GBS replaces two-stage bid landscape modeling with an autoregressive generative model plus reward-aligned policy optimization to improve short- and long-term advertiser surplus in real-time bidding.
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PEARL approximates unbiased percentile-based preference signals via nonparametric contrastive pairwise comparisons and bootstrapping, yielding gains in watch duration, consumption, and interaction rate on a large livestream platform.
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Generative Bid Shading in Real-Time Bidding Advertising
GBS replaces two-stage bid landscape modeling with an autoregressive generative model plus reward-aligned policy optimization to improve short- and long-term advertiser surplus in real-time bidding.
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PEARL: Unbiased Percentile Estimation via Contrastive Learning for Industrial-Scale Livestream Recommendation
PEARL approximates unbiased percentile-based preference signals via nonparametric contrastive pairwise comparisons and bootstrapping, yielding gains in watch duration, consumption, and interaction rate on a large livestream platform.