Search papers, labs, and topics across Lattice.
3
0
4
0
UniMixer achieves state-of-the-art scaling in recommendation systems by unifying disparate architectures into a single framework that learns optimal token mixing patterns.
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.
