Granular Feedback: Leveraging Domain Expertise and Explainable AI to Effectively Steer Models

sponsorship: We would like to thank ZAVO, and Joke Vandepitte in particular, for allowing us to collaborate. We would like to thank FWO by facilitating this interdisciplinary research. Additionally, we would like to thank all participants for their time and valuable insights. This research is part of the research projects funded by KU Leuven (grant C14/21/072) and the Flanders AI Research Program (FAIR). (KU Leuven|C14/21/072, Flanders AI Research Program (FAIR))

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Publication Details

Published
2025-06-13
DOI
https://doi.org/10.1145/3699682.3728338
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
0.00

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article

Granular Feedback: Leveraging Domain Expertise and Explainable AI to Effectively Steer Models

Vero Vanden Abeele, Maxwell Szymanski, John Stamper, Katrien Verbert
Explainable Artificial Intelligence (XAI)
article

Granular Feedback: Leveraging Domain Expertise and Explainable AI to Effectively Steer Models

Vero Vanden Abeele, Maxwell Szymanski, John Stamper, Katrien Verbert
article en

Abstract

sponsorship: We would like to thank ZAVO, and Joke Vandepitte in particular, for allowing us to collaborate. We would like to thank FWO by facilitating this interdisciplinary research. Additionally, we would like to thank all participants for their time and valuable insights. This research is part of the research projects funded by KU Leuven (grant C14/21/072) and the Flanders AI Research Program (FAIR). (KU Leuven|C14/21/072, Flanders AI Research Program (FAIR))

Carnegie Mellon University (US), KU Leuven (BE)
KU Leuven
Openalex Percentile: Top 93%
Explainable Artificial Intelligence (XAI)
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