collaborators

19 papers

cs.AI2026

Automated reproducibility assessments in the social and behavioral sciences using large language models

Tobias Holtdirk, Pietro Marcolongo, Anna Steinberg Schulten +7

Reproducibility in the social and behavioral sciences is typically evaluated by independent researchers who reanalyze the original data to assess whether the published findings can…

cs.HC2026

AI Conversational Interviewing: Scaling Up Semi-Structured and In-depth Interviews

Alexander Wuttke, Max Melchior Lang, Christopher Klamm +2

Public opinion research has long faced a trade-off between depth and scale: standardized surveys enable large-scale measurement but restrict respondents to researcher-defined categ…

cs.LG2026

How Hard is it to Rig a Benchmark? A Social Choice Analysis of Leaderboard Robustness

Polina Gordienko, Georg Schollmeyer, Frauke Kreuter +1

Multi-task benchmarks have become a central pillar of machine learning research, yet their growing influence has incentivised benchmark gaming -- strategic actions taken to improve…

stat.ME2026

From Ground Truth to Measurement: A Statistical Framework for Human Labeling

Robert Chew, Stephanie Eckman, Christoph Kern +1

Supervised machine learning assumes that labeled data provide accurate measurements of the concepts models are meant to learn. Yet in practice, human labeling introduces systematic…

cs.CL2026

Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social Simulation

Bolei Ma, Yong Cao, Indira Sen +4

Large Language Models (LLMs) are increasingly used to simulate public opinion and other social phenomena. Most current studies constrain these simulations to multiple-choice or sho…

cs.CY2026

Reading Between the Tokens: Improving Preference Predictions through Mechanistic Forecasting

Sarah Ball, Simeon Allmendinger, Niklas Kühl +2

Large language models are increasingly used to predict human preferences in both scientific and business endeavors, yet current approaches rely exclusively on analyzing model outpu…