Multi-LLM agent simulations reproduce stance monoculture and toxicity-delta patterns from real Bluesky hateful cascades, with agent heterogeneity as the main fidelity driver and targeted interventions cutting spread 7.5-12.9% at 5.7% benign cost.
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4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 4representative citing papers
AI alignment must move beyond assuming users have fully formed goals and instead provide active cognitive support to help form and refine intent over time.
AgoraSim is a hybrid agent-based modeling framework that runs LLM, vision-language, and classical agents under a shared action space and compares scenario trajectories against matched classical ABM reference dynamics.
EconAI adds memory weighting and economic sentiment indexing to LLM agents so they adapt short-term actions to long-term goals inside a single macro/micro simulation loop.
citing papers explorer
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Simulating Hate Speech Cascades with Multi-LLM Agents: Empirical Grounding, Modeling Fidelity, and Intervention Strategies
Multi-LLM agent simulations reproduce stance monoculture and toxicity-delta patterns from real Bluesky hateful cascades, with agent heterogeneity as the main fidelity driver and targeted interventions cutting spread 7.5-12.9% at 5.7% benign cost.
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Alignment has a Fantasia Problem
AI alignment must move beyond assuming users have fully formed goals and instead provide active cognitive support to help form and refine intent over time.
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AgoraSim: A Hybrid Agent-Based Modeling Framework
AgoraSim is a hybrid agent-based modeling framework that runs LLM, vision-language, and classical agents under a shared action space and compares scenario trajectories against matched classical ABM reference dynamics.
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EconAI: Dynamic Persona Evolution and Memory-Aware Agents in Evolving Economic Environments
EconAI adds memory weighting and economic sentiment indexing to LLM agents so they adapt short-term actions to long-term goals inside a single macro/micro simulation loop.