4 papers
Honey, I Shrunk the Language Model: Impact of Knowledge Distillation Methods on Performance and Explainability
Daniel Hendriks, Philipp Spitzer, Niklas Kühl +1
Artificial Intelligence (AI) has increasingly influenced modern society, recently in particular through significant advancements in Large Language Models (LLMs). However, high comp…
Towards Human-Understandable Multi-Dimensional Concept Discovery
Arne Grobrügge, Niklas Kühl, Gerhard Satzger +1
Concept-based eXplainable AI (C-XAI) aims to overcome the limitations of traditional saliency maps by converting pixels into human-understandable concepts that are consistent acros…
Towards a Problem-Oriented Domain Adaptation Framework for Machine Learning
Philipp Spitzer, Dominik Martin, Laurin Eichberger +1
Domain adaptation is a sub-field of machine learning that involves transferring knowledge from a source domain to perform the same task in the target domain. It is a typical challe…
Don't be Fooled: The Misinformation Effect of Explanations in Human-AI Collaboration
Philipp Spitzer, Joshua Holstein, Katelyn Morrison +3
Across various applications, humans increasingly use black-box artificial intelligence (AI) systems without insight into these systems' reasoning. To counter this opacity, explaina…