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cs.IR2026
Synthetic Data from Cross-Domain Events for Large-Scale Recommendation Systems
Xiangyu Wang, Yawen He, Shivendra Pratap Singh +12
Large-scale recommendation systems operate across diverse domains, yet they face the challenges of data sparsity and noisy implicit feedback. Traditional approaches mitigate this v…
cs.IR2024
Async Learned User Embeddings for Ads Delivery Optimization
Mingwei Tang, Meng Liu, Hong Li +16
In recommendation systems, high-quality user embeddings can capture subtle preferences, enable precise similarity calculations, and adapt to changing preferences over time to maint…