleep","author":"Cotterell Ryan","year":"2018","unstructured":"Ryan Cotterell and Julia Kreutzer. 2018. Explaining and generalizing back-translation through wake-sleep. arXiv preprint arXiv:1806.04402 (2018).","journal-title":"arXiv preprint arXiv:1806.04402"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W19-5203"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W17-4715"},{"key":"e_1_3_2_25_2","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018).","journal-title":"arXiv preprint arXiv:1810.04805"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.5555\/2390948.2390982"},{"key":"e_1_3_2_27_2","article-title":"Understanding back-translation at scale","author":"Edunov Sergey","year":"2018","unstructured":"Sergey Edunov, Myle Ott, Michael Auli, and David Grangier. 2018. Understanding back-translation at scale. arXiv preprint arXiv:1808.09381 (2018).","journal-title":"arXiv preprint arXiv:1808.09381"},{"key":"e_1_3_2_28_2","first-page":"412","volume-title":"Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","author":"Kholy Ahmed El","year":"2013","unstructured":"Ahmed El Kholy, Nizar Habash, Gregor Leusch, Evgeny Matusov, and Hassan Sawaf. 2013. Language independent connectivity strength features for phrase pivot statistical machine translation. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). 412\u2013418."},{"key":"e_1_3_2_29_2","article-title":"Data augmentation for low-resource neural machine translation","author":"Fadaee Marzieh","year":"2017","unstructured":"Marzieh Fadaee, Arianna Bisazza, and Christof Monz. 2017. Data augmentation for low-resource neural machine translation. arXiv preprint arXiv:1705.00440 (2017).","journal-title":"arXiv preprint arXiv:1705.00440"},{"key":"e_1_3_2_30_2","article-title":"Back-translation sampling by targeting difficult words in neural machine translation","author":"Fadaee Marzieh","year":"2018","unstructured":"Marzieh Fadaee and Christof Monz. 2018. Back-translation sampling by targeting difficult words in neural machine translation. arXiv preprint arXiv:1808.09006 (2018).","journal-title":"arXiv preprint arXiv:1808.09006"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W17-4713"},{"key":"e_1_3_2_32_2","article-title":"Zero-resource translation with multi-lingual neural machine translation","author":"Firat Orhan","year":"2016","unstructured":"Orhan Firat, Baskaran Sankaran, Yaser Al-Onaizan, Fatos T. Yarman Vural, and Kyunghyun Cho. 2016. Zero-resource translation with multi-lingual neural machine translation. arXiv preprint arXiv:1606.04164 (2016).","journal-title":"arXiv preprint arXiv:1606.04164"},{"key":"e_1_3_2_33_2","first-page":"1019","article-title":"A theoretically grounded application of dropout in recurrent neural networks","volume":"29","author":"Gal Yarin","year":"2016","unstructured":"Yarin Gal and Zoubin Ghahramani. 2016. A theoretically grounded application of dropout in recurrent neural networks. Adv. Neural Inf. Process. Syst. 29 (2016), 1019\u20131027.","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.5555\/2946645.2946704"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1555"},{"key":"e_1_3_2_36_2","article-title":"A survey of methods to leverage monolingual data in low-resource neural machine translation","author":"Gibadullin Ilshat","year":"2019","unstructured":"Ilshat Gibadullin, Aidar Valeev, Albina Khusainova, and Adil Khan. 2019. A survey of methods to leverage monolingual data in low-resource neural machine translation. arXiv preprint arXiv:1910.00373 (2019).","journal-title":"arXiv preprint arXiv:1910.00373"},{"key":"e_1_3_2_37_2","article-title":"Universal neural machine translation for extremely low resource languages","author":"Gu Jiatao","year":"2018","unstructured":"Jiatao Gu, Hany Hassan, Jacob Devlin, and Victor O. K. Li. 2018. Universal neural machine translation for extremely low resource languages. arXiv preprint arXiv:1802.05368 (2018).","journal-title":"arXiv preprint arXiv:1802.05368"},{"key":"e_1_3_2_38_2","article-title":"Meta-learning for low-resource neural machine translation","author":"Gu Jiatao","year":"2018","unstructured":"Jiatao Gu, Yong Wang, Yun Chen, Kyunghyun Cho, and Victor O. K. Li. 2018. Meta-learning for low-resource neural machine translation. arXiv preprint arXiv:1808.08437 (2018).","journal-title":"arXiv preprint arXiv:1808.08437"},{"key":"e_1_3_2_39_2","article-title":"On using monolingual corpora in neural machine translation","author":"Gulcehre Caglar","year":"2015","unstructured":"Caglar Gulcehre, Orhan Firat, Kelvin Xu, Kyunghyun Cho, Loic Barrault, Huei-Chi Lin, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2015. On using monolingual corpora in neural machine translation. arXiv preprint arXiv:1503.03535 (2015).","journal-title":"arXiv preprint arXiv:1503.03535"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013723"},{"key":"e_1_3_2_41_2","article-title":"The FLoRes evaluation datasets for low-resource machine translation: Nepali-English and Sinhala-English","author":"Guzm\u00e1n Francisco","year":"2019","unstructured":"Francisco Guzm\u00e1n, Peng-Jen Chen, Myle Ott, Juan Pino, Guillaume Lample, Philipp Koehn, Vishrav Chaudhary, and Marc\u2019Aurelio Ranzato. 2019. The FLoRes evaluation datasets for low-resource machine translation: Nepali-English and Sinhala-English. arXiv preprint arXiv:1902.01382 (2019).","journal-title":"arXiv preprint arXiv:1902.01382"},{"key":"e_1_3_2_42_2","first-page":"820","article-title":"Dual learning for machine translation","volume":"29","author":"He Di","year":"2016","unstructured":"Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, and Wei-Ying Ma. 2016. Dual learning for machine translation. Adv. Neural Inf. Process. Syst. 29 (2016), 820\u2013828.","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"e_1_3_2_43_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W18-2703"},{"key":"e_1_3_2_44_2","article-title":"Exploiting out-of-domain parallel data through multilingual transfer learning for low-resource neural machine translation","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. arXiv preprint arXiv:1907.03060 (2019).","journal-title":"arXiv preprint arXiv:1907.03060"},{"key":"e_1_3_2_45_2","doi-asserted-by":"publisher","DOI":"10.1145\/3341726"},{"key":"e_1_3_2_46_2","first-page":"262","volume-title":"Proceedings of the 8th Workshop on Statistical Machine Translation","author":"Irvine Ann","year":"2013","unstructured":"Ann Irvine and Chris Callison-Burch. 2013. Combining bilingual and comparable corpora for low resource machine translation. In Proceedings of the 8th Workshop on Statistical Machine Translation. 262\u2013270."},{"key":"e_1_3_2_47_2","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/W14-1617"},{"key":"e_1_3_2_48_2","doi-asserted-by":"publisher","DOI":"10.1017\/S1351324916000127"},{"key":"e_1_3_2_49_2","first-page":"244","volume-title":"Proceedings of the Joint 5th Workshop on Statistical Machine Translation and Metrics","author":"Isozaki Hideki","year":"2010","unstructured":"Hideki Isozaki, Katsuhito Sudoh, Hajime Tsukada, and Kevin Duh. 2010. Head finalization: A simple reordering rule for SOV languages. In Proceedings of the Joint 5th Workshop on Statistical Machine Translation and Metrics. 244\u2013251."},{"key":"e_1_3_2_50_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5341"},{"key":"e_1_3_2_51_2","first-page":"1580","volume-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics","author":"Jitao Xu","year":"2020","unstructured":"Xu Jitao, Josep M. Crego, and Jean Senellart. 2020. Boosting neural machine translation with similar translations. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 1580\u20131590."},{"key":"e_1_3_2_52_2","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00065"},{"key":"e_1_3_2_53_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10590-017-9203-5"},{"key":"e_1_3_2_54_2","article-title":"Simulated multiple reference training improves low-resource machine translation","author":"Khayrallah Huda","year":"2020","unstructured":"Huda Khayrallah, Brian Thompson, Matt Post, and Philipp Koehn. 2020. Simulated multiple reference training improves low-resource machine translation. arXiv preprint arXiv:2004.14524 (2020).","journal-title":"arXiv preprint arXiv:2004.14524"},{"key":"e_1_3_2_55_2","article-title":"Effective cross-lingual transfer of neural machine translation models without shared vocabularies","author":"Kim Yunsu","year":"2019","unstructured":"Yunsu Kim, Yingbo Gao, and Hermann Ney. 2019. Effective cross-lingual transfer of neural machine translation models without shared vocabularies. arXiv preprint arXiv:1905.05475 (2019).","journal-title":"arXiv preprint arXiv:1905.05475"},{"key":"e_1_3_2_56_2","article-title":"Improving unsupervised word-by-word translation with language model and denoising autoencoder","author":"Kim Yunsu","year":"2019","unstructured":"Yunsu Kim, Jiahui Geng, and Hermann Ney. 2019. Improving unsupervised word-by-word translation with language model and denoising autoencoder. arXiv preprint arXiv:1901.01590 (2019).","journal-title":"arXiv preprint arXiv:1901.01590"},{"key":"e_1_3_2_57_2","article-title":"Pivot-based transfer learning for neural machine translation between non-English languages","author":"Kim Yunsu","year":"2019","unstructured":"Yunsu Kim, Petre Petrov, Pavel Petrushkov, Shahram Khadivi, and Hermann Ney. 2019. Pivot-based transfer learning for neural machine translation between non-English languages. arXiv preprint arXiv:1909.09524 (2019).","journal-title":"arXiv preprint arXiv:1909.09524"},{"key":"e_1_3_2_58_2","doi-asserted-by":"publisher","DOI":"10.5555\/2380816.2380835"},{"key":"e_1_3_2_59_2","article-title":"Trivial transfer learning for low-resource neural machine translation","author":"Kocmi Tom","year":"2018","unstructured":"Tom Kocmi and Ond\u0159ej Bojar. 2018. Trivial transfer learning for low-resource neural machine translation. arXiv preprint arXiv:1809.00357 (2018).","journal-title":"arXiv preprint arXiv:1809.00357"},{"key":"e_1_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.21236\/ADA461156"},{"key":"e_1_3_2_61_2","article-title":"Transfer learning in multilingual neural machine translation with dynamic vocabulary","author":"Lakew Surafel M.","year":"2018","unstructured":"Surafel M. Lakew, Aliia Erofeeva, Matteo Negri, Marcello Federico, and Marco Turchi. 2018. Transfer learning in multilingual neural machine translation with dynamic vocabulary. arXiv preprint arXiv:1811.01137 (2018).","journal-title":"arXiv preprint arXiv:1811.01137"},{"key":"e_1_3_2_62_2","article-title":"Unsupervised machine translation using monolingual corpora only","author":"Lample Guillaume","year":"2017","unstructured":"Guillaume Lample, Alexis Conneau, Ludovic Denoyer, and Marc\u2019Aurelio Ranzato. 2017. Unsupervised machine translation using monolingual corpora only. arXiv preprint arXiv:1711.00043 (2017).","journal-title":"arXiv preprint arXiv:1711.00043"},{"key":"e_1_3_2_63_2","article-title":"Phrase-based & neural unsupervised machine translation","author":"Lample Guillaume","year":"2018","unstructured":"Guillaume Lample, Myle Ott, Alexis Conneau, Ludovic Denoyer, and Marc\u2019Aurelio Ranzato. 2018. Phrase-based & neural unsupervised machine translation. arXiv preprint arXiv:1804.07755 (2018).","journal-title":"arXiv preprint arXiv:1804.07755"},{"key":"e_1_3_2_64_2","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00067"},{"key":"e_1_3_2_65_2","article-title":"Unsupervised pivot translation for distant languages","author":"Leng Yichong","year":"2019","unstructured":"Yichong Leng, Xu Tan, Tao Qin, Xiang-Yang Li, and Tie-Yan Liu. 2019. Unsupervised pivot translation for distant languages. arXiv preprint arXiv:1906.02461 (2019).","journal-title":"arXiv preprint arXiv:1906.02461"},{"key":"e_1_3_2_66_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1570"},{"key":"e_1_3_2_67_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6339"},{"key":"e_1_3_2_68_2","article-title":"One sentence one model for neural machine translation","author":"Li Xiaoqing","year":"2016","unstructured":"Xiaoqing Li, Jiajun Zhang, and Chengqing Zong. 2016. One sentence one model for neural machine translation. arXiv preprint arXiv:1609.06490 (2016).","journal-title":"arXiv preprint arXiv:1609.06490"},{"key":"e_1_3_2_69_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICMCCE48743.2019.00017"},{"key":"e_1_3_2_70_2","article-title":"Continual mixed-language pre-training for extremely low-resource neural machine translation","author":"Liu Zihan","year":"2021","unstructured":"Zihan Liu, Genta Indra Winata, and Pascale Fung. 2021. Continual mixed-language pre-training for extremely low-resource neural machine translation. arXiv preprint arXiv:2105.03953 (2021).","journal-title":"arXiv preprint arXiv:2105.03953"},{"key":"e_1_3_2_71_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2936002"},{"key":"e_1_3_2_72_2","article-title":"Effective approaches to attention-based neural machine translation","author":"Luong Minh-Thang","year":"2015","unstructured":"Minh-Thang Luong, Hieu Pham, and Christopher D. Manning. 2015. Effective approaches to attention-based neural machine translation. arXiv preprint arXiv:1508.04025 (2015).","journal-title":"arXiv preprint arXiv:1508.04025"},{"key":"e_1_3_2_73_2","doi-asserted-by":"publisher","DOI":"10.1145\/3464427"},{"key":"e_1_3_2_74_2","doi-asserted-by":"publisher","DOI":"10.1145\/3314945"},{"key":"e_1_3_2_75_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.532"},{"key":"e_1_3_2_76_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10590-017-9197-z"},{"key":"e_1_3_2_77_2","article-title":"Transfer learning across low-resource, related languages for neural machine translation","author":"Nguyen Toan Q.","year":"2017","unstructured":"Toan Q. Nguyen and David Chiang. 2017. Transfer learning across low-resource, related languages for neural machine translation. arXiv preprint arXiv:1708.09803 (2017).","journal-title":"arXiv preprint arXiv:1708.09803"},{"key":"e_1_3_2_78_2","article-title":"Data diversification: A simple strategy for neural machine translation","author":"Nguyen Xuan-Phi","year":"2019","unstructured":"Xuan-Phi Nguyen, Shafiq Joty, Wu Kui, and Ai Ti Aw. 2019. Data diversification: A simple strategy for neural machine translation. arXiv preprint arXiv:1911.01986 (2019).","journal-title":"arXiv preprint arXiv:1911.01986"},{"key":"e_1_3_2_79_2","article-title":"MacNet: Transferring knowledge from machine comprehension to sequence-to-sequence models","author":"Pan Boyuan","year":"2019","unstructured":"Boyuan Pan, Yazheng Yang, Hao Li, Zhou Zhao, Yueting Zhuang, Deng Cai, and Xiaofei He. 2019. MacNet: Transferring knowledge from machine comprehension to sequence-to-sequence models. arXiv preprint arXiv:1908.01816 (2019).","journal-title":"arXiv preprint arXiv:1908.01816"},{"key":"e_1_3_2_80_2","first-page":"311","volume-title":"Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics","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. 311\u2013318."},{"key":"e_1_3_2_81_2","doi-asserted-by":"publisher","DOI":"10.1145\/2505126"},{"key":"e_1_3_2_82_2","article-title":"Deep contextualized word representations","author":"Peters Matthew E.","year":"2018","unstructured":"Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018. Deep contextualized word representations. arXiv preprint arXiv:1802.05365 (2018).","journal-title":"arXiv preprint arXiv:1802.05365"},{"key":"e_1_3_2_83_2","article-title":"Meta back-translation","author":"Pham Hieu","year":"2021","unstructured":"Hieu Pham, Xinyi Wang, Yiming Yang, and Graham Neubig. 2021. Meta back-translation. arXiv preprint arXiv:2102.07847 (2021).","journal-title":"arXiv preprint arXiv:2102.07847"},{"key":"e_1_3_2_84_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W15-3049"},{"key":"e_1_3_2_85_2","article-title":"Translating translationese: A two-step approach to unsupervised machine translation","author":"Pourdamghani Nima","year":"2019","unstructured":"Nima Pourdamghani, Nada Aldarrab, Marjan Ghazvininejad, Kevin Knight, and Jonathan May. 2019. Translating translationese: A two-step approach to unsupervised machine translation. arXiv preprint arXiv:1906.05683 (2019).","journal-title":"arXiv preprint arXiv:1906.05683"},{"key":"e_1_3_2_86_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1266"},{"issue":"8","key":"e_1_3_2_87_2","first-page":"9","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"Radford Alec","year":"2019","unstructured":"Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et\u00a0al. 2019. Language models are unsupervised multitask learners. OpenAI Blog 1, 8 (2019), 9.","journal-title":"OpenAI Blog"},{"key":"e_1_3_2_88_2","doi-asserted-by":"publisher","DOI":"10.5555\/2002472.2002475"},{"key":"e_1_3_2_89_2","article-title":"Triangular architecture for rare language translation","author":"Ren Shuo","year":"2018","unstructured":"Shuo Ren, Wenhu Chen, Shujie Liu, Mu Li, Ming Zhou, and Shuai Ma. 2018. Triangular architecture for rare language translation. arXiv preprint arXiv:1805.04813 (2018).","journal-title":"arXiv preprint arXiv:1805.04813"},{"key":"e_1_3_2_90_2","article-title":"Explicit cross-lingual pre-training for unsupervised machine translation","author":"Ren Shuo","year":"2019","unstructured":"Shuo Ren, Yu Wu, Shujie Liu, Ming Zhou, and Shuai Ma. 2019. Explicit cross-lingual pre-training for unsupervised machine translation. arXiv preprint arXiv:1909.00180 (2019).","journal-title":"arXiv preprint arXiv:1909.00180"},{"key":"e_1_3_2_91_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.320"},{"key":"e_1_3_2_92_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1297"},{"key":"e_1_3_2_93_2","article-title":"Improving neural machine translation models with monolingual data","author":"Sennrich Rico","year":"2015","unstructured":"Rico Sennrich, Barry Haddow, and Alexandra Birch. 2015. Improving neural machine translation models with monolingual data. arXiv preprint arXiv:1511.06709 (2015).","journal-title":"arXiv preprint arXiv:1511.06709"},{"key":"e_1_3_2_94_2","article-title":"Edinburgh neural machine translation systems for WMT 16","author":"Sennrich Rico","year":"2016","unstructured":"Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016. Edinburgh neural machine translation systems for WMT 16. arXiv preprint arXiv:1606.02891 (2016).","journal-title":"arXiv preprint arXiv:1606.02891"},{"key":"e_1_3_2_95_2","article-title":"Revisiting low-resource neural machine translation: A case study","author":"Sennrich Rico","year":"2019","unstructured":"Rico Sennrich and Biao Zhang. 2019. Revisiting low-resource neural machine translation: A case study. arXiv preprint arXiv:1905.11901 (2019).","journal-title":"arXiv preprint arXiv:1905.11901"},{"key":"e_1_3_2_96_2","article-title":"Better neural machine translation by extracting linguistic information from BERT","author":"Shavarani Hassan S.","year":"2021","unstructured":"Hassan S. Shavarani and Anoop Sarkar. 2021. Better neural machine translation by extracting linguistic information from BERT. arXiv preprint arXiv:2104.02831 (2021).","journal-title":"arXiv preprint arXiv:2104.02831"},{"key":"e_1_3_2_97_2","first-page":"223","volume-title":"Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers","author":"Snover Matthew","year":"2006","unstructured":"Matthew Snover, Bonnie Dorr, Richard Schwartz, Linnea Micciulla, and John Makhoul. 2006. A study of translation edit rate with targeted human annotation. In Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers. 223\u2013231."},{"key":"e_1_3_2_98_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1119"},{"key":"e_1_3_2_99_2","article-title":"Sequence to sequence learning with neural networks","author":"Sutskever Ilya","year":"2014","unstructured":"Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014. Sequence to sequence learning with neural networks. arXiv preprint arXiv:1409.3215 (2014).","journal-title":"arXiv preprint arXiv:1409.3215"},{"key":"e_1_3_2_100_2","article-title":"Attention is all you need","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. arXiv preprint arXiv:1706.03762 (2017).","journal-title":"arXiv preprint arXiv:1706.03762"},{"issue":"12","key":"e_1_3_2_101_2","article-title":"Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion.","volume":"11","author":"Vincent Pascal","year":"2010","unstructured":"Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol, and L\u00e9on Bottou. 2010. Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion.J. Mach. Learn. Res. 11, 12 (2010).","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_102_2","article-title":"A survey on low-resource neural machine translation","author":"Wang Rui","year":"2021","unstructured":"Rui Wang, Xu Tan, Renqian Luo, Tao Qin, and Tie-Yan Liu. 2021. A survey on low-resource neural machine translation. arXiv preprint arXiv:2107.04239 (2021).","journal-title":"arXiv preprint arXiv:2107.04239"},{"key":"e_1_3_2_103_2","article-title":"SwitchOut: An efficient data augmentation algorithm for neural machine translation","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. arXiv preprint arXiv:1808.07512 (2018).","journal-title":"arXiv preprint arXiv:1808.07512"},{"key":"e_1_3_2_104_2","article-title":"Iterative domain-repaired back-translation","author":"Wei Hao-Ran","year":"2020","unstructured":"Hao-Ran Wei, Zhirui Zhang, Boxing Chen, and Weihua Luo. 2020. Iterative domain-repaired back-translation. arXiv preprint arXiv:2010.02473 (2020).","journal-title":"arXiv preprint arXiv:2010.02473"},{"key":"e_1_3_2_105_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6465"},{"key":"e_1_3_2_106_2","article-title":"Improving neural machine translation with pre-trained representation","author":"Weng Rongxiang","year":"2019","unstructured":"Rongxiang Weng, Heng Yu, Shujian Huang, Weihua Luo, and Jiajun Chen. 2019. Improving neural machine translation with pre-trained representation. arXiv preprint arXiv:1908.07688 (2019).","journal-title":"arXiv preprint arXiv:1908.07688"},{"key":"e_1_3_2_107_2","article-title":"Extract and edit: An alternative to back-translation for unsupervised neural machine translation","author":"Wu Jiawei","year":"2019","unstructured":"Jiawei Wu, Xin Wang, and William Yang Wang. 2019. Extract and edit: An alternative to back-translation for unsupervised neural machine translation. arXiv preprint arXiv:1904.02331 (2019).","journal-title":"arXiv preprint arXiv:1904.02331"},{"key":"e_1_3_2_108_2","article-title":"Dual learning for machine translation","author":"Xia Yingce","year":"2016","unstructured":"Yingce Xia, Di He, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, and Wei-Ying Ma. 2016. Dual learning for machine translation. arXiv preprint arXiv:1611.00179 (2016).","journal-title":"arXiv preprint arXiv:1611.00179"},{"key":"e_1_3_2_109_2","article-title":"Data noising as smoothing in neural network language models","author":"Xie Ziang","year":"2017","unstructured":"Ziang Xie, Sida I. Wang, Jiwei Li, Daniel L\u00e9vy, Aiming Nie, Dan Jurafsky, and Andrew Y. Ng. 2017. Data noising as smoothing in neural network language models. arXiv preprint arXiv:1703.02573 (2017).","journal-title":"arXiv preprint arXiv:1703.02573"},{"key":"e_1_3_2_110_2","article-title":"Unsupervised neural machine translation with weight sharing","author":"Yang Zhen","year":"2018","unstructured":"Zhen Yang, Wei Chen, Feng Wang, and Bo Xu. 2018. Unsupervised neural machine translation with weight sharing. arXiv preprint arXiv:1804.09057 (2018).","journal-title":"arXiv preprint arXiv:1804.09057"},{"key":"e_1_3_2_111_2","first-page":"318","volume-title":"Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","author":"Zahabi Samira Tofighi","year":"2013","unstructured":"Samira Tofighi Zahabi, Somayeh Bakhshaei, and Shahram Khadivi. 2013. Using context vectors in improving a machine translation system with bridge language. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). 318\u2013322."},{"key":"e_1_3_2_112_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1160"},{"key":"e_1_3_2_113_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1179"},{"key":"e_1_3_2_114_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/594"},{"key":"e_1_3_2_115_2","volume-title":"Proceedings of the International Conference on Learning Representations","author":"Zheng Zaixiang","year":"2019","unstructured":"Zaixiang Zheng, Hao Zhou, Shujian Huang, Lei Li, Xin-Yu Dai, and Jiajun Chen. 2019. Mirror-generative neural machine translation. In Proceedings of the International Conference on Learning Representations."},{"key":"e_1_3_2_116_2","article-title":"Handling syntactic divergence in low-resource machine translation","author":"Zhou Chunting","year":"2019","unstructured":"Chunting Zhou, Xuezhe Ma, Junjie Hu, and Graham Neubig. 2019. Handling syntactic divergence in low-resource machine translation. arXiv preprint arXiv:1909.00040 (2019).","journal-title":"arXiv preprint arXiv:1909.00040"},{"key":"e_1_3_2_117_2","article-title":"Transfer learning for low-resource neural machine translation","author":"Zoph Barret","year":"2016","unstructured":"Barret Zoph, Deniz Yuret, Jonathan May, and Kevin Knight. 2016. Transfer learning for low-resource neural machine translation. arXiv preprint arXiv:1604.02201 (2016).","journal-title":"arXiv preprint arXiv:1604.02201"}],"container-title":["ACM Transactions on Asian and Low-Resource Language Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3524300","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3524300","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:56Z","timestamp":1750188656000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3524300"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,30]]},"references-count":116,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,9,30]]}},"alternative-id":["10.1145\/3524300"],"URL":"https:\/\/doi.org\/10.1145\/3524300","relation":{},"ISSN":["2375-4699","2375-4702"],"issn-type":[{"value":"2375-4699","type":"print"},{"value":"2375-4702","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,30]]},"assertion":[{"value":"2021-06-10","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-01-27","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-11-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}