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20242026
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cs.CL2026

Identity, Cooperation and Framing Effects within Groups of Real and Simulated Humans

Suhong Moon, Minwoo Kang, Joseph Suh +2

Humans act via a nuanced process that depends both on rational deliberation and also on identity and contextual factors. In this work, we study how large language models (LLMs) can…

cs.CL2025

Graph-Based Alternatives to LLMs for Human Simulation

Joseph Suh, Suhong Moon, Serina Chang

Large language models (LLMs) have become a popular approach for simulating human behaviors, yet it remains unclear if LLMs are necessary for all simulation tasks. We study a broad…

cs.CL2025

Deep Binding of Language Model Virtual Personas: a Study on Approximating Political Partisan Misperceptions

Minwoo Kang, Suhong Moon, Seung Hyeong Lee +4

Large language models (LLMs) are increasingly capable of simulating human behavior, offering cost-effective ways to estimate user responses to various surveys and polls. However, t…

cs.CL2025

Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions

Joseph Suh, Erfan Jahanparast, Suhong Moon +2

Large language models (LLMs) present novel opportunities in public opinion research by predicting survey responses in advance during the early stages of survey design. Prior method…

cs.CL2024

Rediscovering the Latent Dimensions of Personality with Large Language Models as Trait Descriptors

Joseph Suh, Suhong Moon, Minwoo Kang +1

Assessing personality traits using large language models (LLMs) has emerged as an interesting and challenging area of research. While previous methods employ explicit questionnaire…