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cs.IR2024★ 1 cited
Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation
Xing Tang, Yang Qiao, Fuyuan Lyu +2
As user behaviors become complicated on business platforms, online recommendations focus more on how to touch the core conversions, which are highly related to the interests of pla…
cs.IR2023
OptMSM: Optimizing Multi-Scenario Modeling for Click-Through Rate Prediction
Xing Tang, Yang Qiao, Yuwen Fu +3
A large-scale industrial recommendation platform typically consists of multiple associated scenarios, requiring a unified click-through rate (CTR) prediction model to serve them si…
cs.IR2023
Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation
Dugang Liu, Yang Qiao, Xing Tang +4
Research on debiased recommendation has shown promising results. However, some issues still need to be handled for its application in industrial recommendation. For example, most o…