Multi-modal Document Understanding

Multi-Modal Document Understanding is a document analysis framework that integrates and interprets complementary information from multiple data modalities—such as textual, visual, and layout features—within a single document to achieve a comprehensive, context-aware representation of its content and structure.

33

Publications

2.3K

Citations

174

Authors

35

Institutions

Publications per year

2017–2026

30

Authors

174

  1. FW
    Furu Wei

    Microsoft Research Asia (China), China

    7 publications · 792 citations

    7

    h-index

  2. YX
    Yiheng Xu

    Microsoft Research Asia (China), China

    7 publications · 792 citations

    7

    h-index

  3. GW
    Guoxin Wang

    Beijing Institute of Technology, China

    4 publications · 644 citations

    4

    h-index

  4. CZ
    Cha Zhang

    Microsoft (United States), United States

    4 publications · 644 citations

    4

    h-index

  5. LC
    Lei Cui

    Northwest University, China

    3 publications · 267 citations

    3

    h-index

1–5 of 174

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 236 citations

    9

    h-index

  2. Proceedings of the 30th ACM International Conference on Multimedia

    Conference · 2 publications · 47 citations

    2

    h-index

  3. Pattern Recognition

    2 publications · 86 citations

    2

    h-index

  4. 1

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 45 citations

    1

    h-index

1–5