10 papers
Uncertainty Modeling for Multi-Objective RTA Interception with Distillation Acceleration
Gaoxiang Zhao, Ruinan Qiu, Pengpeng Zhao +4
Real-Time Auction (RTA) interception decides which incoming advertising requests reach downstream systems, and therefore controls the quality of the data those systems learn from.…
JD-BP: A Joint-Decision Generative Framework for Auto-Bidding and Pricing
Linghui Meng, Chun Gan, Shengsheng Niu +8
Auto-bidding services optimize real-time bidding strategies for advertisers under key performance indicator (KPI) constraints such as target return on investment and budget. Howeve…
Auto-bidding under Return-on-Spend Constraints with Uncertainty Quantification
Jiale Han, Chun Gan, Chengcheng Zhang +4
Auto-bidding systems are widely used in advertising to automatically determine bid values under constraints such as total budget and Return-on-Spend (RoS) targets. Existing works o…
ADORE: Autonomous Domain-Oriented Relevance Engine for E-commerce
Zheng Fang, Donghao Xie, Ming Pang +5
Relevance modeling in e-commerce search remains challenged by semantic gaps in term-matching methods (e.g., BM25) and neural models' reliance on the scarcity of domain-specific har…
GCRank: A Generative Contextual Comprehension Paradigm for Takeout Ranking Model
Ziheng Ni, Congcong Liu, Cai Shang +10
The ranking stage serves as the central optimization and allocation hub in advertising systems, governing economic value distribution through eCPM and orchestrating the user-centri…
Generative Modeling with Multi-Instance Reward Learning for E-commerce Creative Optimization
Qiaolei Gu, Yu Li, DingYi Zeng +6
In e-commerce advertising, selecting the most compelling combination of creative elements -- such as titles, images, and highlights -- is critical for capturing user attention and…