7 papers
DRIVE: Distributional and Retrieval-Augmented Bidding with Value Evaluation
Miduo Cui, Haochen Wang, Shangqin Mao +6
Auto-bidding is a core component of real-time advertising systems, where decisions must optimize long-term performance under budget and cost constraints, while online exploration i…
HMAF: A Hierarchical Multi-Slot GD-RTB Allocation Framework
Tianxing Bu, Zhaoqi Zhang, Linyou Cai +7
In modern online advertising platforms, Guaranteed Delivery (GD) contracts coexist and bid with Real-Time Bidding (RTB) auctions. Recent approaches either decouple GD and RTB optim…
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…