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Rochelle Choenni

Rochelle Choenni has 4 papers in our library, in 2022–2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Dependency parsing; often with Ekaterina Shutova, Dan Garrette, Ivan Titov.

4 papers in our library · 2022–2026

OpenAlex · h-index 9 · 66 works · 267 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 64 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #6922

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 · Netherlands2018–2026 · 39 paperscurrent🏛️Ministry of Security and JusticeThe Hague · Netherlands2010–2018 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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 7The field of science this work belongs to (OpenAlex fields).Computer Science · 4 worksArtificial Intelligence · 4 worksArts and Humanities · 3 worksLanguage and Linguistics · 3 worksExperimental and Cognitive Psychology · 1 workPsychology · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 7Research subjects and languages the work is about.Multilingual & cross-lingual NLP · 2 worksLanguage models & pretraining · 2 worksIdioms & multiword expressions · 1 workDependency parsing · 1 workLow-resource languages · 1 workInterpretability · 1 workVision & language · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Cognitive linguistics · 1 work

 Works by year

2020s

20261 paper20241 paper20231 paper20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Metaphor Understanding Challenge Dataset for LLMs (2024 · 47 citations)
    Metaphor is common in everyday language, yet it is unclear whether LLMs actually interpret it or just rely on surface word similarity.
  2. Investigating Language Relationships in Multilingual Sentence Encoders Through the Lens of Linguistic Typology (2022 · 24 citations)
    Multilingual sentence encoders support cross-lingual transfer, but it is unclear which properties of individual languages they capture and how they represent typological similarity and difference between languages.
  3. Cross-Lingual Transfer with Language-Specific Subnetworks for Low-Resource Dependency Parsing (2023 · 20 citations)
    Multilingual encoders like mBERT use one set of parameters for all languages. This enables transfer, but updates from dissimilar languages can conflict, and low-resource languages suffer most. The authors manage parameter sharing during fine-tuning with language-specific subnetworks. For each training language, they…
  4. Finding Culture-Sensitive Neurons in Vision-Language Models (2026 · 2 citations)
    Vision-language models (VLMs) often answer worse on culturally specific images and questions, but it is unclear where culture-related processing happens inside them.

All works

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

  1. Metaphor Understanding Challenge Dataset for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyu Tong, Rochelle Choenni, Martha Lewis, et al.2024 · 47 citations
  2. Investigating Language Relationships in Multilingual Sentence Encoders Through the Lens of Linguistic TypologyComputational LinguisticsRochelle Choenni, Ekaterina Shutova2022 · 24 citations
  3. Cross-Lingual Transfer with Language-Specific Subnetworks for Low-Resource Dependency ParsingComputational LinguisticsRochelle Choenni, Dan Garrette, Ekaterina Shutova2023 · 20 citations
  4. On the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human Translations? ↗arXiv:2406.14267 · no summary yetRochelle Choenni et al.2024 · 5 citations
  5. Finding Culture-Sensitive Neurons in Vision-Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Xiutian Zhao, Rochelle Choenni, Rohit Saxena, et al.2026 · 2 citations
  6. An Empirical Analysis of Machine Translation for Expanding Multilingual Benchmarks ↗Proceedings of the Tenth Conference on Machine Translation · no summary yetSara Rajaee et al.2025 · 1 citation

 Co-authors here

7 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 64 times (of the 149,439 papers whose bibliographies we read); 18 citing papers with a page here →.

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