Paragraph Embeddings

Paragraph Embeddings is a text representation technique that captures the semantic meaning of an entire paragraph as a fixed-dimensional vector, distinguishing it from word or sentence embeddings by modeling broader contextual coherence and discourse structure across multiple sentences.

36

Publications

8.2K

Citations

137

Authors

57

Institutions

Publications per year

2017–2026

28

Variants

Paragraph VectorParagraph Vectors

Authors

137

  1. JL
    Jiwei Li

    Stanford University, United States

    2 publications · 726 citations

    2

    h-index

  2. QV
    Quoc V. Le

    Google (United States), United States

    2 publications · 5.4K citations

    2

    h-index

  3. JG
    Jiafeng Guo

    Chinese Academy of Sciences, China

    2 publications · 103 citations

    2

    h-index

  4. QA
    Qingyao Ai

    Tsinghua University, China

    2 publications · 103 citations

    2

    h-index

  5. DJ
    Dan Jurafsky

    Stanford University, United States

    2 publications · 726 citations

    2

    h-index

1–5 of 137

Venues

  1. arXiv (Cornell University)

    Repository · 7 publications · 5.8K citations

    7

    h-index

  2. IEEE Access

    2 publications · 61 citations

    2

    h-index

  3. Applied Soft Computing

    1 publications · 34 citations

    1

    h-index

  4. Mathematics

    1 publications · 17 citations

    1

    h-index

  5. Information Processing & Management

    1 publications · 43 citations

    1

    h-index

1–5