5 papers
HoMer: Addressing Heterogeneities by Modeling Sequential and Set-wise Contexts for CTR Prediction
Shuwei Chen, Jiajun Cui, Zhengqi Xu +4
Click-through rate (CTR) prediction, which models behavior sequence and non-sequential features (e.g., user/item profiles or cross features) to infer user interest, underpins indus…
NGA: Non-autoregressive Generative Auction with Global Externalities for Advertising Systems
Zuowu Zheng, Ze Wang, Fan Yang +5
Online advertising auctions are fundamental to internet commerce, demanding solutions that not only maximize revenue but also ensure incentive compatibility, high-quality user expe…
EGA-V1: Unifying Online Advertising with End-to-End Learning
Junyan Qiu, Ze Wang, Fan Zhang +7
Modern industrial advertising systems commonly employ Multi-stage Cascading Architectures (MCA) to balance computational efficiency with ranking accuracy. However, this approach pr…
EGA-V2: An End-to-end Generative Framework for Industrial Advertising
Zuowu Zheng, Ze Wang, Fan Yang +4
Traditional online industrial advertising systems suffer from the limitations of multi-stage cascaded architectures, which often discard high-potential candidates prematurely and d…
Vertical Semi-Federated Learning for Efficient Online Advertising
Wenjie Li, Shu-Tao Xia, Jiangke Fan +2
Traditional vertical federated learning schema suffers from two main issues: 1) restricted applicable scope to overlapped samples and 2) high system challenge of real-time federate…