3 papers
cs.IR2026
From a Static Multi-Level Small Semantic Codebook to a Dynamic Single-Level Large Semantic Codebook for Generative Recommendation
Tianlu Xie, Xin Ku, Mingjie Sun +8
Generative recommendation represents each item with a sequence of discrete Semantic IDs (SIDs) and predicts the sequence to retrieve the next item. Typical systems use multi-level…
cs.IR2026
QARM V2: Quantitative Alignment Multi-Modal Recommendation for Reasoning User Sequence Modeling
Tian Xia, Jiaqi Zhang, Yueyang Liu +25
With the evolution of large language models (LLMs), there is growing interest in leveraging their rich semantic understanding to enhance industrial recommendation systems (RecSys).…
cs.LG2025
Deep Active Learning in the Open World
Tian Xie, Jifan Zhang, Haoyue Bai +1
Machine learning models deployed in open-world scenarios often encounter unfamiliar conditions and perform poorly in unanticipated situations. As AI systems advance and find applic…