Mix, Don't Pick: Why Synthetic Corpus Composition Matters for Time Series Foundation Model Pretraining 事件

Mix, Don't Pick: Why Synthetic Corpus Composition Matters for Time Series Foundation Model Pretraining arXiv:2606.09912v1 Announce Type: cross Abstract: Choosing the wrong synthetic generator for time-series foundation model pretraining is costly: under identical training budgets, the best and worst generators produce up to a $2\times$ gap in forecasting error, yet the field has no principled way to make this choice. The problem is compounded by the fact that generator rankings are not stable a