2 papers
cs.IR2026
An Event is Worth One Token: Event Tokenization for Industrial-scale LLM Recommendation
Fan Xia, Zhaoheng Zheng, Iman Setayesh +12
LLM-based recommendation has scaled along model capacity and sequence length, yet each position encodes only text, semantic IDs, or a few categorical features, discarding rich user…
cs.IR2026
GR2 Technical Report
Yufei Li, Zaiwei Zhang, Mingfu Liang +67
Industrial recommendation systems serve billions of users through a multi-stage funnel -- retrieval, early-stage ranking, and re-ranking -- where the final re-ranking step dispropo…