7 papers
Bid2X: Revealing Dynamics of Bidding Environment in Online Advertising from A Foundation Model Lens
Jiahao Ji, Tianyu Wang, Yeshu Li +5
Auto-bidding is crucial in facilitating online advertising by automatically providing bids for advertisers. While previous work has made great efforts to model bidding environments…
Breaking the Curse of Repulsion: Remoteness-Aware Control of Negative Off-Policy Updates
Jie Jiang, Yusen Huo, Yangru Huang +3
Off-policy policy optimization reuses historical behavior, including negative-advantage samples that suppress known failures. We show that repeated reuse can turn this useful signa…
DARA: Few-shot Budget Allocation in Online Advertising via In-Context Decision Making with RL-Finetuned LLMs
Mingxuan Song, Yusen Huo, Bohan Zhou +5
Optimizing the advertiser's cumulative value of winning impressions under budget constraints poses a complex challenge in online advertising, under the paradigm of AI-Generated Bid…
DecisionLLM: Large Language Models for Long Sequence Decision Exploration
Xiaowei Lv, Zhilin Zhang, Yijun Li +10
Long-sequence decision-making, which is usually addressed through reinforcement learning (RL), is a critical component for optimizing strategic operations in dynamic environments,…
An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising
Zhijian Duan, Yusen Huo, Tianyu Wang +6
In online advertising, advertisers commonly utilize auto-bidding services to bid for impression opportunities. A typical objective of the auto-bidder is to optimize the advertiser'…
AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games
Kefan Su, Yusen Huo, Zhilin Zhang +5
Decision-making in large-scale games is an essential research area in artificial intelligence (AI) with significant real-world impact. However, the limited access to realistic larg…