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| "title": "Alexandra Birch, (Edinburgh) Andrew Finch, (Apple) Hiroaki Hayashi (CMU) Kenneth Heafield (Edinburgh) Marcin Junczys-Dowmunt (Microsoft) Ioannis Konstas (Heriot Watt University) Xian Li (Facebook) Graham Neubig, (CMU) Yusuke Oda, (Google) Program Committee", | |
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| "paper_id": "2020", | |
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| "abstract": [], | |
| "body_text": [ | |
| { | |
| "text": "Welcome to the Fourth Workshop on Neural Generation and Translation. This workshop aims to cultivate research on the leading edge in neural machine translation and other aspects of machine translation, generation, and multilinguality that utilize neural models. We received a total of 28 submissions in total. From the 21 long papers we accepted 16. There were two cross-submissions, three extended abstracts. All research papers were reviewed twice through a double blind review process, and avoiding conflicts of interest. The topics of the papers were split equally between the natural language generation and machine translation themes. We would like to thank all authors for their submissions, and the program committee members for their valuable efforts in reviewing the papers for the workshop.", | |
| "cite_spans": [], | |
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| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| } | |
| ], | |
| "back_matter": [], | |
| "bib_entries": { | |
| "BIBREF0": { | |
| "ref_id": "b0", | |
| "title": "Generating Diverse Translations via Weighted Fine-tuning and Hypotheses Filtering for the Duolingo STAPLE Task Sweta Agrawal and Marine Carpuat The JHU Submission to the 2020 Duolingo Shared Task on Simultaneous Translation and Paraphrase for Language Education Huda Khayrallah", | |
| "authors": [ | |
| { | |
| "first": "Jacob", | |
| "middle": [], | |
| "last": "Bremerman", | |
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| }, | |
| { | |
| "first": "Arya", | |
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| "D" | |
| ], | |
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| }, | |
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| "year": 2020, | |
| "venue": "Sidharth Kashyap, Emmanouil-Ioannis Farsarakis and Mateusz Chudyk Improving Document-Level Neural Machine Translation with Domain Adaptation Sami Ul Haq, Sadaf Abdul Rauf, Arslan Shoukat and Noor-e-Hira Simultaneous Translation and Paraphrase for Language Education Stephen Mayhew", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Growing Together: Modeling Human Language Learning With n-Best Multi- Checkpoint Machine Translation El Moatez Billah Nagoudi, Muhammad Abdul-Mageed and Hasan Cavusoglu Generating Diverse Translations via Weighted Fine-tuning and Hypotheses Filter- ing for the Duolingo STAPLE Task Sweta Agrawal and Marine Carpuat The JHU Submission to the 2020 Duolingo Shared Task on Simultaneous Transla- tion and Paraphrase for Language Education Huda Khayrallah, Jacob Bremerman, Arya D. McCarthy, Kenton Murray, Winston Wu and Matt Post Simultaneous paraphrasing and translation by fine-tuning Transformer models Rakesh Chada The NiuTrans System for WNGT 2020 Efficiency Task Chi Hu, Bei Li, Yinqiao Li, Ye Lin, Yanyang Li, Chenglong Wang, Tong Xiao and Jingbo Zhu Efficient and High-Quality Neural Machine Translation with OpenNMT Guillaume Klein, Dakun Zhang, Cl\u00e9ment Chouteau, Josep Crego and Jean Senellart Edinburgh's Submissions to the 2020 Machine Translation Efficiency Task Nikolay Bogoychev, Roman Grundkiewicz, Alham Fikri Aji, Maximiliana Behnke, Kenneth Heafield, Sidharth Kashyap, Emmanouil-Ioannis Farsarakis and Mateusz Chudyk Improving Document-Level Neural Machine Translation with Domain Adaptation Sami Ul Haq, Sadaf Abdul Rauf, Arslan Shoukat and Noor-e-Hira Simultaneous Translation and Paraphrase for Language Education Stephen Mayhew, Klinton Bicknell, Chris Brust, Bill McDowell, Will Monroe and Burr Settles", | |
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| } | |
| }, | |
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| } | |
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