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cs.IR2026
LASER: An Efficient Target-Aware Segmented Attention Framework for End-to-End Long Sequence Modeling
Tianhe Lin, Ziwei Xiong, Baoyuan Ou +8
Modeling ultra-long user behavior sequences is pivotal for capturing evolving and lifelong interests in modern recommendation systems. However, deploying such models in real-time i…
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…
cs.IR2025
NoteLLM-2: Multimodal Large Representation Models for Recommendation
Chao Zhang, Haoxin Zhang, Shiwei Wu +6
Large Language Models (LLMs) have demonstrated exceptional proficiency in text understanding and embedding tasks. However, their potential in multimodal representation, particularl…