Visual Inception: Compromising Long-term Planning in Agentic Recommenders via Multimodal Memory Poisoning

arXiv:2604.16966v1 Announce Type: cross Abstract: The evolution from static ranking models to Agentic Recommender Systems (Agentic RecSys) empowers AI agents to maintain long-term user profiles and autonomously plan service tasks. While this paradigm shift enhances personalization, it introduces a vulnerability: reliance on Long-term Memory (LTM). In this paper, we uncover a threat termed "Visual Inception." Unlike traditional adversarial attacks that seek immediate misclassification, Visual Inc