6 citations · 10 across the 5 of their papers we have counts for
5 papers
TBIN: Modeling Long Textual Behavior Data for CTR Prediction
Shuwei Chen, Xiang Li, Jian Dong +3
Click-through rate (CTR) prediction plays a pivotal role in the success of recommendations. Inspired by the recent thriving of language models (LMs), a surge of works improve predi…
A Deep Behavior Path Matching Network for Click-Through Rate Prediction
Jian Dong, Yisong Yu, Yapeng Zhang +6
User behaviors on an e-commerce app not only contain different kinds of feedback on items but also sometimes imply the cognitive clue of the user's decision-making. For understandi…
Decision-Making Context Interaction Network for Click-Through Rate Prediction
Xiang Li, Shuwei Chen, Jian Dong +4
Click-through rate (CTR) prediction is crucial in recommendation and online advertising systems. Existing methods usually model user behaviors, while ignoring the informative conte…
Video Scene Parsing with Predictive Feature Learning
Xiaojie Jin, Xin Li, Huaxin Xiao +9
In this work, we address the challenging video scene parsing problem by developing effective representation learning methods given limited parsing annotations. In particular, we co…
Collaborative Layer-wise Discriminative Learning in Deep Neural Networks
Xiaojie Jin, Yunpeng Chen, Jian Dong +2
Intermediate features at different layers of a deep neural network are known to be discriminative for visual patterns of different complexities. However, most existing works ignore…