57 citations · 75 across the 11 of their papers we have counts for
12 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…
Transferring Domain Knowledge with (X)AI-Based Learning Systems
Philipp Spitzer, Niklas Kühl, Marc Goutier +2
In numerous high-stakes domains, training novices via conventional learning systems does not suffice. To impart tacit knowledge, experts' hands-on guidance is imperative. However,…
Understanding Data Understanding: A Framework to Navigate the Intricacies of Data Analytics
Joshua Holstein, Philipp Spitzer, Marieke Hoell +2
As organizations face the challenges of processing exponentially growing data volumes, their reliance on analytics to unlock value from this data has intensified. However, the intr…
Human Delegation Behavior in Human-AI Collaboration: The Effect of Contextual Information
Philipp Spitzer, Joshua Holstein, Patrick Hemmer +4
The integration of artificial intelligence (AI) into human decision-making processes at the workplace presents both opportunities and challenges. One promising approach to leverage…
Towards Effective Human-AI Decision-Making: The Role of Human Learning in Appropriate Reliance on AI Advice
Max Schemmer, Andrea Bartos, Philipp Spitzer +4
The true potential of human-AI collaboration lies in exploiting the complementary capabilities of humans and AI to achieve a joint performance superior to that of the individual AI…
The Impact of Imperfect XAI on Human-AI Decision-Making
Katelyn Morrison, Philipp Spitzer, Violet Turri +3
Explainability techniques are rapidly being developed to improve human-AI decision-making across various cooperative work settings. Consequently, previous research has evaluated ho…
ML-Based Teaching Systems: A Conceptual Framework
Philipp Spitzer, Niklas Kühl, Daniel Heinz +1
As the shortage of skilled workers continues to be a pressing issue, exacerbated by demographic change, it is becoming a critical challenge for organizations to preserve the knowle…
On the Perception of Difficulty: Differences between Humans and AI
Philipp Spitzer, Joshua Holstein, Michael Vössing +1
With the increased adoption of artificial intelligence (AI) in industry and society, effective human-AI interaction systems are becoming increasingly important. A central challenge…
Training Novices: The Role of Human-AI Collaboration and Knowledge Transfer
Philipp Spitzer, Niklas Kühl, Marc Goutier
Across a multitude of work environments, expert knowledge is imperative for humans to conduct tasks with high performance and ensure business success. These humans possess task-spe…