2 papers
cs.LG2026
Let Training Guide Selection: Online Synthetic Data Filtering via Real-Anchored Utility
Yanran Wu, Sana Lakdawala, Renzo Tassara Miller +6
Synthetic data can scale training supervision when real-world data are limited, but noise and distribution mismatch can reduce its value. Existing synthetic data selection methods…
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…