Shen Wang

Diffusion models can now generate user preferences for multi-behavior sequential recommendation, outperforming traditional methods by better capturing uncertainty and enabling more diverse recommendations.

Achieve lossless acceleration of ranking models by structurally re-parameterizing feature fusion matrix multiplication, sidestepping the accuracy drop common in lightweighting and distillation.