AI RESEARCH
Synthetic Data from Cross-Domain Events for Large-Scale Recommendation Systems
arXiv CS.AI
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ArXi:2606.00282v1 Announce Type: cross Large-scale recommendation systems operate across diverse domains, yet they face the challenges of data sparsity and noisy implicit feedback. Traditional approaches mitigate this via model-specific knowledge distillation from source domains to a target domain. Inspired by the transformative success of synthetic data generation in large language models (LLMs), we