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Yu Bao

Yu Bao has 2 papers in our library, in 2019–2021, most of them on Machine translation; often with Hao Zhou, Lei Li, Jiajun Chen.

2 papers in our library · 2019–2021

OpenAlex · ORCID · h-index 20 · 64 works · 1,591 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 200 times in our library · ⭐ Paper Stars ranking: #4046

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Guangxi Medical UniversityNanning · China2020–2026 · 7 paperscurrent🎓Guizhou UniversityGuiyang · China2026 · 1 papercurrent🎓Qingdao UniversityQingdao · China2026 · 1 papercurrent🎓Shanghai Jiao Tong UniversityShanghai · China2009–2017 · 15 papers🎓Nanjing UniversityNanjing · China2019–2025 · 13 papers🎓East China Normal UniversityShanghai · China2009–2024 · 5 papers🏥Shanghai Sixth People's HospitalShanghai · China2009–2016 · 5 papers🔬Collaborative Innovation Center of Advanced MicrostructuresNanjing · China2022–2025 · 4 papers🔬National Laboratory of Solid State MicrostructuresNanjing2022–2025 · 4 papers🎓Renmin University of ChinaBeijing · China2024–2025 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 9 more institutions on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Machine translation · 1 work

 Works by year

2020s

20211 paperGlancing Transformer for Non-Autoregressive Neural Machine Translation

2010s

20191 paperGenerating Sentences from Disentangled Syntactic and Semantic Spaces

 Papers

The most cited first (OpenAlex and our library).

  1. Glancing Transformer for Non-Autoregressive Neural Machine Translation (2021 · 180 citations)
    Non-autoregressive translation (NAT) models emit all target tokens at once, which makes them fast. However, they assume target words are independent given the source, so they translate noticeably worse than the autoregressive Transformer. Iterative fixes such as Mask-Predict recover quality but need several decoding…
  2. Generating Sentences from Disentangled Syntactic and Semantic Spaces (2019 · 154 citations)
    Standard variational autoencoders for text store all sentence information in one continuous latent vector.

 Co-authors here

11 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 200 times (of the 141,840 papers whose bibliographies we read); 9 citing papers with a page here →.

Updated

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