3 papers
cs.AI2026
When Can LLM Digital Twins Reduce Human Measurement? From Behavioral Fidelity to Statistical Substitutability
Steven Wang, Kyle Hunt, Shaojie Tang +1
LLM-based digital twins promise to reduce repeated human data collection by generating person- specific responses, yet existing evaluations provide little evidence about whether th…
cs.CL2025
Can Finetuing LLMs on Small Human Samples Increase Heterogeneity, Alignment, and Belief-Action Coherence?
Steven Wang, Kyle Hunt, Shaojie Tang +1
There is ongoing debate about whether large language models (LLMs) can serve as substitutes for human participants in survey and experimental research. While recent work in fields…
stat.ME2025
Identifying Subgroup and Context Effects in Conjoint Experiments
Steven Wang, Isys Johnson, Jessica Grogan +4
Conjoint experiments have become central to survey research in political science and related fields because they allow researchers to study preferences across multiple attributes s…