4 papers
A hierarchy tree data structure for behavior-based user segment representation
Yang Liu, Xuejiao Kang, Sathya Iyer +10
User attributes are essential in multiple stages of modern recommendation systems and are particularly important for mitigating the cold-start problem and improving the experience…
Target-Aware Early Stage Ranking
Juhee Hong, Meng Liu, Shengzhi Wang +18
Early Stage Ranking (ESR) in large-scale recommendation systems is dominated by ''user--item decoupling'' Two Tower architectures, which scale efficiently but cannot capture fine-g…
Enhancing Performance and Scalability of Large-Scale Recommendation Systems with Jagged Flash Attention
Rengan Xu, Junjie Yang, Yifan Xu +17
The integration of hardware accelerators has significantly advanced the capabilities of modern recommendation systems, enabling the exploration of complex ranking paradigms previou…
Async Learned User Embeddings for Ads Delivery Optimization
Mingwei Tang, Meng Liu, Hong Li +16
In recommendation systems, high-quality user embeddings can capture subtle preferences, enable precise similarity calculations, and adapt to changing preferences over time to maint…