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Edouard Grave

Equal-contribution author of Meta's LLaMA paper; co-author of fastText and of Kyutai's Moshi

The November 2023 announcement of the Kyutai research lab describes Edouard Grave as a research scientist with experience in the corporate research labs Apple MLR and Facebook AI Research (FAIR), and says that at FAIR, Grave co-led the development of the LLaMA large language model and the fastText library. Grave is one of the equal-contribution authors of LLaMA: Open and Efficient Foundation Language Models (2023) and a co-author of the two 2016 fastText papers on subword word vectors and efficient text classification. Kyutai's team page lists Grave among its alumni with the title Chief Language Officer, and Grave co-authored Kyutai's Moshi speech-text foundation model paper (2024).123456

At a glance

Current role
None confirmed in the sources
Work listed
3
Sources cited
11
Profile reviewed

Career

Edouard Grave worked as a research scientist in two corporate research labs, Apple MLR and Facebook AI Research (FAIR). The November 2023 announcement of the Kyutai research lab says that at FAIR, Grave co-led the development of the LLaMA language model and of the fastText library.1

Grave was one of the founding researchers named when Kyutai, a non-profit open-science AI lab, launched in November 2023. Kyutai's team page now lists Grave among its alumni, with the title Chief Language Officer.15

Research

Grave co-authored the 2016 fastText papers on subword-aware word vectors and efficient text classification, and in 2019 co-authored CCNet, a pipeline for extracting high-quality monolingual datasets from Common Crawl. The fastText code was released under the MIT license.3478

With Gautier Izacard and colleagues, Grave worked on retrieval for language models: the 2020 Fusion-in-Decoder paper on combining passage retrieval with generative question answering, Contriever (2021) for unsupervised dense retrieval with contrastive learning, and Atlas (2022), a retrieval-augmented language model for few-shot learning.91011

Grave is one of the equal-contribution authors of LLaMA (2023), and at Kyutai co-authored the 2024 paper introducing Moshi, a speech-text foundation model for real-time, full-duplex spoken dialogue.26

Work and contributions

  • LLaMA Published research

    One of five equal-contribution authors of LLaMA: Open and Efficient Foundation Language Models (2023), whose author list gives a Meta AI affiliation; the Kyutai launch announcement says Grave co-led the development of LLaMA at FAIR.21

  • fastText Open-source code

    Co-author of Enriching Word Vectors with Subword Information (2016) and Bag of Tricks for Efficient Text Classification (2016); the fastText repository is published under the MIT License, and the Kyutai launch announcement says Grave co-led the library's development.3471

  • Moshi Published research

    Co-author of Moshi: a speech-text foundation model for real-time dialogue (2024), which introduces a full-duplex spoken dialogue framework and points to the kyutai-labs/moshi repository.6

Timeline

  1. Co-authored "Bag of Tricks for Efficient Text Classification", the fastText classification paper.4
  2. Co-authored "Enriching Word Vectors with Subword Information", the fastText word-vector paper.3
  3. Co-authored CCNet, a pipeline for extracting monolingual datasets from web crawl data.8
  4. Co-authored with Gautier Izacard the Fusion-in-Decoder paper on retrieval for open-domain question answering.9
  5. Co-authored Contriever, an unsupervised dense retriever trained with contrastive learning.10
  6. Co-authored Atlas, a retrieval-augmented language model for few-shot learning.11
  7. Equal-contribution author of the LLaMA foundation language model paper.2
  8. Named among the founding researchers at the launch of the Kyutai open-science AI lab.1
  9. Co-authored the Moshi speech-text foundation model paper at Kyutai.6

Documented roles

The sources do not confirm a current role; these are the roles they document.

Companies in their history

  • Meta 106 people in the wiki
  • Apple 27 people in the wiki

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References

11 sources · profile reviewed Oct 21, 2026 · data updated Oct 21, 2026

  1. Launch of Kyutai, an independent research lab dedicated to AI open science (founding announcement, team biographies)CMA CGM Group · Announcement · published Nov 17, 2023 · accessed Oct 21, 2026
  2. LLaMA: Open and Efficient Foundation Language Models (arXiv 2302.13971), author list and Meta AI affiliationarXiv · Paper · published Feb 27, 2023 · accessed Oct 21, 2026
  3. Enriching Word Vectors with Subword Information (arXiv 1607.04606)arXiv · Paper · published Jul 15, 2016 · accessed Oct 21, 2026
  4. Bag of Tricks for Efficient Text Classification (arXiv 1607.01759)arXiv · Paper · published Jul 6, 2016 · accessed Oct 21, 2026
  5. Kyutai — Team (alumni)Kyutai · Official page · accessed Oct 21, 2026
  6. Moshi: a speech-text foundation model for real-time dialogue (arXiv 2410.00037)arXiv · Paper · published Sep 17, 2024 · accessed Oct 21, 2026
  7. facebookresearch/fastText LICENSE (MIT)Meta (GitHub repository) · License · accessed Oct 21, 2026
  8. CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data (arXiv 1911.00359)arXiv · Paper · published Nov 1, 2019 · accessed Oct 21, 2026
  9. Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering (arXiv 2007.01282)arXiv · Paper · published Jul 2, 2020 · accessed Oct 21, 2026
  10. Unsupervised Dense Information Retrieval with Contrastive Learning (arXiv 2112.09118)arXiv · Paper · published Dec 16, 2021 · accessed Oct 21, 2026
  11. Atlas: Few-shot Learning with Retrieval Augmented Language Models (arXiv 2208.03299)arXiv · Paper · published Aug 5, 2022 · accessed Oct 21, 2026