Neural Text Representation

Neural Text Representation is a computational method for encoding textual data into distributed vector representations through deep learning architectures, distinguished by its reliance on neural network models to automatically capture semantic and syntactic patterns from raw text.

1.9K

Publications

214K

Citations

5.3K

Authors

1.3K

Institutions

Publications per year

2017–2026

1.5K

Authors

5.3K

  1. XQ
    Xipeng Qiu

    Fudan University, China

    19 publications · 1.4K citations

    15

    h-index

  2. XH
    Xuanjing Huang

    Fudan University, China

    16 publications · 1K citations

    13

    h-index

  3. RS
    Ruslan Salakhutdinov

    Carnegie Mellon University, United States

    12 publications · 3.7K citations

    12

    h-index

  4. YZ
    Yue Zhang

    Westlake University, China

    13 publications · 1.1K citations

    12

    h-index

  5. YJ
    Yangfeng Ji

    University of Virginia, United States

    11 publications · 681 citations

    11

    h-index

1–5 of 5.3K

Venues

  1. arXiv (Cornell University)

    Repository · 300 publications · 63.5K citations

    74

    h-index

  2. IEEE Access

    56 publications · 3K citations

    31

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 47 publications · 2.8K citations

    28

    h-index

  4. International Conference on Computational Linguistics

    Conference · 28 publications · 1.7K citations

    21

    h-index

  5. Information Processing & Management

    15 publications · 1.2K citations

    15

    h-index

1–5