4 citations · 8 across the 5 of their papers we have counts for
5 papers
Sycophancy Claims about Language Models: The Missing Human-in-the-Loop
Jan Batzner, Volker Stocker, Stefan Schmid +1
Sycophantic response patterns in Large Language Models (LLMs) have been increasingly claimed in the literature. We review methodological challenges in measuring LLM sycophancy and…
Whose Personae? Synthetic Persona Experiments in LLM Research and Pathways to Transparency
Jan Batzner, Volker Stocker, Bingjun Tang +4
Synthetic personae experiments have become a prominent method in Large Language Model alignment research, yet the representativeness and ecological validity of these personae vary…
LeMat-Synth: a multi-modal toolbox to curate broad synthesis procedure databases from scientific literature
Magdalena Lederbauer, Siddharth Betala, Valerie Gentzke +22
Wide access to advanced experimental methods in materials science has given rise to an abundance of procedural knowledge, which is scattered across decades of scientific literature…
Communication Bias in Large Language Models: A Regulatory Perspective
Adrian Kuenzler, Stefan Schmid
Large language models (LLMs) are increasingly central to many applications, raising concerns about bias, fairness, and regulatory compliance. This paper reviews risks of biased out…
GermanPartiesQA: Benchmarking Commercial Large Language Models and AI Companions for Political Alignment and Sycophancy
Jan Batzner, Volker Stocker, Stefan Schmid +1
Large language models (LLMs) are increasingly shaping citizens' information ecosystems. Products incorporating LLMs, such as chatbots and AI Companions, are now widely used for dec…