most citedHIEN: Hierarchical Intention Embedding Network for Click-Through Rate Prediction

16 citations · 16 across the 5 of their papers we have counts for

collaborators
Showing cs.IRShow all

5 papers · 1 filter

cs.IR2025

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…

cs.IR2025

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…

cs.IR2025

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…

cs.IR2022

AutoAttention: Automatic Field Pair Selection for Attention in User Behavior Modeling

Zuowu Zheng, Xiaofeng Gao, Junwei Pan +4

In Click-through rate (CTR) prediction models, a user's interest is usually represented as a fixed-length vector based on her history behaviors. Recently, several methods are propo…

cs.IR2022★ 16 cited

HIEN: Hierarchical Intention Embedding Network for Click-Through Rate Prediction

Zuowu Zheng, Changwang Zhang, Xiaofeng Gao +1

Click-through rate (CTR) prediction plays an important role in online advertising and recommendation systems, which aims at estimating the probability of a user clicking on a speci…