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Dieuwke Hupkes

Dieuwke Hupkes has 2 papers in our library, in 2019–2021, most of them on Language models & pretraining, Syntax & grammar formalisms; often with Adina Williams, Douwe Kiela, German Kruszewski.

2 papers in our library · 2019–2021

OpenAlex · h-index 17 · 98 works · 1,694 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 1,465 citations in our library · 9 more in our library without a page yet · ⭐ Paper Star rank #2993

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 AmsterdamAmsterdam · Netherlands2016–2024 · 25 papers🏢MetaMenlo Park · United States2021–2022 · 20 papers🏢MetaLondon · United Kingdom2021 · 5 papers🎓McGill UniversityMontreal · Canada2021–2024 · 3 papers🎓University of EdinburghEdinburgh · United Kingdom2021–2024 · 3 papers🎓Ludwig-Maximilians-Universität MünchenMunich · Germany2024–2025 · 2 papers🎓University College LondonLondon · United Kingdom2024–2025 · 2 papers🔬Mila - Quebec Artificial Intelligence InstituteMontreal · Canada2021–2022 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 more institutions on single bylines are not listed.

 Topics

 Language models & pretraining (2) Syntax & grammar formalisms (1)

 Works by year

2020s

20211 paper

2010s

20191 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little (2021 · 292 citations)
    The paper asks why masked language model (MLM) pre-training works so well. One common view holds that models like BERT learn syntactic abstractions similar to a classical NLP pipeline. The authors test a different explanation: the benefit comes mainly from capturing higher-order word co-occurrence statistics.
  2. The emergence of number and syntax units in LSTM language models (2019 · 194 citations)
    LSTM language models handle long-distance subject–verb number agreement well, but it was unclear whether they rely on real syntactic structure or on shallow cues.

Also in our library

9 more works of theirs are in our library without a page here yet; they will appear as we publish them.

 Co-authors here

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

 Cited by

Papers of our library cite their works 1,465 times (of the 140,884 papers whose bibliographies we read); 148 citing papers with a page here →.

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