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cs.IR2026
CMSL: Constructive Multi-Sequence Learning for Recommendation Systems
Zikun Cui, Renzhi Wu, Junjie Yang +10
Sequence learning has emerged as the promising paradigm in recommendation systems, surpassing traditional Deep Learning Recommendation Models (DLRM) by capturing the temporal nuanc…
cs.IR2026
A General Framework for Multimodal LLM-Based Multimedia Understanding in Large-Scale Recommendation Systems
Yiming Zhu, Xu Liu, Ziyun Xu +9
Conventional recommendation systems frequently fail to fully exploit the high-dimensional semantic signals inherent in multimedia content, thereby limiting the fidelity of user pre…
cs.IR2026
SilverTorch: A Unified Model-based System to Democratize Large-Scale Recommendation on GPUs
Bi Xue, Hong Wu, Lei Chen +29
Serving deep learning based recommendation models (DLRM) at scale is challenging. Existing approaches rely on dedicated ANN indexing and filtering services on CPUs, suffering from…