📰 Workshop on Discourse in Machine Translation 2019 — accepted papers

Workshop on Discourse in Machine Translation 2019 is the 2019 edition of the Workshop on Discourse in Machine Translation, held in Hong Kong, China, November 2019 (publisher: Association for Computational Linguistics). The ACL Anthology lists 6 papers of it; our library holds 2 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. Data augmentation using back-translation for context-aware neural machine translation ↗Amane Sugiyama, Naoki Yoshinaga89 citations
2. When and Why is Document-level Context Useful in Neural Machine Translation?Yunsu Kim, Duc Thanh Tran, Hermann Ney60 citations · our summary
3. Analysing concatenation approaches to document-level NMT in two different domains ↗Yves Scherrer, Jörg Tiedemann, Sharid Loáiciga24 citations
4. Context-aware Neural Machine Translation with Coreference InformationTakumi Ohtani, Hidetaka Kamigaito, Masaaki Nagata et al.8 citations · our summary
5. Context-Aware Neural Machine Translation Decoding ↗Eva Martínez Garcia, Carles Creus, Cristina España-Bonet7 citations
6. Analysing Coreference in Transformer Outputs ↗Ekaterina Lapshinova-Koltunski, Cristina España-Bonet, Josef van Genabith2 citations

All accepted papers (6)

The most cited first; 2 with our summary link to their page here, the others to the original.

1. Data augmentation using back-translation for context-aware neural machine translation ↗Amane Sugiyama, Naoki Yoshinaga89 citations
2. When and Why is Document-level Context Useful in Neural Machine Translation?Yunsu Kim, Duc Thanh Tran, Hermann Ney60 citations · our summary
3. Analysing concatenation approaches to document-level NMT in two different domains ↗Yves Scherrer, Jörg Tiedemann, Sharid Loáiciga24 citations
4. Context-aware Neural Machine Translation with Coreference InformationTakumi Ohtani, Hidetaka Kamigaito, Masaaki Nagata et al.8 citations · our summary
5. Context-Aware Neural Machine Translation Decoding ↗Eva Martínez Garcia, Carles Creus, Cristina España-Bonet7 citations
6. Analysing Coreference in Transformer Outputs ↗Ekaterina Lapshinova-Koltunski, Cristina España-Bonet, Josef van Genabith2 citations

📄 Papers with our summary in our library (2)

The most cited first (OpenAlex citations plus our library's).

1. When and Why is Document-level Context Useful in Neural Machine Translation?Workshop on Discourse in Machine TranslationYunsu Kim, Duc Thanh Tran, Hermann Ney2019 · 124 citations
2. Context-aware Neural Machine Translation with Coreference InformationWorkshop on Discourse in Machine TranslationTakumi Ohtani, Hidetaka Kamigaito, Masaaki Nagata, et al.2019 · 19 citations

🧭 Top topics

Topics of its works in our library, with the number of works on each.

🔁Machine translation (2)🔗Coreference resolution (1)

📚 Fields

🎭Arts and Humanities (2)🖥️Computer Science (2)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🎓Tokyo Institute of TechnologyTokyo · Japan1 work here🏢NTTTokyo · Japan1 work here🎓RWTH Aachen UniversityAachen · Germany1 work here

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/venues/workshop-on-discourse-in-machine-translation/2019/