Time-Series Foundation Models That Understand Data Revisions
arXiv:2609.28576v1 Announce Type: new Abstract: Historical observations are not always fixed: statistical agencies revise previously published values as new evidence arrives. Forecasting from a contemporary download can therefore expose a model to information unavailable at the date it purportedly…
Read the full story at arXiv cs.LG ↗
Timeline · 2 reports
- 2026-09-26 04:00 · arXiv cs.LG
SGA: Uncertainty Quantification for Multi-Step Forecasting in Time Series Foundation Models - 2026-09-26 04:00 · arXiv cs.LG
Time-Series Foundation Models That Understand Data Revisions