45 citations · 118 across the 22 of their papers we have counts for
7 papers · 1 filter
Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems
Yunli Wang, Zhiqiang Wang, Jian Yang +4
Cascade ranking is widely used for large-scale top-k selection problems in online advertising and recommendation systems, and learning-to-rank is an important way to optimize the m…
Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation
Yunzhu Pan, Chen Gao, Jianxin Chang +5
Sequential recommendation is one of the most important tasks in recommender systems, which aims to recommend the next interacted item with historical behaviors as input. Traditiona…
Multi-Task Recommendations with Reinforcement Learning
Ziru Liu, Jiejie Tian, Qingpeng Cai +8
In recent years, Multi-task Learning (MTL) has yielded immense success in Recommender System (RS) applications. However, current MTL-based recommendation models tend to disregard t…
Reinforcing User Retention in a Billion Scale Short Video Recommender System
Qingpeng Cai, Shuchang Liu, Xueliang Wang +6
Recently, short video platforms have achieved rapid user growth by recommending interesting content to users. The objective of the recommendation is to optimize user retention, the…
Disentangled Causal Embedding With Contrastive Learning For Recommender System
Weiqi Zhao, Dian Tang, Xin Chen +5
Recommender systems usually rely on observed user interaction data to build personalized recommendation models, assuming that the observed data reflect user interest. However, user…
TWIN: TWo-stage Interest Network for Lifelong User Behavior Modeling in CTR Prediction at Kuaishou
Jianxin Chang, Chenbin Zhang, Zhiyi Fu +8
Life-long user behavior modeling, i.e., extracting a user's hidden interests from rich historical behaviors in months or even years, plays a central role in modern CTR prediction s…
PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information
Jianxin Chang, Chenbin Zhang, Yiqun Hui +4
With the increase of content pages and interactive buttons in online services such as online-shopping and video-watching websites, industrial-scale recommender systems face challen…