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Xuan Zhang

Xuan Zhang has 2 papers in our library, in 2019–2026, most of them on Machine translation; often with Bo Zheng, Chao Deng, Fei Yin.

2 papers in our library · 2019–2026

OpenAlex · ORCID · h-index 14 · 31 works · 742 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 74 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #5979

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

🎓Johns Hopkins UniversityBaltimore · United States2018–2024 · 11 papersEducation since 2019 · Ph.D., Department of Computer Sciencecurrent🎓University of AgderKristiansand · Norway2011–2019 · 4 papers🎓Virginia TechBlacksburg · United States2016–2017 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksComputational Theory and Mathematics · 1 work

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

 Works by year

2020s

20261 paper

2010s

20191 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Curriculum Learning for Domain Adaptation in Neural Machine Translation (2019 · 169 citations)
    Neural MT systems trained on broad, mixed-domain data tend to underperform on specialised domains where parallel text is scarce.
  2. Geoparsing: Diagram Parsing for Plane and Solid Geometry with a Unified Formal Language (2026)
    Multimodal LLMs often fail at geometry problems because they misread diagrams. They miss or invent points, lines, and relations. Prior diagram-parsing work, such as PGDP5K and FormalGeo7K, handled only plane figures. The authors build a single formal language that adopts the predicate-style notation of PGPS9K and…

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Curriculum Learning for Domain Adaptation in Neural Machine TranslationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Xuan Zhang, Pamela Shapiro, Gaurav Kumar, et al.2019 · 169 citations
  2. Reproducible and Efficient Benchmarks for Hyperparameter Optimization of Neural Machine Translation Systems ↗Transactions of the Association for Computational Linguistics · no summary yetXuan Zhang, Kevin Duh2020 · 39 citations
  3. SEMA: Text Simplification Evaluation through Semantic Alignment ↗Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications · no summary yetXuan Zhang et al.2020 · 4 citations
  4. Geoparsing: Diagram Parsing for Plane and Solid Geometry with a Unified Formal LanguageFindings of the Association for Computational LinguisticsPeijie Wang, Ming-Liang Zhang, Jun Cao, et al.2026

 Co-authors here

12 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 74 times (of the 149,439 papers whose bibliographies we read); 4 citing papers with a page here →.

Updated

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