Preference-guided Design Generation

Preference-Guided Design Generation is a generative design framework that integrates user or model-derived preferences as explicit guidance signals to steer the exploration and synthesis of design alternatives, distinguishing itself from conventional generative methods by prioritizing iterative alignment with evolving subjective or contextual criteria.

16

Publications

1K

Citations

59

Authors

22

Institutions

Publications per year

2017–2026

6

Authors

59

  1. XM
    Xiaojuan Ma

    Hong Kong University of Science and Technology, Hong Kong SAR China

    1 publications · 17 citations

    1

    h-index

  2. JL
    Jerry Liu

    Hewlett-Packard (United States), United States

    1 publications · 60 citations

    1

    h-index

  3. CW
    Chao Wu

    Zhejiang University, China

    1 publications · 10 citations

    1

    h-index

  4. WP
    William P. Birmingham

    University of Michigan, United States

    1 publications · 31 citations

    1

    h-index

  5. PS
    Pratyush Sen

    Newcastle University, United Kingdom

    1 publications · 17 citations

    1

    h-index

1–5 of 59

Venues

  1. Design Studies

    2 publications · 396 citations

    2

    h-index

  2. Journal of Mechanical Design

    1 publications · 20 citations

    1

    h-index

  3. 1

    h-index

  4. Journal of Engineering Design

    1 publications · 17 citations

    1

    h-index

  5. 1

    h-index

1–5