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English(EN) Constrained Auto-Bidding via Generative Response Modeling

新的生成式响应模型增强广告自动竞价

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种名为生成式响应模型（GRM）的新方法，用于广告中的自动竞价系统。该模型根据历史数据和竞价乘数预测未来的流量量和成本/价值曲线。与将约束集成到奖励信号中的先前方法不同，GRM直接对响应进行建模，这被证明可以提高约束稳定性和在AuctionNet数据集上的整体性能。 AI

影响 这种新模型可能带来更稳定有效的数字广告自动竞价策略。

排序理由 该集群描述了一篇详细介绍特定AI应用新模型的最新研究论文。

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新的生成式响应模型增强广告自动竞价

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Eunseok Yang, Xingdong Zuo, Kyung-Min Kim ·

    通过生成式响应建模实现约束自动出价

    arXiv:2605.27811v1 Announce Type: new Abstract: Auto-bidding systems aim to maximize advertiser value over long horizons under budget constraints and ratio targets such as cost-per-acquisition, yet future traffic and auction dynamics are non-stationary and uncertain. Existing app…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    通过生成式响应建模实现约束自动出价

    Auto-bidding systems aim to maximize advertiser value over long horizons under budget constraints and ratio targets such as cost-per-acquisition, yet future traffic and auction dynamics are non-stationary and uncertain. Existing approaches face distinct limitations: control-based…

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