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arXiv AI By Haoran Bu, Zejian Chen, Litian Zhang, Xi Zhang

GraphWake: Group Polarization via Memory-Mediated Polarization Cascade in LLM-Agent Communities

Read the original on arXiv AI →

GraphWake demonstrates a new threat called Memory‑Mediated Polarization Cascade, where LLM‑driven agents use their memory to persistently store and later reproduce arguments that reinforce their stances. The attack unfolds in three stages: exposure and memory retention, retrieval and reproduction during neutral discussion, and iterative propagation to untreated agents. Experiments show that GraphWake significantly increases group polarization across various discussions and memory systems.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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