arXiv AI
Modeling Social Dynamics with an LLM-Enabled Agent Based Network-Dynamic (LAND) Model
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arXiv AI
Oct 27
LLM-Augmented Agent-Based Simulation of Cyber Social Agents
The paper introduces the concept of Cyber Social Agents (CSAs), automated actors on social media defined by a taxonomy of archetypes based on operational tactics and rhetorical style. It integrates this taxonomy into a large language model (LLM)-driven simulation where agents interact within a network, allowing the study of how diverse agent types influence information diffusion and social influence. The approach bridges rule‑based agent models and LLM‑powered simulations by parameterizing generated agents with empirically grounded CSA personas.
arXiv AI
Jun 30
Modeling Earth-Scale Human-Like Societies with One Billion Agents
arXiv:2506. 12078v2 Announce Type: replace-cross Abstract: Understanding the dynamic evolution of complex social phenomena requires both high-fidelity modeling of human behavior and large-scale simulations.
arXiv AI
Oct 7
Disentangling Models from Personas in Heterogeneous LLM Simulations
arXiv:2610.07535v1 Announce Type: cross Abstract: Multi-agent simulations with large language models (LLMs) often operate networks of agents with a single base model. This overlooks the inter-model e...
arXiv AI
Jul 22
Learning to Make Friends: Coaching LLM Agents toward Emergent Social Ties
arXiv:2510. 19299v2 Announce Type: replace Abstract: Can large language model (LLM) agents reproduce the complex social dynamics that characterize human online behavior -- shaped by homophily, reciprocity, and social validation -- and what memory and learning mechanisms enable such dynamics to emerge?
arXiv AI
Jul 16
Social Simulations: from Agent-Based Modeling to Digital Twins
arXiv:2607. 13693v1 Announce Type: cross Abstract: This book chapter covers the evolution of social simulation from classical agent-based models, in which agents interact according to explicitly defined behavioral rules, to AI-enhanced simulations based on Large Language Models and, ultimately, Social Digital Twins: high-fidelity, data-driven representations of real-world socio-technical systems.
arXiv AI
Jun 16
MiroBench: Benchmarking Realism in Agentic Simulation of Real-world Discussions
arXiv:2606. 14715v1 Announce Type: cross Abstract: LLM agents are increasingly used to simulate real world interactions, but it remains unclear whether simulated behaviors preserve the content patterns and interaction dynamics of real human behaviors.