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Bibliographic Details
Main Authors:	Zhang, Shangyu, Quan, Shijie, Wang, Zhongren, Pan, Junwei, Zhuang, Tianqu, Fu, Bo, Sun, Yilong, Lin, Jieying, Chen, Jushuo, Li, Xiaotian, Feng, Zhixiang, Hu, Xian, Deng, Huiting, Lu, Hua, Wang, Jinpeng, Dai, Boqi, Chen, Xiaoyu, Hu, Bin, Huang, Lili, Wu, Yanwen, Cai, Yeshou, Zhou, Qi, Tang, Huang, Yang, Chunfeng, Yin, Chengguo, Jiang, Tingyu, Wang, Lifeng, Huang, Shudong, Liu, Dapeng, Xiao, Lei, Gu, Haijie, Xia, Shu-Tao, Jiang, Jie
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2508.14948
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Table of Contents:

Online advertising relies on accurate recommendation models, with recent advances using pre-trained large-scale foundation models (LFMs) to capture users' general interests across multiple scenarios and tasks. However, existing methods have critical limitations: they extract and transfer only user representations (URs), ignoring valuable item representations (IRs) and user-item cross representations (CRs); and they simply use a UR as a feature in downstream applications, which fails to bridge upstream-downstream gaps and overlooks more transfer granularities. In this paper, we propose LFM4Ads, an All-Representation Multi-Granularity transfer framework for ads recommendation. It first comprehensively transfers URs, IRs, and CRs, i.e., all available representations in the pre-trained foundation model. To effectively utilize the CRs, it identifies the optimal extraction layer and aggregates them into transferable coarse-grained forms. Furthermore, we enhance the transferability via multi-granularity mechanisms: non-linear adapters for feature-level transfer, an Isomorphic Interaction Module for module-level transfer, and Standalone Retrieval for model-level transfer. LFM4Ads has been successfully deployed in Tencent's industrial-scale advertising platform, processing tens of billions of daily samples while maintaining terabyte-scale model parameters with billions of sparse embedding keys across approximately two thousand features. Since its production deployment in Q4 2024, LFM4Ads has achieved 10+ successful production launches across various advertising scenarios, including primary ones like Weixin Moments and Channels. These launches achieve an overall GMV lift of 2.45% across the entire platform, translating to estimated annual revenue increases in the hundreds of millions of dollars.

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