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Nino Vieillard

Nino Vieillard has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Efficient models & compression; often with Piotr Stanczyk, Alexandre Rame, Geoffrey Cideron.

2 papers in our library · 2023–2024

OpenAlex · h-index 10 · 32 works · 1,282 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 4,928 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #5542

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 States2019–2026 · 14 paperscurrent🎓Université de LorraineNancy · France2020–2022 · 6 papers🔬Institut Élie Cartan de LorraineVandœuvre-lès-Nancy · France2020–2022 · 5 papers🔬Centre National de la Recherche ScientifiqueParis · France2021–2022 · 4 papers🔬Institut national de recherche en sciences et technologies du numériqueLe Chesnay-Rocquencourt · France2021–2022 · 3 papers🎓Bar-Ilan UniversityRamat Gan · Israel2023 · 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 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Efficient models & compression · 2 worksLanguage models & pretraining · 2 works

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes (2023 · 299 citations)
    Distilling a large autoregressive language model into a smaller student usually means training on a fixed set of sequences, either ground-truth targets or outputs the teacher generated.
  2. BOND: Aligning LLMs with Best-of-N Distillation (2024 · 23 citations)
    Best-of-N sampling draws N responses from a reference model and keeps the one a reward model scores highest.

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. Gemma 2: Improving Open Language Models at a Practical Size ↗arXiv:2408.00118 · no summary yetGemma Team et al.2024 · 1,302 citations
  2. Gemma 3 Technical Report ↗arXiv:2503.19786 · no summary yetGemma Team et al.2025 · 1,147 citations
  3. On-Policy Distillation of Language Models: Learning from Self-Generated MistakesarXiv:2306.13649Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.2023 · 299 citations
  4. BOND: Aligning LLMs with Best-of-N DistillationarXiv:2407.14622Pier Giuseppe Sessa, Robert Dadashi, Leonard Hussenot, et al.2024 · 23 citations

 Co-authors here

11 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 4,928 times (of the 149,439 papers whose bibliographies we read); 1,234 citing papers with a page here →.

Updated

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