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Lysandre Debut

Lysandre Debut has 2 papers in our library, in 2019–2020, most of them on Efficient models & compression; often with Julien Chaumond, Thomas Wolf, Victor Sanh.

2 papers in our library · 2019–2020

OpenAlex · h-index 4 · 9 works · 12,615 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 10,234 times in our library · ⭐ Paper Stars ranking: #115

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

🏢Hugging FaceNew York · United States2019–2021 · 6 paperscurrent

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

 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.Efficient models & compression · 1 work

💡 Concepts 2Key ideas and methods explained on our concept pages.Natural language processing · 1 workTransformer and attention · 1 work

 Works by year

2020s

20201 paper

2010s

20191 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Transformers: State-of-the-Art Natural Language Processing (2020 · 15,755 citations)
    Pretrained Transformer models now drive much of the progress in NLP. Using them in practice raises engineering problems: sharing weights, adapting them to new tasks, comparing architectures fairly, and serving them efficiently. The paper presents Transformers, Hugging Face's open-source library released under Apache…
  2. DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter (2019 · 6,751 citations)
    Large pre-trained language models such as BERT deliver high quality. However, they require a lot of memory and computation, which makes them hard to run on smartphones or on a limited budget. The authors from Hugging Face propose DistilBERT: a compact general-purpose model obtained through knowledge distillation…

 Co-authors here

5 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 10,234 times (of the 149,439 papers whose bibliographies we read); 1,291 citing papers with a page here →.

Updated

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