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Modeling U.S. Attitudes Toward China via an Event-Steered Multi-Agent Simulator
arXiv:2606.06971v1 Announce Type: new Abstract: Understanding the dynamic evolution of opinions, such as U.S. public attitudes toward China, is essential for assessing geopolitical risks. However, existing LLM-based multiagent simulators predominantly rely on static rules and fixed datasets, limiting their ability to capture the dynamic, event-driven nature of macro-level opinion shifts in real-world settings.