activity
20242026
collaborators

7 papers

cs.CY2026

Uncovering Salience-Driven Dynamics in Consumer Confidence with Generative Social Simulation

Yixu Huang, Yunlu Yin, Jiayu Lin +6

Consumer confidence is typically modeled as a persistent macroeconomic index, yet its movements arise from households that interpret economic information through heterogeneous cons…

cs.CL2026

Revising Context, Shifting Simulated Stance: Auditing LLM-Based Stance Simulation in Online Discussions

Xinnong Zhang, Wanting Shan, Hanjia Lyu +2

Large language models are increasingly used to simulate social media users and infer how individuals may respond to online discussions. However, it remains unclear whether these si…

cs.CL2025

SocioVerse: A World Model for Social Simulation Powered by LLM Agents and A Pool of 10 Million Real-World Users

Xinnong Zhang, Jiayu Lin, Xinyi Mou +18

Social simulation is transforming traditional social science research by modeling human behavior through interactions between virtual individuals and their environments. With recen…

cs.CL2024

AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Models

Xiawei Liu, Shiyue Yang, Xinnong Zhang +6

The rise of various social platforms has transformed journalism. The growing demand for news content has led to the increased use of large language models (LLMs) in news production…

cs.CL2024

From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents

Xinyi Mou, Xuanwen Ding, Qi He +8

Traditional sociological research often relies on human participation, which, though effective, is expensive, challenging to scale, and with ethical concerns. Recent advancements i…

cs.CL2024

AgentSense: Benchmarking Social Intelligence of Language Agents through Interactive Scenarios

Xinyi Mou, Jingcong Liang, Jiayu Lin +8

Large language models (LLMs) are increasingly leveraged to empower autonomous agents to simulate human beings in various fields of behavioral research. However, evaluating their ca…