4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.HC2026
Generics in science communication: Misaligned interpretations across laypeople, scientists, and large language models
Uwe Peters, Andrea Bertazzoli, Jasmine M. DeJesus +2
Scientists often use generics, that is, unquantified statements about whole categories of people or phenomena, when communicating research findings (e.g., "statins reduce cardiovas…
cs.CL2025★ 1 cited
Generalization Bias in Large Language Model Summarization of Scientific Research
Uwe Peters, Benjamin Chin-Yee
Artificial intelligence chatbots driven by large language models (LLMs) have the potential to increase public science literacy and support scientific research, as they can quickly…
cs.HC2024★ 4 cited
Cultural Bias in Explainable AI Research: A Systematic Analysis
Uwe Peters, Mary Carman
For synergistic interactions between humans and artificial intelligence (AI) systems, AI outputs often need to be explainable to people. Explainable AI (XAI) systems are commonly t…