State space models offer an efficient solution for sequential recommendation, addressing the effectiveness-efficiency dilemma.
The author introduces Mamba4Rec, leveraging selective state space models to address the effectiveness-efficiency dilemma in sequential recommendation. By incorporating a series of techniques, Mamba4Rec outperforms RNN- and attention-based baselines in both effectiveness and efficiency.