Contamination Map Methodology

Time series / Model

Moirai-1.0-R

Organisation
Salesforce AI Research
Family
Moirai · version 1.0-R
Released
2024-02-04 (arXiv v1 submission date (https://arxiv.org/abs/2402.02592v1); HF repos Salesforce/moirai-1.0-R-* created 2024-02-11 (HF API); uni2ts README lists the model release under 'Mar 2024')
Checkpoints
Salesforce/moirai-1.0-R-small, Salesforce/moirai-1.0-R-base, Salesforce/moirai-1.0-R-large
Weights
Open · cc-by-nc-4.0 (weights, per HF model card); uni2ts code is Apache-2.0
Links
PaperModel cardCode

Training data disclosure: Full list

Level determined for 100% of benchmark cells.

“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Training corpora

Declared exclusions

Benchmark cells

GIFT-Eval

Not seen Jena Weather (GIFT-Eval) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen BizITObs - Application · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen BizITObs - Service · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen BizITObs - L2C · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen Bitbrains - Fast Storage · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen Bitbrains - rnd · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Seen, split unclear Restaurant (Recruit Restaurant Visitor Forecasting) · the dataset was used; the source does not say which part (via LOTSA (Large-scale Open Time Series Archive))

Evidence (4)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“Restaurant”
arxiv.org · paper · Appendix A, Table 17 (Others) · retrieved 2026-10-15

Not seen ETT1 (GIFT-Eval) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen ETT2 (GIFT-Eval) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Seen, split unclear Loop Seattle (LibCity) · the dataset was used; the source does not say which part (via LOTSA (Large-scale Open Time Series Archive))

Evidence (4)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“Loop Seattle”
arxiv.org · paper · Appendix A, Table 13 (LibCity) · retrieved 2026-10-15

Seen, split unclear SZ-Taxi (LibCity) · the dataset was used; the source does not say which part (via LOTSA (Large-scale Open Time Series Archive))

Evidence (4)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“SZ-Taxi”
arxiv.org · paper · Appendix A, Table 13 (LibCity) · retrieved 2026-10-15

Seen, split unclear M_DENSE (LibCity) · the dataset was used; the source does not say which part (via LOTSA (Large-scale Open Time Series Archive))

Evidence (4)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“Rotterdam”
arxiv.org · paper · Appendix A, Table 13 (LibCity) · retrieved 2026-10-15

Not seen Solar (LSTNet, 137 Alabama PV plants) · the authors state the dataset was excluded from training

Evidence (1)
“We omit Electricity (Trindade, 2015) and Solar (Lai et al., 2018) datasets for out-of-distribution evaluation.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear Hierarchical Sales (Mancuso et al., 2020) · the dataset was used; the source does not say which part (via LOTSA (Large-scale Open Time Series Archive))

Evidence (4)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“Hierarchical Sales”
arxiv.org · paper · Appendix A, Table 17 (Others) · retrieved 2026-10-15

Test data seen M4 Yearly · the whole dataset was used (via LOTSA (Large-scale Open Time Series Archive))

Evidence (6)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“M4 Yearly”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“For the following datasets, we include their entirety in LOTSA without a held-out test set for the following reasons:”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15
“M1 Yearly, M1 Quarterly, M3 Yearly, M3 Quarterly, M4 Yearly, M4 Quarterly, Tourism Yearly: Some time series in these datasets are too short after train/test splits, thus we do not split them”
arxiv.org · paper · Appendix A, Monash exceptions list · retrieved 2026-10-15

Test data seen M4 Quarterly · the whole dataset was used (via LOTSA (Large-scale Open Time Series Archive))

Evidence (6)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“M4 Quarterly”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“For the following datasets, we include their entirety in LOTSA without a held-out test set for the following reasons:”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15
“M1 Yearly, M1 Quarterly, M3 Yearly, M3 Quarterly, M4 Yearly, M4 Quarterly, Tourism Yearly: Some time series in these datasets are too short after train/test splits, thus we do not split them”
arxiv.org · paper · Appendix A, Monash exceptions list · retrieved 2026-10-15

Seen, split unclear M4 Monthly · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“M4 Monthly”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear M4 Weekly · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“M4 Weekly”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear M4 Daily · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“M4 Daily”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear M4 Hourly · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“M4 Hourly”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear Hospital · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“Hospital”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear COVID Deaths · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“COVID Deaths”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear US Births · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“US Births”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear Saugeen River Flow · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“Saugeen”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear Temperature Rain · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“Temperature Rain”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear KDD Cup 2018 · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“KDD Cup 2018”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Seen, split unclear Car Parts · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“Car Parts”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Not seen ElectricityLoadDiagrams20112014 (UCI) · the authors state the dataset was excluded from training

Evidence (2)
“We omit Electricity (Trindade, 2015) and Solar (Lai et al., 2018) datasets for out-of-distribution evaluation.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15
“The Electricity dataset (Trindade, 2015) is also included in BuildingsBench but we omit it from LOTSA and use it for out-of-distribution evaluation instead.”
arxiv.org · paper · Appendix A, BuildingsBench paragraph · retrieved 2026-10-15

Long-horizon forecasting (ETT, Electricity, Traffic, Weather, Exchange, ILI)

Not seen ETTh1 · the authors state the dataset was excluded from training

Evidence (3)
“datasets used in the following have not been included in LOTSA.”
arxiv.org · paper · Section 4.2 · retrieved 2026-10-15
“We evaluate on a subset of the popular long sequence forecasting benchmark (Wu et al., 2021), omitting datasets which have datasets from the same source present in our pre-training data and cannot be considered zero-shot.”
arxiv.org · paper · Section 4.2, Long Sequence Forecasting · retrieved 2026-10-15
“ETTh1”
arxiv.org · paper · Table 6 · retrieved 2026-10-15

Not seen ETTh2 · the authors state the dataset was excluded from training

Evidence (3)
“datasets used in the following have not been included in LOTSA.”
arxiv.org · paper · Section 4.2 · retrieved 2026-10-15
“We evaluate on a subset of the popular long sequence forecasting benchmark (Wu et al., 2021), omitting datasets which have datasets from the same source present in our pre-training data and cannot be considered zero-shot.”
arxiv.org · paper · Section 4.2, Long Sequence Forecasting · retrieved 2026-10-15
“ETTh2”
arxiv.org · paper · Table 6 · retrieved 2026-10-15

Not seen ETTm1 · the authors state the dataset was excluded from training

Evidence (3)
“datasets used in the following have not been included in LOTSA.”
arxiv.org · paper · Section 4.2 · retrieved 2026-10-15
“We evaluate on a subset of the popular long sequence forecasting benchmark (Wu et al., 2021), omitting datasets which have datasets from the same source present in our pre-training data and cannot be considered zero-shot.”
arxiv.org · paper · Section 4.2, Long Sequence Forecasting · retrieved 2026-10-15
“ETTm1”
arxiv.org · paper · Table 6 · retrieved 2026-10-15

Not seen ETTm2 · the authors state the dataset was excluded from training

Evidence (3)
“datasets used in the following have not been included in LOTSA.”
arxiv.org · paper · Section 4.2 · retrieved 2026-10-15
“We evaluate on a subset of the popular long sequence forecasting benchmark (Wu et al., 2021), omitting datasets which have datasets from the same source present in our pre-training data and cannot be considered zero-shot.”
arxiv.org · paper · Section 4.2, Long Sequence Forecasting · retrieved 2026-10-15
“ETTm2”
arxiv.org · paper · Table 6 · retrieved 2026-10-15

Not seen Electricity (ECL, 321 clients) · the authors state the dataset was excluded from training

Evidence (3)
“datasets used in the following have not been included in LOTSA.”
arxiv.org · paper · Section 4.2 · retrieved 2026-10-15
“We evaluate on a subset of the popular long sequence forecasting benchmark (Wu et al., 2021), omitting datasets which have datasets from the same source present in our pre-training data and cannot be considered zero-shot.”
arxiv.org · paper · Section 4.2, Long Sequence Forecasting · retrieved 2026-10-15
“Electricity”
arxiv.org · paper · Table 6 · retrieved 2026-10-15

Seen, split unclear Traffic (PeMS San Francisco Bay, 862 sensors) · a training split was used; its overlap with this benchmark's test data is not established (via LOTSA (Large-scale Open Time Series Archive))

Evidence (5)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“Traffic Hourly”
arxiv.org · paper · Appendix A, Table 14 (Monash) · retrieved 2026-10-15
“apart from the exceptions listed below, we only include the train region in LOTSA, by holding out the final forecast horizon as the test set.”
arxiv.org · paper · Appendix A, Monash paragraph · retrieved 2026-10-15

Not seen Weather (Jena, 2020; Autoformer) · the authors state the dataset was excluded from training

Evidence (5)
“datasets used in the following have not been included in LOTSA.”
arxiv.org · paper · Section 4.2 · retrieved 2026-10-15
“Walmart (Walmart Competition Admin, 2014) Weather”
arxiv.org · paper · Table 18 · retrieved 2026-10-15
“datasets used in the following have not been included in LOTSA.”
arxiv.org · paper · Section 4.2 · retrieved 2026-10-15
“We evaluate on a subset of the popular long sequence forecasting benchmark (Wu et al., 2021), omitting datasets which have datasets from the same source present in our pre-training data and cannot be considered zero-shot.”
arxiv.org · paper · Section 4.2, Long Sequence Forecasting · retrieved 2026-10-15
“Weather”
arxiv.org · paper · Table 6 · retrieved 2026-10-15

Not seen Exchange-Rate · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Related data seen ILI (CDC influenza-like illness, national) · related dataset CDC FluView ILINet (LOTSA) was used (via LOTSA (Large-scale Open Time Series Archive))

Evidence (7)
“Trained on LOTSA, which is a dataset of datasets, we introduce the notion of sub-datasets”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15
“The Moirai-1.0-R series have been trained on the Large-scale Open Time Series Archive (LOTSA)”
raw.githubusercontent.com · readme · LOTSA Data v1 · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15
“CDC Fluview ILINet”
arxiv.org · paper · Appendix A, Table 17 (Others) · retrieved 2026-10-15
“includes the weekly recorded influenza-like illness (ILI) patients data from Centers for Disease Control and Prevention of the United States between 2002 and 2021”
arxiv.org · paper · Section 4 (Datasets) · retrieved 2026-10-15
“https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html”
arxiv.org · paper · Section 4, footnote 4 · retrieved 2026-10-15
“CDC Fluview ILINet CDC Fluview WHO NREVSS”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15

Time-series anomaly detection

Not seen TSB-AD-U (TSB-AD univariate) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen TSB-AD-M (TSB-AD multivariate) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen UCR Time Series Anomaly Archive (Hexagon ML/UCR, KDD Cup 2021) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen Server Machine Dataset (SMD) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen Mars Science Laboratory (MSL) telemetry anomaly dataset · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen Soil Moisture Active Passive (SMAP) telemetry anomaly dataset · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen Pooled Server Metrics (PSM) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen Secure Water Treatment (SWaT) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen Yahoo S5 Labeled Anomaly Detection Dataset (Yahoo Webscope S5) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen Numenta Anomaly Benchmark (NAB) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Time-series classification

Not seen UCR Time Series Classification Archive (2018) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Not seen UEA Multivariate Time Series Classification Archive (2018) · absent from the complete list of training data

Evidence (2)
“LOTSA is a collection of time series datasets curated for pre-training of LTMs. In the following, we describe its constituent datasets and their respective sources, listing any pre-processing and data splitting performed.”
arxiv.org · paper · Appendix A · retrieved 2026-10-15
“Large Time Series Model pre-trained on [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data)”
huggingface.co · model card · retrieved 2026-10-15

Notes

Sizes small/base/large (14m/91m/311m per card). LSF Traffic was omitted from evaluation because LOTSA contains LargeST/PeMS data from the same source. Weights were later patched on HF (uni2ts PR #111) to fix a projection-layer ordering issue; training data unchanged. Other stated exclusions, not tracked here: Walmart (all); Istanbul Traffic (all); Turkey Power (all); Monash Time Series Forecasting Repository (test region) (test); CloudOps TSF (Azure VM Traces 2017, Borg Cluster Data 2011, Alibaba Cluster Trace 2018) test set (test).

Sources