AI RESEARCH
SODE: Analyzing Social Dynamics in LLM Agents
arXiv CS.AI
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ArXi:2605.23949v1 Announce Type: cross As Large Language Models (LLMs) evolve into interactive agents, understanding their behavioral alignment within human social dynamics becomes essential. While behavioral game theory offers a framework to study these interactions, previous work has predominantly relied on outcome-based metrics such as average scores. This focus overlooks the mechanisms that facilitate sustainable cooperation, as identical scores can be derived from vastly different strategies. To bridge this gap, we.