9 citations · 16 across the 7 of their papers we have counts for
7 papers
KuaiLive-M3: A Multi-Modal, Multi-Domain, and Multi-Feedback Dataset for Live Streaming Recommendation
Ke Guo, Changle Qu, Jiayaqi Cheng +7
Existing public live streaming datasets suffer from three major limitations: they provide limited access to temporally evolving multimodal live content, overlook users' cross-domai…
Heterogeneous Multi-treatment Uplift Modeling for Trade-off Optimization in Short-Video Recommendation
Chenhao Zhai, Chang Meng, Xueliang Wang +5
The rapid proliferation of short videos on social media platforms presents unique challenges and opportunities for recommendation systems. Users exhibit diverse preferences, and th…
Coarse-to-fine Dynamic Uplift Modeling for Real-time Video Recommendation
Chang Meng, Chenhao Zhai, Xueliang Wang +6
With the rise of short video platforms, video recommendation technology faces more complex challenges. Currently, there are multiple non-personalized modules in the video recommend…
Future Impact Decomposition in Request-level Recommendations
Xiaobei Wang, Shuchang Liu, Xueliang Wang +6
In recommender systems, reinforcement learning solutions have shown promising results in optimizing the interaction sequence between users and the system over the long-term perform…
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…
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…
Deconfounding Duration Bias in Watch-time Prediction for Video Recommendation
Ruohan Zhan, Changhua Pei, Qiang Su +5
Watch-time prediction remains to be a key factor in reinforcing user engagement via video recommendations. It has become increasingly important given the ever-growing popularity of…