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    Language, speech & LLMs· 2021

    Evaluating Large Language Models Trained on Code

    Mark Chen (first author) · 2021

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    arXiv 2107.03374OpenAlex W3177813494

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    Why it matters

    Established executable code-generation evaluation and demonstrated practical program synthesis with LLMs.

    Condensed from the expert lists' notes.

    The record

    First released
    2021 (from arXiv 2107.03374)
    Citations
    12,149 citations, as counted by Papers With Code (CC BY-SA 4.0)
    Named by
    both expert lists
    Score
    0.443 · computed rank 303 · consensus 0.29, must-read 0.5, citations percentile 0.875 (2020s · language), awards 0, existing lists 0. Method

    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.