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    Language, speech & LLMs· 2023

    LLaMA: Open and Efficient Foundation Language Models

    Hugo Touvron (first author) · 2023

    Read the original

    arXiv 2302.13971OpenAlex W4322718191

    On the reading lists

    Why it matters

    Catalyzed the modern open-weight LLM ecosystem and efficient small-model research.

    Condensed from the expert lists' notes.

    The record

    First released
    2023 (from arXiv 2302.13971)
    Citations
    22,056 citations, as counted by Papers With Code (CC BY-SA 4.0)
    Named by
    both expert lists
    Score
    0.694 · computed rank 76 · consensus 0.85, must-read 1, citations percentile 0.969 (2020s · language), awards 0, existing lists 0. Method

    Editor's notes

    • Readability check: fail: A model release report; its lasting ideas are better learned from the scaling-law papers. (AI draft (Claude), not yet reviewed, 2026-10-29)

    Data sources

    Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.