Alibaba's LazFormer transfers generative pre-training to industrial recommendation ranking
_reachsumit · x · 2026-09-15
Alibaba researchers propose LazFormer, a scalable Transformer recommender that autoregressively pre-generates sequential features and transfers dense parameters into ranking via residual adapters, addressing negative transfer and sparse-parameter overfitting while cutting compute and convergence time versus training a ranking model from scratch.
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