collaborators

9 papers

cs.LG2026

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…

cs.AI2026

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…

cs.LG2026

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…

cs.IR2026

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…

cs.LG2025

Expert-Guided Diffusion Planner for Auto-Bidding

Yunshan Peng, Wenzheng Shu, Jiahao Sun +6

Auto-bidding is widely used in advertising systems, serving a diverse range of advertisers. Generative bidding is increasingly gaining traction due to its strong planning capabilit…

cs.IR2025

VQL: An End-to-End Context-Aware Vector Quantization Attention for Ultra-Long User Behavior Modeling

Kaiyuan Li, Yongxiang Tang, Yanhua Cheng +5

In large-scale recommender systems, ultra-long user behavior sequences encode rich signals of evolving interests. Extending sequence length generally improves accuracy, but directl…