9 citations · 18 across the 11 of their papers we have counts for
5 papers · 1 filter
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…
Measuring what Matters: Construct Validity in Large Language Model Benchmarks
Andrew M. Bean, Ryan Othniel Kearns, Angelika Romanou +39
Evaluating large language models (LLMs) is crucial for both assessing their capabilities and identifying safety or robustness issues prior to deployment. Reliably measuring abstrac…
Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations
Anka Reuel, Avijit Ghosh, Jenny Chim +32
Foundation models are increasingly central to high-stakes AI systems, and governance frameworks now depend on evaluations to assess their risks and capabilities. Although general c…
Oversight Structures for Agentic AI in Public-Sector Organizations
Chris Schmitz, Jonathan Rystrøm, Jan Batzner
This paper finds that the introduction of agentic AI systems intensifies existing challenges to traditional public sector oversight mechanisms -- which rely on siloed compliance un…