activity
20172025
most citedFast camera focus estimation for gaze-based focus control

38 citations · 127 across the 16 of their papers we have counts for

collaborators

31 papers

cs.AI20258 cited

Towards Adaptive Feedback with AI: Comparing the Feedback Quality of LLMs and Teachers on Experimentation Protocols

Kathrin Seßler, Arne Bewersdorff, Claudia Nerdel +1

Effective feedback is essential for fostering students' success in scientific inquiry. With advancements in artificial intelligence, large language models (LLMs) offer new possibil…

cs.CY2025

Europe's AI Imperative -- A Pragmatic Blueprint for Global Tech Leadership

Gjergji Kasneci, Urs Gasser, Thomas F. Hofmann +5

Europe is at a make-or-break moment in the global AI race, squeezed between the massive venture capital and tech giants in the US and China's scale-oriented, top-down drive. At thi…

cs.HC2024

Wrapped in Anansi's Web: Unweaving the Impacts of Generative-AI Personalization and VR Immersion in Oral Storytelling

Ka Hei Carrie Lau, Bhada Yun, Samuel Saruba +2

Oral traditions, vital to cultural identity, are losing relevance among youth due to the dominance of modern media. This study addresses the revitalization of these traditions by r…

cs.HC20241 cited

DataliVR: Transformation of Data Literacy Education through Virtual Reality with ChatGPT-Powered Enhancements

Hong Gao, Haochun Huai, Sena Yildiz-Degirmenci +2

Data literacy is essential in today's data-driven world, emphasizing individuals' abilities to effectively manage data and extract meaningful insights. However, traditional classro…

cs.CV202214 cited

Where and What: Driver Attention-based Object Detection

Yao Rong, Naemi-Rebecca Kassautzki, Wolfgang Fuhl +1

Human drivers use their attentional mechanisms to focus on critical objects and make decisions while driving. As human attention can be revealed from gaze data, capturing and analy…

cs.HC20226 cited

User Trust on an Explainable AI-based Medical Diagnosis Support System

Yao Rong, Nora Castner, Efe Bozkir +1

Recent research has supported that system explainability improves user trust and willingness to use medical AI for diagnostic support. In this paper, we use chest disease diagnosis…