2 papers
cs.IR2026
MuSeR: Scalable Long-sequence Recommendation with Multi-interest Modeling
Yongkang Fu, Beining Bao, Yu Jiang +10
Ultra-long user behavior sequences carry rich signals of stable and diverse preferences, yet industrial recommender systems typically truncate histories to a few hundred actions un…
cs.IR2026
Rethinking Semantic Collaborative Integration: Why Alignment Is Not Enough
Maolin Wang, Dongze Wu, Jianing Zhou +7
Large language models (LLMs) have become an important semantic infrastructure for modern recommender systems. A prevailing paradigm integrates LLM-derived semantic embeddings with…