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cs.IR2026
Effective Knowledge Transfer for Multi-Task Recommendation Models
Guohao Cai, Jun Yuan, Zhenhua Dong
The conversion rate (CVR) is a crucial metric for evaluating the effectiveness of platforms, as it quantifies the alignment of content with audience preferences. However, the limit…
cs.IR2024
RecSys Arena: Pair-wise Recommender System Evaluation with Large Language Models
Zhuo Wu, Qinglin Jia, Chuhan Wu +4
Evaluating the quality of recommender systems is critical for algorithm design and optimization. Most evaluation methods are computed based on offline metrics for quick algorithm e…
cs.IR2024
A Parameter Update Balancing Algorithm for Multi-task Ranking Models in Recommendation Systems
Jun Yuan, Guohao Cai, Zhenhua Dong
Multi-task ranking models have become essential for modern real-world recommendation systems. While most recommendation researches focus on designing sophisticated models for speci…