Zhi-Guang Yang

Progressive Learning from Content to Relevance to Personalization for CTR Prediction

FineSID is proposed, a progressive learning framework that unifies content tokenization, query--item semantic pretraining, and personalized post-training via a shared fine-grained discrete representation that improves within-product creative discrimination and improves within-product creative discrimination.