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    Language, speech & LLMs· 2014

    GloVe: Global Vectors for Word Representation

    Jeffrey Pennington (first author) · 2014

    Read the original

    DOI 10.3115/v1/d14-1162OpenAlex W2250539671

    On the reading lists

    Why it matters

    Combined global word co-occurrence statistics with vector learning, establishing influential pretrained embeddings.

    Condensed from the expert lists' notes.

    The record

    First released
    2014 (from OpenAlex)
    Citations
    35,748 citations, as counted by Semantic Scholar logoSemantic Scholar (non-commercial licence)
    Awards
    ACL Test of Time
    Named by
    both expert lists
    Also relevant to
    Computer vision & multimodal
    Score
    0.774 · computed rank 19 · consensus 0.81, must-read 0, citations percentile 0.944 (2010s · language), awards 1, existing lists 0.5. 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), and Semantic Scholar logoSemantic Scholar (used under its non-commercial API licence). Each count names its source. See the method.