11 papers
When Thinking Pays Off: Incentive Alignment for Human-AI Collaboration
Joshua Holstein, Patrick Hemmer, Gerhard Satzger +1
Collaboration with artificial intelligence (AI) has improved human decision-making across various domains by leveraging the complementary capabilities of humans and AI. Yet, humans…
From Model Uncertainty to Human Attention: Localization-Aware Visual Cues for Scalable Annotation Review
Moussa Kassem Sbeyti, Joshua Holstein, Philipp Spitzer +2
High-quality labeled data is essential for training robust machine learning models, yet obtaining annotations at scale remains expensive. AI-assisted annotation has therefore becom…
Development of Mental Models in Human-AI Collaboration: A Conceptual Framework
Joshua Holstein, Gerhard Satzger
Artificial intelligence has become integral to organizational decision-making and while research has explored many facets of this human-AI collaboration, the focus has mainly been…
Data Quality Challenges in Retrieval-Augmented Generation
Leopold Müller, Joshua Holstein, Sarah Bause +2
Organizations increasingly adopt Retrieval-Augmented Generation (RAG) to enhance Large Language Models with enterprise-specific knowledge. However, current data quality (DQ) framew…
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…