Elamur Research⌕
☰
home / authors / David Belanger

David Belanger

David Belanger has 2 papers in our library, in 2017–2020, most of them on Named entity recognition; often with Andrew McCallum, David Dohan, Emma Strubell.

2 papers in our library · 2017–2020

OpenAlex · ORCID · h-index 24 · 68 works · 3,156 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 503 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #2402

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

🏢GoogleMountain View · United States2017–2021 · 12 papers🎓University of Massachusetts AmherstAmherst Center · United States2014–2020 · 12 papers🎓Montana State UniversityBozeman · United States1998–2003 · 10 papers🏢Merck & Co., Inc., Rahway, NJ, USARahway · United States2010–2011 · 6 papers🎓Stevens Institute of TechnologyHoboken · United States2019–2020 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution 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).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Named entity recognition · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Named entity recognition · 1 work

 Works by year

2020s

20201 paper

2010s

20171 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Fast and Accurate Entity Recognition with Iterated Dilated Convolutions (2017 · 548 citations)
    Bi-LSTM encoders, often paired with a CRF, are the standard approach to sequence tagging, but they process tokens one after another and cannot fully use GPU parallelism.
  2. Rethinking Attention with Performers (2020 · 491 citations)
    The standard Transformer scales poorly to long sequences: the attention mechanism requires time and memory that grow quadratically with the number of tokens L.

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. Fast and Accurate Entity Recognition with Iterated Dilated ConvolutionsConference on Empirical Methods in Natural Language Processing (EMNLP)Emma Strubell, Patrick Verga, David Belanger, et al.2017 · 548 citations
  2. Rethinking Attention with PerformersarXiv:2009.14794Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, et al.2020 · 491 citations
  3. Multilingual Relation Extraction using Compositional Universal Schema ↗Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetPatrick Verga et al.2016 · 139 citations
  4. Boundless: Generative Adversarial Networks for Image Extension ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetDilip Krishnan et al.2019 · 73 citations

 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 503 times (of the 149,439 papers whose bibliographies we read); 65 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/david-belanger/