14 papers
Generative Optimization for Incentivized Advertising with Global Level Constraints
Gege Chen, Ning Luo, Hao Jiang +7
Incentivized advertising allocates monetary or virtual rewards to drive user engagement, where a key challenge is optimizing continuous incentive magnitudes under strict global con…
UniGD: A Unified Generative-Discriminative Framework for Industrial Retrieval
Shujie Ji, Yawei Kong, Yilin Zhao +3
Generative retrieval (GR) is a promising paradigm for industrial search advertising, yet its deployment is constrained by strict relevance and latency requirements. Existing system…
TWICE: Two-Clock, Two-Window Learning for Long-Horizon Conversion Prediction in Online Advertising
Kaiyuan Li, Kun Wang, Zhongbo Wang +4
Long-horizon conversion prediction under delayed feedback creates a two-clock, two-window learning problem in online advertising. A short base observation window releases recent cl…
HOBA: Hierarchical On-Policy Bidding Agents for Adaptive Online Advertising
Ji Wu, Yunshan Peng, Wentao Bai +5
Online advertising bidding systems typically deploy multiple offline-trained expert models (e.g., PID controllers, model predictive control, offline RL policies) but face two criti…
R&F-Inventory: A Large-Scale Dataset for Monotonic Inventory Estimation in Reach and Frequency Advertising
Yunshan Peng, Ji Wu, Wentao Bai +6
Reach and Frequency (R&F) contract advertising is an important form of widely used brand advertising. Unlike performance advertising, R&F contracts emphasize controllable delivery…
Aggregate and Broadcast: Scalable and Efficient Feature Interaction for Recommender Systems
Kaiyuan Li, Yongxiang Tang, Wenzheng Shu +5
Feature interaction is a core ingredient in ranking models for large-scale recommender systems, yet making it both expressive and efficiently scalable remains challenging. Exhausti…