Meta Lattice: Model Space Redesign for Cost-Effective Industry-Scale Ads Recommendations

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Authors: Liang Luo, Yuxin Chen, Zhengyu Zhang, Mengyue Hang, Andrew Gu, Buyun Zhang, Boyang Liu, Chen Chen, C. Simon Fan, Feifan Gu, Huayu Li, Jade Nie
+29 more Jiayi Xu, Jiyan Yang, Jongsoo Park, Laming Chen, Longhao Jin, Qin Huang, Shali Jiang, Shiwen Shen, Shuaiwen Wang, Siyang Yuan, Tongyi Tang, Weilin Zhang, Xi Liu, Xiaohan Wei, Yuchen Hao, Xiaozhen Xia, Yasmine A. Badr, Z. Chen, Chengze Fan, Dong Liang, Qianru Li, Sihan Zeng, Wenjun Wang, Z. Chen, Yinbin Ma, Maxim Naumov, Yantao Yao, Wenlin Chen, Ellie Wen
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Abstract

The rapidly evolving landscape of products, surfaces, policies, and regulations poses significant challenges for deploying state-of-the-art recommendation models at industry scale, primarily due to data fragmentation across domains and escalating infrastructure costs that hinder sustained quality improvements.

Fields of Study & Subjects

Recommender Systems and Techniques Advanced Graph Neural Networks Explainable Artificial Intelligence (XAI)

Publication details

Pages
2335–2346
Publication date
20 April 2026