ScioMind combines anchoring-based belief updates, hierarchical memory, and dynamic profiles in LLM multi-agent systems to produce more stable, diverse, and psychologically aligned opinion trajectories than prior fixed-rule or unconstrained approaches.
arXiv preprint arXiv:2403.09498 , year=
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ES-MAS combines a new CURE dataset of 258 events and 14,000 news items with dual-stream integration and localized interaction modules to simulate opinion dynamics and claims better reproduction of historical U.S.-China attitude trends than prior simulators.
GraphMind equips LLM agents with graph awareness to construct human-like social networks, producing botnets that substantially degrade performance of both text-based and graph-based detectors.
citing papers explorer
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ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles
ScioMind combines anchoring-based belief updates, hierarchical memory, and dynamic profiles in LLM multi-agent systems to produce more stable, diverse, and psychologically aligned opinion trajectories than prior fixed-rule or unconstrained approaches.
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Modeling U.S. Attitudes Toward China via an Event-Steered Multi-Agent Simulator
ES-MAS combines a new CURE dataset of 258 events and 14,000 news items with dual-stream integration and localized interaction modules to simulate opinion dynamics and claims better reproduction of historical U.S.-China attitude trends than prior simulators.
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Beyond Individual Mimicry: Constructing Human-Like Social network with Graph-Augmented LLM Agents
GraphMind equips LLM agents with graph awareness to construct human-like social networks, producing botnets that substantially degrade performance of both text-based and graph-based detectors.