2 papers
cs.IR2026
Compute Only Once: UG-Separation for Efficient Large Recommendation Models
Hui Lu, Zheng Chai, Shipeng Bai +15
Driven by scaling laws, recommender systems increasingly rely on larger-scale models to capture complex feature interactions and user behaviors, but this trend also leads to prohib…
cs.IR2025
LEMUR: Large scale End-to-end MUltimodal Recommendation
Xintian Han, Honggang Chen, Quan Lin +14
Traditional ID-based recommender systems often struggle with cold-start and generalization challenges. Multimodal recommendation systems, which leverage textual and visual data, of…