Feedback-driven Generation

Feedback-Driven Generation is a generative methodology within interactive systems that iteratively refines output through continuous integration of user or system-provided feedback as a primary mechanism for adaptive content creation.

46

Publications

2.5K

Citations

180

Authors

69

Institutions

Publications per year

2017–2026

26

Authors

180

  1. DG
    Dragan Gašević

    Monash University, Australia

    4 publications · 413 citations

    4

    h-index

  2. GC
    Guanliang Chen

    Monash University, Australia

    3 publications · 403 citations

    3

    h-index

  3. YT
    Yi‐Shan Tsai

    Monash University, Australia

    3 publications · 403 citations

    3

    h-index

  4. JL
    Jionghao Lin

    Monash University, Australia

    3 publications · 403 citations

    3

    h-index

  5. TR
    Thomas Reps

    University of Wisconsin–Madison, United States

    3 publications · 537 citations

    3

    h-index

1–5 of 180

Venues

  1. ACM SIGPLAN Notices

    2 publications · 390 citations

    2

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  2. arXiv (Cornell University)

    Repository · 2 publications · 226 citations

    2

    h-index

  3. Journal of Learning Analytics

    1 publications · 10 citations

    1

    h-index

  4. Assessment & Evaluation in Higher Education

    1 publications · 80 citations

    1

    h-index

  5. IEEE Transactions on Big Data

    1 publications · 43 citations

    1

    h-index

1–5