8 papers
UniRec: Cross-stage Multi-Task Fusion with Preference Optimization for Cascaded Recommender Systems
Lingyuan Kong, Jiaqi Cui, Fanjiao Zeng +6
Industrial recommender systems use cascaded stages with different candidate spaces, data distributions, and latency constraints. Each stage include multi-objective prediction and m…
Once Generated, Ranked: End-to-End Generative Slate Recommendation with Unified Semantic-Collaborative IDs
Yang Hu, Jiayi Guo, Jingui Ma +6
Slate recommendation treats a slate rather than an individual item as the recommendation unit, requiring joint optimization of item interactions and slate utility. Existing approac…
xMTF: A Formula-Free Model for Reinforcement-Learning-Based Multi-Task Fusion in Recommender Systems
Yang Cao, Changhao Zhang, Xiaoshuang Chen +2
Recommender systems need to optimize various types of user feedback, e.g., clicks, likes, and shares. A typical recommender system handling multiple types of feedback has two compo…
Creator-Side Recommender System: Challenges, Designs, and Applications
Xiaoshuang Chen, Yibo Wang, Yao Wang +4
Users and creators are two crucial components of recommender systems. Typical recommender systems focus on the user side, providing the most suitable items based on each user's req…
RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems
Shuo Su, Xiaoshuang Chen, Yao Wang +5
Modern recommender systems are built upon computation-intensive infrastructure, and it is challenging to perform real-time computation for each request, especially in peak periods,…
Cache-Aware Reinforcement Learning in Large-Scale Recommender Systems
Xiaoshuang Chen, Gengrui Zhang, Yao Wang +4
Modern large-scale recommender systems are built upon computation-intensive infrastructure and usually suffer from a huge difference in traffic between peak and off-peak periods. I…
CREAD: A Classification-Restoration Framework with Error Adaptive Discretization for Watch Time Prediction in Video Recommender Systems
Jie Sun, Zhaoying Ding, Xiaoshuang Chen +4
The watch time is a significant indicator of user satisfaction in video recommender systems. However, the prediction of watch time as a target variable is often hindered by its hig…
UNEX-RL: Reinforcing Long-Term Rewards in Multi-Stage Recommender Systems with UNidirectional EXecution
Gengrui Zhang, Yao Wang, Xiaoshuang Chen +3
In recent years, there has been a growing interest in utilizing reinforcement learning (RL) to optimize long-term rewards in recommender systems. Since industrial recommender syste…