1 citations · 3 across the 12 of their papers we have counts for
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cs.IR2024★ 1 cited
InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction
Zhichen Zeng, Xiaolong Liu, Mengyue Hang +25
Click-through rate (CTR) prediction, which predicts the probability of a user clicking an ad, is a fundamental task in recommender systems. The emergence of heterogeneous informati…
cs.LG2024★ 1 cited
Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation
Liang Luo, Buyun Zhang, Michael Tsang +11
We study a mismatch between the deep learning recommendation models' flat architecture, common distributed training paradigm and hierarchical data center topology. To address the a…
cs.LG2024★ 1 cited
Wukong: Towards a Scaling Law for Large-Scale Recommendation
Buyun Zhang, Liang Luo, Yuxin Chen +12
Scaling laws play an instrumental role in the sustainable improvement in model quality. Unfortunately, recommendation models to date do not exhibit such laws similar to those obser…