LoopMemGR: From Behavior Logs to Evolving Memory for Generative Recommendation
Generative recommendation formulates next-item prediction as conditional autoregressive generation over discrete Semantic IDs, enabling end-to-end recommendation over large-scale item spaces. However, most existing methods follow a history-as-context paradigm that repeatedly reconstructs user preference from behavior h...