GraphWake: Group Polarization via Memory-Mediated Polarization Cascade in LLM-Agent Communities
LLM-driven agents can autonomously exchange opinions on online platforms and form communities. Such agent-operated social platforms raise a new security concern: attackers may manipulate agents to induce group polarization. Existing methods manipulate agent prompts or construct echo chambers, both of which are difficult to realize in practice. We therefore formulate a new threat, Memory-Mediated Polarization Cascade, which uses agent memory as a persistence channel and public discussion as a propagation channel. This threat contains three stages. During exposure and memory retention, the attacker exposes a small set of target agents to arguments that reinforce their respective stated stan...
| Authors | Haoran Bu, Zejian Chen, Litian Zhang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 18 August 2026 |
| Last updated at source | 18 August 2026 |
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