collaborators

7 papers

cs.MA2026

EduMirror: Modeling Educational Social Dynamics with Value-driven Multi-agent Simulation

Jingzhe Lin, Hengbin Yu, Yongdan Zeng +1

Understanding how educational social dynamics evolve is critical for informing effective educational policies and counterfactual interventions. However, traditional methods face a…

cs.MA2026

Beyond Self-Interest: Modeling Social-Oriented Motivation for Human-like Multi-Agent Interactions

Jingzhe Lin, Ceyao Zhang, Yaodong Yang +3

Large Language Models (LLMs) demonstrate significant potential for generating complex behaviors, yet most approaches lack mechanisms for modeling social motivation in human-like mu…

cs.MA2026

How do Role Models Shape Collective Morality? Exemplar-Driven Moral Learning in Multi-Agent Simulation

Junjie Liao, Huacong Tang, Zhou Ziheng +2

Do We Need Role Models? How do Role Models Shape Collective Morality? To explore the questions, we build a multi-agent simulation powered by a Large Language Model, where agents wi…

cs.CY2026

Simple Role Assignment is Extraordinarily Effective for Safety Alignment

Zhou Ziheng, Jiakun Ding, Zhaowei Zhang +6

Principle-based alignment often lacks context sensitivity and completeness. Grounded in Theory of Mind, we propose role conditioning as a compact alternative: social roles (e.g., m…

cs.AI2025

Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia

Chandler Smith, Marwa Abdulhai, Manfred Diaz +83

Large Language Model (LLM) agents have demonstrated impressive capabilities for social interaction and are increasingly being deployed in situations where they might engage with bo…

cs.MA2025

Why Are We Moral? An LLM-based Agent Simulation Approach to Study Moral Evolution

Zhou Ziheng, Huacong Tang, Mingjie Bi +7

The evolution of morality presents a puzzle: natural selection should favor self-interest, yet humans developed moral systems promoting altruism. Traditional approaches must abstra…

cs.CL2025

Are the Values of LLMs Structurally Aligned with Humans? A Causal Perspective

Yipeng Kang, Junqi Wang, Yexin Li +8

As large language models (LLMs) become increasingly integrated into critical applications, aligning their behavior with human values presents significant challenges. Current method…