Multimodal Inference

Multimodal Inference is a cognitive process within inferential comprehension that integrates and interprets information from multiple representational modes—such as linguistic, visual, auditory, and gestural inputs—to generate coherent, implicit understandings that transcend the individual modalities.

61

Publications

2.7K

Citations

313

Authors

125

Institutions

Publications per year

2017–2026

44

Authors

313

  1. DH
    Demis Hassabis

    Google DeepMind (United Kingdom), United Kingdom

    3 publications · 116 citations

    3

    h-index

  2. MB
    Matthew Botvinick

    Princeton University, United States

    3 publications · 116 citations

    3

    h-index

  3. CB
    Christopher Burgess

    Menzies School of Health Research, Australia

    3 publications · 116 citations

    3

    h-index

  4. IH
    Irina Higgins

    Google (United States), United States

    3 publications · 116 citations

    3

    h-index

  5. NS
    Nicolas Sonnerat

    Google DeepMind (United Kingdom), United Kingdom

    3 publications · 116 citations

    3

    h-index

1–5 of 313

Venues

  1. arXiv (Cornell University)

    Repository · 12 publications · 566 citations

    12

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 74 citations

    3

    h-index

  3. Information Fusion

    2 publications · 139 citations

    2

    h-index

  4. Psychonomic Bulletin & Review

    1 publications · 70 citations

    1

    h-index

  5. Topics in Cognitive Science

    1 publications · 51 citations

    1

    h-index

1–5