arXiv AI By Xiangyu Wang, Yawen He, Shivendra Pratap Singh, Han Huang, Mengtong Hu, Sharath Ciddu, Yi-Hsuan Hsieh, Erik Groving, Yi Ding, Jieming Di, Tony Wang, Min Yun, Xiaoyu Chen, Ling Leng, Rob Malkin

Synthetic Data from Cross-Domain Events for Large-Scale Recommendation Systems

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arXiv:2606. 00282v1 Announce Type: cross Abstract: Large-scale recommendation systems operate across diverse domains, yet they face the challenges of data sparsity and noisy implicit feedback.

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arXiv AI
Jun 2

Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation

arXiv:2602. 07298v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) represent a promising frontier for recommender systems, yet their development has been impeded by the absence of predictable scaling laws, which are crucial for guiding research and optimizing resource allocation.

By Benyu Zhang, Qiang Zhang, Jianpeng Cheng, Hong-You Chen, Qifei Wang, Wei Sun, Shen Li, Jia Li, Jiahao Wu, Qunshu Zhang, Neeraj Bhatia, Xiangjun Fan, Hong Yan