5 citations · 8 across the 4 of their papers we have counts for
4 papers
HeterRec: Heterogeneous Information Transformer for Scalable Sequential Recommendation
Hao Deng, Haibo Xing, Kanefumi Matsuyama +8
Transformer-based sequential recommendation (TSR) models have shown superior performance in recommendation systems, where the quality of item representations plays a crucial role.…
CSMF: Cascaded Selective Mask Fine-Tuning for Multi-Objective Embedding-Based Retrieval
Hao Deng, Haibo Xing, Kanefumi Matsuyama +6
Multi-objective embedding-based retrieval (EBR) has become increasingly critical due to the growing complexity of user behaviors and commercial objectives. While traditional approa…
Addressing Information Loss and Interaction Collapse: A Dual Enhanced Attention Framework for Feature Interaction
Yi Xu, Zhiyuan Lu, Xiaochen Li +5
The Transformer has proven to be a significant approach in feature interaction for CTR prediction, achieving considerable success in previous works. However, it also presents poten…
LREA: Low-Rank Efficient Attention on Modeling Long-Term User Behaviors for CTR Prediction
Xin Song, Xiaochen Li, Jinxin Hu +5
With the rapid growth of user historical behavior data, user interest modeling has become a prominent aspect in Click-Through Rate (CTR) prediction, focusing on learning user inten…