Synthetic data can improve generalization when real data is scarce, but excessive reliance may introduce distributional mismatches that degrade performance. In this paper, we
arXiv:2603.22294v1 Announce Type: cross Abstract: Synthetic Data Generation (SDG), leveraging Large Language Models (LLMs), has recently been recognized and broadly adopted as an
arXiv:2608.27996v1 Announce Type: new Abstract: Digital twins (DTs) and learned world models are increasingly used to generate synthetic data that augment the scarce real datasets
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