BWhat changed
Scaled and quantized time-series values into a fixed token vocabulary, pretrained language-model architectures with cross-entropy and sampled future trajectories for probabilistic forecasts; supplemented public data with Gaussian-process synthetic series.
Scientific scope
Scaled and quantized time-series values into a fixed token vocabulary, pretrained language-model architectures with cross-entropy and sampled future trajectories for probabilistic forecasts; supplemented public data with Gaussian-process synthetic series. T5 and probabilistic forecasting are inherited. Zero-shot findings concern held-out datasets, not universal calibration or guaranteed domain transfer. Later Chronos-Bolt direct quantile prediction and Chronos2 covariate/multivariate changes are not part of this original record.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. T5 and probabilistic forecasting are inherited. Zero-shot findings concern held-out datasets, not universal calibration or guaranteed domain transfer. Later Chronos-Bolt direct quantile prediction and Chronos2 covariate/multivariate changes are not part of this original record.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
- Chronos: Learning the Language of Time Series
- Ansari et al.: Chronos quantized-token probabilistic forecasting — author/institution implementation
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
Full scientific record · Browse contribution grades · Request a correction