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English(EN) SMART: LLM-Augmented Hybrid Retrieval for Dynamic Product Ads

SMART系统使用LLM增强检索将广告转化率提升27.6%

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了SMART，一种新颖的检索系统，旨在通过智能地结合基于关键字和基于LLM的搜索方法来优化动态产品广告（DPAs）。这种方法解决了使用LLM进行大规模产品目录检索所带来的高成本和词汇不匹配问题。SMART在初始关键字搜索显示出不足时，会自适应地将用户引导至LLM驱动的语义探索，从而显著降低LLM推理成本，同时保持再营销性能。在Snap的现场A/B测试中，SMART在广告转化率方面取得了显著的改进。 AI

影响 这种混合检索系统可以显著降低为大规模推荐和广告系统部署LLM的成本。

排序理由 发布了一篇详细介绍新系统及其性能指标的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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

SMART系统使用LLM增强检索将广告转化率提升27.6%

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发布了一篇详细介绍新系统及其性能指标的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Congfei Zhang, Jingxiao Ma, Xiaodong Liu, Hsiang-wei Chao, Siman Wang, Ge Liu, Shantanu Aggarwal, Vincent Zhang, Meghana Missula, Rachel Liao, Zichu Li, Xiao Bai, Yunzhi Zhou, Yajun Wang, Zhe Liu, Jinchao Li, Yu Zhang ·

    SMART：LLM增强型混合检索用于动态产品广告

    arXiv:2607.23121v1 Announce Type: cross Abstract: Dynamic Product Ads (DPA) require retrieving relevant items from multi-million product catalogs, balancing two competing objectives: retargeting (re-surfacing known interests) and prospecting (discovering new categories). While La…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Yu Zhang ·

    SMART：LLM增强型混合检索用于动态产品广告

    Dynamic Product Ads (DPA) require retrieving relevant items from multi-million product catalogs, balancing two competing objectives: retargeting (re-surfacing known interests) and prospecting (discovering new categories). While Large Language Models (LLMs) capture semantic intent…

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