AI & ML
LLM-Augmented Agent-Based Simulation of Cyber Social Agents
arXiv cs.MA0 views
arXiv:2610.32988v1 Announce Type: new Abstract: Social media bots are often portrayed as malicious automations to be detected and removed, but automation on social media platforms encompasses a wide spectrum of roles, behaviors, and rhetorical strategies that can shape online discourse in both constructive and destructive ways. This work conceptualizes these automated actors as \textbf{Cyber Social Agents} through a taxonomy of archetypes characterized by their operational tactics and rhetorical style. We integrate this taxonomy into an LLM-driven social simulation, where agents communicate and coordinate in a network environment. Using empirically grounded CSA personas, we simulate heterogeneous online societies to study how agent diversity shapes information diffusion and social influence. Our approach bridges the gap between rule-based agent models and LLM-powered simulations with generated agents that are parameterized from empirical data.
Source：https://arxiv.org/abs/2610.32988PreviousCompatibility-based Bayesian inference: asymptotic limits, variational principles, and Wasserstein geometryNextWhen Agents Collude: Weak-to-Strong On-Policy Distillation for Mitigating Strategic Deception in Multi-Agent Systems
Related posts
10 Open-Source Robotics Repositories for 3D Perception, VLA Policies, and Sensor Calibration
0dev.to
My self-modifying system tried to wire a gate-passing module into its own protection enforcer. It was refused three times.
0dev.to
Last night an AI agent performed brain surgery on a mouse
0Hacker News
The Card-Update Page Gets One Visit. Design for That Visit.
0dev.to UX
SaaS Partner Scout: A Script for Identifying GitHub SaaS Project Contributors
0dev.to GitHub
WARN Act and Retaliation — Can Your Employer Punish You for Asking About a Layoff Notice?
0dev.to Data