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cs.IR2023
Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking
Xuewei Wang, Qiang Jin, Shengyu Huang +10
Dividing ads ranking system into retrieval, early, and final stages is a common practice in large scale ads recommendation to balance the efficiency and accuracy. The early stage r…
cs.IR2023★ 1 cited
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations
Danwei Li, Zhengyu Zhang, Siyang Yuan +5
Multi-task learning (MTL) aims to enhance the performance and efficiency of machine learning models by simultaneously training them on multiple tasks. However, MTL research faces t…