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LEADRE: Multi-Faceted Knowledge Enhanced LLM Empowered Display Advertisement Recommender System

21 November 2024
Fengxin Li
Yi Li
Yue Liu
Chao Zhou
Yuan Wang
Xiaoxiang Deng
Wei Xue
Dapeng Liu
Lei Xiao
Haijie Gu
Jie Jiang
Hongyan Liu
Biao Qin
Jun He
ArXiv (abs)PDFHTML
Main:2 Pages
5 Figures
6 Tables
Appendix:12 Pages
Abstract

Display advertising provides significant value to advertisers, publishers, and users. Traditional display advertising systems utilize a multi-stage architecture consisting of retrieval, coarse ranking, and final ranking. However, conventional retrieval methods rely on ID-based learning to rank mechanisms and fail to adequately utilize the content information of ads, which hampers their ability to provide diverse recommendation lists.

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