most citedThe PIMMUR Principles: Ensuring Validity in Collective Behavior of LLM Societies

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cs.CL2026

On the Behavioral Traits of LLM Agents

Haokai Zhao, Jie Gao, Yunze Xiao +5

Users increasingly describe different AI agents as distinct colleagues to work with. AI personality research aims to quantify such impressions by attributing human- like "traits" t…

cs.CL2026

Agentopia: Long-Term Life Simulation and Learning in Agent Societies

Xintao Wang, Sirui Zheng, Hongqiu Wu +10

Humans learn from social life. Simulating this process with LLM-powered agents represents a promising research direction, raising a natural question: whether LLMs can learn from su…

cs.CL2026

Artificial Intolerance: Stigmatizing Language in Clinical Documentation Skews Large Language Model Decision-Making

Jen-tse Huang, Didi Zhou, Faith Kamau +5

Large Language Models (LLMs) are increasingly deployed in high-stakes domains such as clinical decision support and medical documentation. However, the robustness of these models a…

cs.CL2026

The Chameleon's Limit: Investigating Persona Collapse and Homogenization in Large Language Models

Yunze Xiao, Vivienne J. Zhang, Chenghao Yang +3

Large language models (LLMs) have powered multi-agent simulations such as survey respondents or application users. However, LLMs lack the population-level diversity required by the…

cs.CL2026

Knowing But Not Doing: Convergent Morality and Divergent Action in LLMs

Jen-tse Huang, Jiantong Qin, Xueli Qiu +3

Value alignment is central to the development of safe and socially compatible artificial intelligence. However, how Large Language Models (LLMs) represent and enact human values in…

cs.CL2026

HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns

Xintao Wang, Jian Yang, Weiyuan Li +8

Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona simulation and Role-Playing Langu…

cs.CL2025★ 1 cited

The PIMMUR Principles: Ensuring Validity in Collective Behavior of LLM Societies

Jiaxu Zhou, Jen-tse Huang, Xuhui Zhou +5

Large language models (LLMs) are increasingly used to simulate human collective behavior, yet claims that such simulations are human-like remain largely untested. We conducted a sy…