44 citations · 105 across the 25 of their papers we have counts for
10 papers · 1 filter
EEG and Eye-Tracking Evidence That AI Disclosure Shapes Face Evaluation
Teodora Mitrevska, Luise Donat, Andreas Butz +3
AI-generated faces can be difficult to distinguish from real ones, leaving viewers to rely on source labels when judging an image. Yet prior work has made it difficult to separate…
How Did Writing Change At CHI? Analyzing 44 Years of CHI Writing Before and After the Introduction of Large Language Models
Thomas Kosch, Robin Welsch, Michael Hedderich +1
The availability of Large Language Models (LLMs) reshaped scientific discourse at a linguistic level. LLMs are assumed to homogenize academic writing, flattening it into a single g…
Available but Unclaimed: An Empirical Study of Human-AI Synergy
Robin Welsch, Michelle Rausch, Pascal Knierim +4
People increasingly reason with large language models (LLMs), yet complementary capabilities do not guarantee outperforming both components. In a between-subjects study, participan…
A Modular Workflow for Multimodal Reading Experiments
Thomas Krämer, Thomas Kosch, Dagmar Kern +1
We introduce a web-based modular workflow for real-time multimodal experiments in naturalistic online reading. The workflow integrates eye tracking, EEG, and interaction data from…
Topic Matters: How Linguistic Properties can Shape Reading Behaviour in Selective Exposure Studies
Thomas Krämer, Dagmar Kern, Thomas Kosch +1
Research on selective exposure frequently relies on eye tracking to study reading behaviour, often assuming that texts across different controversial topics are comparable once bas…
Explaining Too Much? Understanding How Large Language Model Reasoning Traces Influence Performance and Metacognition
Daniela Fernandes, Daniel Buschek, Lev Tankelevitch +2
Large Language Model interfaces are increasingly verbose, exposing intermediate reasoning traces alongside final answers. Traces are framed as transparency mechanisms, yet it is un…
LLM-Based Educational Simulation: Evaluating Temporal Student Persona Stability Across ADHD Profiles
Jana Gonnermann-Müller, Jennifer Haase, Nicolas Leins +2
Large language model (LLM)-based student simulation offers a scalable alternative for educational research, teacher training, and learner practice. However, its validity depends on…
Within-Model vs Between-Prompt Variability in Large Language Models for Creative Tasks
Jennifer Haase, Jana Gonnermann-Müller, Paul H. P. Hanel +4
How much of LLM output variance is explained by prompts versus model choice versus stochasticity through sampling? We answer this by evaluating 12 LLMs on 10 creativity prompts wit…
Escaping the Filter Bubble: Evaluating Electroencephalographic Theta Band Synchronization as Indicator for Selective Exposure in Online News Reading
Thomas Krämer, Daniel Hienert, Francesco Chiossi +2
Selective exposure to online news occurs when users favor information that confirms their beliefs, creating filter bubbles and limiting diverse perspectives. Interactive systems ca…
Stable Personas: Dual-Assessment of Temporal Stability in LLM-Based Human Simulation
Jana Gonnermann-Müller, Jennifer Haase, Nicolas Leins +2
Large Language Models (LLMs) acting as artificial agents offer the potential for scalable behavioral research, yet their validity depends on whether LLMs can maintain stable person…