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Terra Blevins

Terra Blevins has 3 papers in our library, in 2018–2024, most of them on Word sense disambiguation, Multilingual & cross-lingual NLP, Syntax & grammar formalisms; often with Luke Zettlemoyer, Akari Asai, Hannaneh Hajishirzi.

3 papers in our library · 2018–2024

OpenAlex · h-index 10 · 59 works · 576 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 411 times in our library · 5 more in our library without a page yet · ⭐ Paper Stars ranking: #3372

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

🎓Northeastern UniversityBoston · United States2025–2026 · 10 paperscurrent🎓University of ViennaVienna · Austria2025–2026 · 3 paperscurrent🎓University of WashingtonSeattle · United States2016–2025 · 25 papers🔬Allen Institute for Artificial IntelligenceSeattle · United States2023–2024 · 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.

 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 · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 works

🧭 Topics 3Research subjects and languages the work is about.Word sense disambiguation · 1 workSyntax & grammar formalisms · 1 workMultilingual & cross-lingual NLP · 1 work

💡 Concepts 2Key ideas and methods explained on our concept pages.Word sense disambiguation · 1 workZipf's law · 1 work

 Works by year

2020s

20241 paperBUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer20201 paperMoving Down the Long Tail of Word Sense Disambiguation with Gloss Informed Bi-encoders

2010s

20181 paperDeep RNNs Encode Soft Hierarchical Syntax

 Papers

The most cited first (OpenAlex and our library).

  1. Moving Down the Long Tail of Word Sense Disambiguation with Gloss Informed Bi-encoders (2020 · 232 citations)
    Word Sense Disambiguation (WSD) systems tend to fail on rare senses. Sense frequencies follow a Zipfian distribution, so models learn to favor the most frequent sense (MFS) and do poorly on less frequent senses (LFS) or senses never seen in training. Blevins and Zettlemoyer address this with a bi-encoder model (BEM).…
  2. Deep RNNs Encode Soft Hierarchical Syntax (2018 · 178 citations)
    This short paper asks whether deep recurrent networks trained on ordinary NLP objectives learn syntactic structure that they were never directly taught.
  3. BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer (2024 · 85 citations)
    Research on few-shot learning with large language models has focused mostly on English. It has remained unclear how in-context learning (ICL) compares with fine-tuning when only a few target-language examples are available. The authors present BUFFET, a benchmark whose name refers to evaluating few-shot transfer…

All works

8 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. Moving Down the Long Tail of Word Sense Disambiguation with Gloss Informed Bi-encodersAnnual Meeting of the Association for Computational Linguistics (ACL)Terra Blevins, Luke Zettlemoyer2020 · 232 citations
  2. Demystifying Prompts in Language Models via Perplexity EstimationarXiv:2212.04037 · original ↗ · no summary yetHila Gonen et al.2022 · 211 citations
  3. Deep RNNs Encode Soft Hierarchical SyntaxAnnual Meeting of the Association for Computational Linguistics (ACL)Terra Blevins, Omer Levy, Luke Zettlemoyer2018 · 178 citations
  4. BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual TransferConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Akari Asai, Sneha Kudugunta, Xinyan Yu, et al.2024 · 85 citations
  5. Breaking the Curse of Multilinguality with Cross-lingual Expert Language ModelsProceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · original ↗ · no summary yetTerra Blevins et al.2024 · 41 citations
  6. MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language ModelingProceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · original ↗ · no summary yetTomasz Limisiewicz et al.2024 · 25 citations
  7. Comparing Hallucination Detection Metrics for Multilingual GenerationarXiv:2402.10496 · original ↗ · no summary yetHaoqiang Kang, Terra Blevins, Luke Zettlemoyer2024 · 18 citations
  8. Mining Paraphrasal Typed Templates from a Plain Text CorpusProceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · original ↗ · no summary yetOr Biran, Terra Blevins, Kathleen McKeown2016 · 10 citations

 Co-authors here

10 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 411 times (of the 141,840 papers whose bibliographies we read); 36 citing papers with a page here →.

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