41 citations · 122 across the 27 of their papers we have counts for
8 papers · 1 filter
KuaiSim: A Comprehensive Simulator for Recommender Systems
Kesen Zhao, Shuchang Liu, Qingpeng Cai +5
Reinforcement Learning (RL)-based recommender systems (RSs) have garnered considerable attention due to their ability to learn optimal recommendation policies and maximize long-ter…
AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems
Zhenghai Xue, Qingpeng Cai, Bin Yang +4
The field of Reinforcement Learning (RL) has garnered increasing attention for its ability of optimizing user retention in recommender systems. A primary obstacle in this optimizat…
A Large Language Model Enhanced Conversational Recommender System
Yue Feng, Shuchang Liu, Zhenghai Xue +5
Conversational recommender systems (CRSs) aim to recommend high-quality items to users through a dialogue interface. It usually contains multiple sub-tasks, such as user preference…
Generative Flow Network for Listwise Recommendation
Shuchang Liu, Qingpeng Cai, Zhankui He +5
Personalized recommender systems fulfill the daily demands of customers and boost online businesses. The goal is to learn a policy that can generate a list of items that matches th…
State Regularized Policy Optimization on Data with Dynamics Shift
Zhenghai Xue, Qingpeng Cai, Shuchang Liu +4
In many real-world scenarios, Reinforcement Learning (RL) algorithms are trained on data with dynamics shift, i.e., with different underlying environment dynamics. A majority of cu…
Exploration and Regularization of the Latent Action Space in Recommendation
Shuchang Liu, Qingpeng Cai, Bowen Sun +7
In recommender systems, reinforcement learning solutions have effectively boosted recommendation performance because of their ability to capture long-term user-system interaction.…
Divide and Conquer: Towards Better Embedding-based Retrieval for Recommender Systems From a Multi-task Perspective
Yuan Zhang, Xue Dong, Weijie Ding +3
Embedding-based retrieval (EBR) methods are widely used in modern recommender systems thanks to its simplicity and effectiveness. However, along the journey of deploying and iterat…
Two-Stage Constrained Actor-Critic for Short Video Recommendation
Qingpeng Cai, Zhenghai Xue, Chi Zhang +9
The wide popularity of short videos on social media poses new opportunities and challenges to optimize recommender systems on the video-sharing platforms. Users sequentially intera…