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Stéphane Clinchant

Stéphane Clinchant has 2 papers in our library, in 2021, most of them on Information retrieval & search; often with Benjamin Piwowarski, Thibault Formal.

2 papers in our library · 2021

OpenAlex · ORCID · Wikidata · h-index 22 · 135 works · 2,012 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 190 times in our library · ⭐ Paper Stars ranking: #3486

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

🏢NaverSeongnam-si · South Korea2019–2026 · 15 paperscurrent🏢XeroxSaint-Denis · France2008–2016 · 15 papers🔬Laboratoire d'Informatique de GrenobleGrenoble · France2009–2012 · 8 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 6The 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 worksInformation Systems · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Information retrieval & search · 2 works

💡 Concepts 1Key ideas and methods explained on our concept pages.Inverted index · 1 work

 Works by year

2020s

20212 papers

 Papers

The most cited first (OpenAlex and our library).

  1. SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking (2021 · 512 citations)
    First-stage retrieval must pull candidate passages from a huge collection quickly. Classic bag-of-words rankers such as BM25 are fast because they use inverted indexes, but they miss relevant texts that phrase things differently from the query. Dense BERT retrievers handle that vocabulary mismatch, but they depend on…
  2. SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval (2021 · 83 citations)
    First-stage retrieval needs to be both accurate and fast. Dense retrievers do well but lack explicit term matching. Learned sparse models keep the benefits of bag-of-words search, such as inverted indexes, exact matching and interpretability. This paper improves SPLADE, a sparse model that turns BERT MLM logits into…

 Co-authors here

2 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 190 times (of the 149,439 papers whose bibliographies we read); 33 citing papers with a page here →.

Updated

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