--- title: "Chenhui Chu — author profile and papers" description: "Chenhui Chu, Kyoto University: 2 papers on Elamur Research (2017–2018), h-index 20 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/chenhui-chu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/chenhui-chu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Chenhui Chu # Chenhui Chu 2 papers on this site · 2017–2018 current affiliation [Kyoto University](https://md.research.elamur.ai/free/en/universities/kyoto-university/), Kyoto, Japan Chenhui Chu has 2 papers on this site, in 2017–2018, most of them on [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/); often with [Raj Dabre](https://md.research.elamur.ai/free/en/authors/raj-dabre/), [Rui Wang](https://md.research.elamur.ai/free/en/authors/rui-wang/), [Sadao Kurohashi](https://md.research.elamur.ai/free/en/authors/sadao-kurohashi/). [OpenAlex](https://openalex.org/A5102757632) · [ORCID](https://orcid.org/0000-0001-9848-6384) · [**h-index 20**](https://openalex.org/authors/A5102757632) · [201 works](https://openalex.org/works?filter=author.id:A5102757632) · [2 226 citations](https://openalex.org/works?filter=author.id:A5102757632&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [2 works on this site](https://md.research.elamur.ai/free/en/authors/chenhui-chu/#papers) · [324 citations in our library](https://md.research.elamur.ai/free/en/authors/chenhui-chu/cited-by/) · 13 more works in our library The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Chenhui+Chu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Chenhui+Chu) · [dblp](https://dblp.org/search?q=Chenhui+Chu) · [ACL Anthology](https://aclanthology.org/search/?q=Chenhui+Chu) ## Affiliations - [Kyoto University](https://md.research.elamur.ai/free/en/universities/kyoto-university/) · Kyoto, Japan —current · 2012–2026 on 125 papers · employment (ORCID) - [The University of Osaka](https://md.research.elamur.ai/free/en/universities/the-university-of-osaka/) · Osaka, Japan —2016–2025 on 30 papers - [National Institute of Information and Communications Technology](https://md.research.elamur.ai/free/en/labs/national-institute-of-information-and-communications-technology/) · Tokyo, Japan —2022–2023 on 2 papers - [Japan Science and Technology Agency](https://md.research.elamur.ai/free/en/government/japan-science-and-technology-agency/) · Tokyo, Japan —2015–2017 on 9 papers - [Japan Society for the Promotion of Science](https://ror.org/00hhkn466) · Tokyo, Japan —2015–2016 on 4 papers From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 more institutions on single bylines are not listed. ## Topics [Machine translation 2](https://md.research.elamur.ai/free/en/topics/machine-translation/) ## Works by year ### 2010s [**2018** 1 paper](https://md.research.elamur.ai/free/en/papers/chu-2018-survey-domain-adaptation-neural-machine/) · [**2017** 1 paper](https://md.research.elamur.ai/free/en/papers/chu-2017-empirical-comparison-domain-adaptation-methods/) ## Papers The most cited first (OpenAlex and our library). 1. **[An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chu-2017-empirical-comparison-domain-adaptation-methods/)** *(2017 · 316 citations)* The paper addresses neural machine translation (NMT) for domains with little parallel data. In these settings plain NMT often loses to phrase-based SMT, and standard fine tuning on a small in-domain corpus quickly overfits. The authors propose "mixed fine tuning", which combines fine tuning with tag-based multi… 2. **[A Survey of Domain Adaptation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chu-2018-survey-domain-adaptation-neural-machine/)** *(2018 · 304 citations)* Neural machine translation achieves strong results when large parallel corpora exist. However, most language pairs and domains have little or no in-domain parallel data, so standard NMT performs badly on specialized text. Chu and Wang claim that theirs is the first broad review to cover how NMT can be adapted across… ## Also in our library 13 more works of theirs are in our library without a page here yet; they will appear as we publish them. ## Co-authors here 3 co-authors with a page, the most papers together first. - [Raj Dabre](https://md.research.elamur.ai/free/en/authors/raj-dabre/) - [Rui Wang](https://md.research.elamur.ai/free/en/authors/rui-wang/) - [Sadao Kurohashi](https://md.research.elamur.ai/free/en/authors/sadao-kurohashi/) ## Cited by Papers of our library cite their works 324 times (of the 140 884 papers whose bibliographies we read); [11 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/chenhui-chu/cited-by/).