Minor perturbations in persona format, instruction framing, and network structure shift cooperation by up to 76 percentage points and polarization metrics consistently, showing that LLM social simulations require per-claim robustness audits via the new TRAILS taxonomy.
The wisdom of partisan crowds: Comparing collective intelligence in humans and llm-based agents
3 Pith papers cite this work. Polarity classification is still indexing.
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A Bayesian framework disentangles topic, agreement, and anchoring biases from interaction effects in LLM multi-turn dialogues, revealing convergence to attractors that shift with fine-tuning.
CogEvolution combines ICAP cognitive taxonomy, IRT memory retrieval, and evolutionary algorithms into a generative agent that simulates dynamic student cognitive evolution and outperforms baselines in fidelity and learning curves.
citing papers explorer
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Stop Drawing Scientific Claims from LLM Social Simulations Without Robustness Audits
Minor perturbations in persona format, instruction framing, and network structure shift cooperation by up to 76 percentage points and polarization metrics consistently, showing that LLM social simulations require per-claim robustness audits via the new TRAILS taxonomy.
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Disentangling Interaction and Bias Effects in Opinion Dynamics of Large Language Models
A Bayesian framework disentangles topic, agreement, and anchoring biases from interaction effects in LLM multi-turn dialogues, revealing convergence to attractors that shift with fine-tuning.
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CogEvolution: A Human-like Generative Educational Agent to Simulate Student's Cognitive Evolution
CogEvolution combines ICAP cognitive taxonomy, IRT memory retrieval, and evolutionary algorithms into a generative agent that simulates dynamic student cognitive evolution and outperforms baselines in fidelity and learning curves.