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Meituan deploys Generative Bid Shading to optimize ad spending

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Generative Bid Shading (GBS), a new approach for optimizing ad bidding in real-time advertising. GBS utilizes an autoregressive generative model to create shading ratios and a reward preference alignment system with a hierarchical dynamic network to extract features. This method aims to improve both short-term and long-term surplus by overcoming limitations of existing two-stage bid shading techniques. GBS has been successfully deployed on the Meituan DSP platform, handling billions of daily bid requests. AI

IMPACT Introduces a novel generative approach for ad bidding that has been deployed at scale, potentially influencing industry practices.

RANK_REASON This is a research paper detailing a new method for ad bidding optimization.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Meituan deploys Generative Bid Shading to optimize ad spending

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This is a research paper detailing a new method for ad bidding optimization.
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Yinqiu Huang, Hao Ma, Wenshuai Chen, Zongwei Wang, Shuli Wang, Yongqiang Zhang, Xue Wei, Yinhua Zhu, Haitao Wang, Xingxing Wang ·

    Generative Bid Shading in Real-Time Bidding Advertising

    arXiv:2508.06550v3 Announce Type: replace-cross Abstract: Bid shading plays a crucial role in Real-Time Bidding (RTB) by adaptively adjusting the bid to avoid advertisers overspending. Existing mainstream two-stage methods, which first model bid landscapes and then optimize surpl…

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