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cs.IR2025
Pre-train and Fine-tune: Recommenders as Large Models
Zhenhao Jiang, Chenghao Chen, Hao Feng +5
In reality, users have different interests in different periods, regions, scenes, etc. Such changes in interest are so drastic that they are difficult to be captured by recommender…
cs.IR2023
Mobile Supply: The Last Piece of Jigsaw of Recommender System
Zhenhao Jiang, Biao Zeng, Hao Feng +4
Recommendation system is a fundamental functionality of online platforms. With the development of computing power of mobile phones, some researchers have deployed recommendation al…