Yaqiang Zang

Traditional recommendation systems suffer from multi-stage objective misalignment. Generative recommendation offers end-to-end training, yet existing methods are largely inductive and miss complex intents that require world-knowledge-driven deductive reasoning. LLMs reason well but are impractica...

In industrial commodity recommendation systems, the representation quality of Item-Id vocabularies directly impacts the scalability and generalization ability of recommendation models. A key challenge is that traditional Item-Id vocabularies, when subjected to sparse scaling, suffer from low-freq...