MemRec: Collaborative Memory-Augmented Agentic Recommender System

arXiv:2601.08816v3 Announce Type: replace-cross Abstract: The evolution of recommender systems has shifted from traditional collaborative filtering to LLM-based agentic systems, which rely on semantic user and item memories to make predictions. However, existing agents maintain these memories in isolation. This overlooks crucial collaborative signals, such as user-item co-engagements and peer relationships across the community, which significantly limits their ability to uncover hidden preferenc