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cs.IR2026
Recommendation as Generation: Unifying Personalized Video Generation and Recommendation at Industrial Scale
Yanhua Cheng, Bo Wang, Haotian Zhang +17
Traditional short-video recommendation systems match user interest to a fixed pool of pre-produced videos, which limits their ability to capture fine-grained and dynamic preference…
cs.IR2024
LEARN: Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application
Jian Jia, Yipei Wang, Yan Li +8
Contemporary recommendation systems predominantly rely on ID embedding to capture latent associations among users and items. However, this approach overlooks the wealth of semantic…