4 papers · 1 filter
Equip Pre-ranking with Target Attention by Residual Quantization
Yutong Li, Yu Zhu, Yichen Qiao +4
The pre-ranking stage in industrial recommendation systems faces a fundamental conflict between efficiency and effectiveness. While powerful models like Target Attention (TA) excel…
User Long-Term Multi-Interest Retrieval Model for Recommendation
Yue Meng, Cheng Guo, Xiaohui Hu +4
User behavior sequence modeling, which captures user interest from rich historical interactions, is pivotal for industrial recommendation systems. Despite breakthroughs in ranking-…
USD: A User-Intent-Driven Sampling and Dual-Debiasing Framework for Large-Scale Homepage Recommendations
Jiaqi Zheng, Cheng Guo, Yi Cao +3
Large-scale homepage recommendations face critical challenges from pseudo-negative samples caused by exposure bias, where non-clicks may indicate inattention rather than disinteres…
A Generative Re-ranking Model for List-level Multi-objective Optimization at Taobao
Yue Meng, Cheng Guo, Yi Cao +2
E-commerce recommendation systems aim to generate ordered lists of items for customers, optimizing multiple business objectives, such as clicks, conversions and Gross Merchandise V…