7 papers
Action-Aware Generative Sequence Modeling for Short Video Recommendation
Wenhao Li, Zihan Lin, Zhengxiao Guo +7
With the rapid development of the Internet, users have increasingly higher expectations for the recommendation accuracy of online content consumption platforms. However, short vide…
KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation
Changle Qu, Sunhao Dai, Ke Guo +7
Live streaming platforms have become a dominant form of online content consumption, offering dynamically evolving content, real-time interactions, and highly engaging user experien…
Comment Staytime Prediction with LLM-enhanced Comment Understanding
Changshuo Zhang, Zihan Lin, Shukai Liu +2
In modern online streaming platforms, the comments section plays a critical role in enhancing the overall user experience. Understanding user behavior within the comments section i…
Stratified Expert Cloning for Retention-Aware Recommendation at Scale
Chengzhi Lin, Annan Xie, Shuchang Liu +3
User retention is critical in large-scale recommender systems, significantly influencing online platforms' long-term success. Existing methods typically focus on short-term engagem…
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…
Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction
Zhongxiang Fan, Zhaocheng Liu, Jian Liang +5
This paper investigates the one-epoch overfitting phenomenon in Click-Through Rate (CTR) models, where performance notably declines at the start of the second epoch. Despite extens…
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…