Adaptive Generative Systems

Adaptive Generative Systems is a class of generative systems that dynamically modifies its internal parameters or structure in response to input conditions, user interactions, or environmental feedback to improve output quality, relevance, or functionality over time.

11

Publications

468

Citations

41

Authors

18

Institutions

Publications per year

2017–2026

6

Authors

41

  1. IM
    Irene M. Herremans

    University of Calgary, Canada

    1 publications · 31 citations

    1

    h-index

  2. JW
    Junliang Wang

    Donghua University, China

    1 publications · 139 citations

    1

    h-index

  3. PD
    Paolo Di Lorenzo

    Sapienza University of Rome, Italy

    1 publications · 38 citations

    1

    h-index

  4. SB
    Shlomo Berkovsky

    Commonwealth Scientific and Industrial Research Organisation, Australia

    1 publications · 53 citations

    1

    h-index

  5. YS
    Yang Song

    The University of Sydney, Australia

    1 publications · 53 citations

    1

    h-index

1–5 of 41

Venues

  1. Journal of Economic Behavior & Organization

    1 publications · 34 citations

    1

    h-index

  2. The Learning Organization

    1 publications · 31 citations

    1

    h-index

  3. Medical Image Analysis

    1 publications · 53 citations

    1

    h-index

  4. 1

    h-index

  5. Designing Interactive Systems Conference

    Conference · 1 publications · 17 citations

    1

    h-index

1–5