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Huyen Nguyen

Huyen Nguyen has 2 papers in our library, in 2019–2022, most of them on English, Universal Dependencies, Semantic role labeling; often with Alexandre Rademaker, Huaiyu Zhu, Yunyao Li.

2 papers in our library · 2019–2022

OpenAlex · h-index 6 · 11 works · 558 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 90 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #5734

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

🎓University of North TexasDenton · United States2020–2024 · 2 papers🏢NvidiaSanta Clara · United States2019 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 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 4Research subjects and languages the work is about.English · 2 worksSemantic role labeling · 1 workUniversal Dependencies · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20221 paperUniversal Proposition Bank 2.0

2010s

20191 paperSimpleBooks: Long-term dependency book dataset with simplified English vocabulary for word-level language modeling

 Papers

The most cited first (OpenAlex and our library).

  1. Universal Proposition Bank 2.0 (2022 · 18 citations)
    Most languages have no propbank because manual annotation is expensive. The non-English propbanks that do exist use their own rolesets, which makes a single multilingual semantic role labeler impractical. UP2.0 extends the authors' 2017 resource by automatically labeling UD treebank text in 23 languages (8 families…
  2. SimpleBooks: Long-term dependency book dataset with simplified English vocabulary for word-level language modeling (2019)
    Smaller benchmarks for word-level language modeling are not good stand-ins for larger ones. In small corpora each word type occurs only a few times. As a result, architectures that lead on small sets, such as LSTMs on WikiText-2, often lose on large sets, where Transformers dominate WikiText-103. This weakens cheap…

All works

3 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. NeMo: a toolkit for building AI applications using Neural ModulesarXiv:1909.09577 · original ↗ · no summary yetOleksii Kuchaiev et al.2019 · 243 citations
  2. Universal Proposition Bank 2.0Language Resources and Evaluation Conference (LREC)Ishan Jindal, Alexandre Rademaker, Michał Ulewicz, et al.2022 · 18 citations
  3. SimpleBooks: Long-term dependency book dataset with simplified English vocabulary for word-level language modelingarXiv:1911.12391Huyen Nguyen2019

 Co-authors here

3 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 90 times (of the 141,840 papers whose bibliographies we read); 9 citing papers with a page here →.

Updated

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