OmniBehavior benchmark demonstrates that LLMs simulating real human behavior converge on hyper-active positive average personas, losing long-tail individual differences.
Unveiling the truth and facilitating change: Towards agent-based large-scale social movement simulation
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
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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Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Traces
OmniBehavior benchmark demonstrates that LLMs simulating real human behavior converge on hyper-active positive average personas, losing long-tail individual differences.
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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.