3 papers
cs.IR2025
DUET: Dual Model Co-Training for Entire Space CTR Prediction
Yutian Xiao, Meng Yuan, Fuzhen Zhuang +9
The pre-ranking stage plays a pivotal role in large-scale recommender systems but faces an intrinsic trade-off between model expressiveness and computational efficiency. Owing to t…
cs.IR2025
MARS: Modality-Aligned Retrieval for Sequence Augmented CTR Prediction
Yutian Xiao, Shukuan Wang, Binhao Wang +6
Click-through rate (CTR) prediction serves as a cornerstone of recommender systems. Despite the strong performance of current CTR models based on user behavior modeling, they are s…
cs.IR2025
Generate the browsing process for short-video recommendation
Chao Feng, Yanze Zhang, Chenghao Zhang
This paper proposes a generative method to dynamically simulate users' short video watching journey for watch time prediction in short video recommendation. Unlike existing methods…