arXiv:2608.22582v1 Announce Type: cross
Abstract: Large-scale population surveys are essential for generating robust social and scientific insights, yet they face significant challenges, including de...
By Julia Romberg, Tobias Gummer, Gabriella Lapesa, Tanja Kunz, Claudia Wagner
arXiv:2610.23149v1 Announce Type: cross
Abstract: Large language model chatbots have been proposed as AI-interviewers for collecting qualitative interview data at scale, potentially bridging social s...
By Semra Guven, Tobias G{\aa}rdhus, Andreas Bjerre-Nielsen, Anna Rogers, Hjalmar Bang Carlsen
arXiv:2605.10659v3 Announce Type: replace
Abstract: Digital personas powered by Large Language Models (LLMs) are increasingly proposed as substitutes for human survey respondents, yet it remains uncl...
By Mumin Jia, Yilin Chen, Divya Sharma, Jairo Diaz-Rodriguez
arXiv:2607. 10628v1 Announce Type: cross Abstract: We present Anamnesis, an interactive system for demographically controllable survey simulation using large language models.
By Song-Ze Yu, Joseph Suh, Serina Chang, David M. Chan
InterviewPlayground is a simulation environment designed to evaluate AI interviewers by using simulated participants whose behaviors are grounded in social theory. The platform generates an InterviewReportCard that assesses AI interviewers across validated measures. Empirical validation shows that performance in InterviewPlayground predicts human study outcomes with a Pearson correlation of 0.86, supporting its use for assessing AI interviewer performance and failure modes.
By Jonathan Ivey, Aimee Liang, Arthur Y. S. Wang, Madeline Mandell, Ziang Xiao, Anjalie Field
ExpertIVS is a framework that uses 14 sociological expert agents to interpret World Values Survey responses, reconstructing individual value systems in a coherent, internally consistent manner rather than simply concatenating survey answers. It introduces a multi‑agent debate mechanism to assess LLM alignment with these value profiles during dynamic interactions. Experiments on 480 individuals from 12 countries show a 90.78% value restoration fidelity and a 5.3% improvement in value generalization over baseline methods, while also demonstrating strong personality discriminability and behavioral consistency.
By Zhen Wang, Yuqi Ren, Yuehan Cui, Hongxiang Wang, Jianxiang Peng, Zhaoxia Zhang, Bingkun Zhu, Tongxuan Zhang, Dezhi Tong, Deyi Xiong