Zhiyu Mou — accepted AI-conference papers

2026

Enhancing Generative Auto-bidding with Offline Reward Evaluation and Policy Search

Zhiyu Mou, Yiqin Lv, Miao Xu, Cheems Wang, Yixiu Mao, Jinghao Chen +6

ICLR 2026oral

Auto-bidding serves as a critical tool for advertisers to improve their advertising performance. Recent progress has demonstrated that AI-Generated Bidding (AIGB), which learns a conditional generative planner from offline data, achieves superior performance compared to typical offline reinforcement…

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2022

Sustainable Online Reinforcement Learning for Auto-bidding

Zhiyu Mou, Yusen Huo, Rongquan Bai, Mingzhou Xie, Chuan Yu, Jian Xu +1

NeurIPS 2022accept

Recently, auto-bidding technique has become an essential tool to increase the revenue of advertisers. Facing the complex and ever-changing bidding environments in the real-world advertising system (RAS), state-of-the-art auto-bidding policies usually leverage reinforcement learning (RL) algorithms t…

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