Contamination Map Methodology

Time series / Model

Timer

Organisation
Tsinghua University (THUML)
Family
Timer · version Timer (ICML 2024; zero-shot variants Timer-1B / Timer-16B / Timer-28B)
Released
2024-02-04 (arXiv v1 submission date, https://arxiv.org/abs/2402.02368)
Checkpoints
Timer-1B, Timer-16B, Timer-28B
Weights
Open · MIT (code repository)
Links
PaperCode

Training data disclosure: Full list

Level determined for 100% of benchmark cells.

“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

Training corpora

Other declared training data

Declared exclusions

Benchmark cells

GIFT-Eval

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (2)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (2)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (2)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (2)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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) · absent from the complete list of training data

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (2)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (4)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (4)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (3)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (3)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (3)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (3)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (3)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (3)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 · the dataset was used; the source does not say which part (via Unified Time Series Dataset (UTSD))

Evidence (2)
“Timer-1B is pre-trained on UTSD”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15
“US Births | 0.00M”
huggingface.co · dataset card · Dataset Description table · retrieved 2026-10-15

Seen, split unclear Saugeen River Flow · the dataset was used; the source does not say which part (via Unified Time Series Dataset (UTSD))

Evidence (2)
“Timer-1B is pre-trained on UTSD”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15
“Saugen River Flow | 0.02M”
huggingface.co · dataset card · Dataset Description table · retrieved 2026-10-15

Seen, split unclear Temperature Rain · the dataset was used; the source does not say which part (via Unified Time Series Dataset (UTSD))

Evidence (2)
“Timer-1B is pre-trained on UTSD”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15
“Temperature Rain | 23.25M”
huggingface.co · dataset card · Dataset Description table · retrieved 2026-10-15

Seen, split unclear KDD Cup 2018 · the dataset was used; the source does not say which part (via Unified Time Series Dataset (UTSD))

Evidence (2)
“Timer-1B is pre-trained on UTSD”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15
“KDD Cup 2018 | 2.94M”
huggingface.co · dataset card · Dataset Description table · 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 (3)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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) · absent from the complete list of training data

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (2)
“All the downstream datasets are not included in the pre-training stage to prevent data leakage.”
arxiv.org · paper · Section 4 (Experiments) · retrieved 2026-10-15
“(1) ETT (Zhou et al., 2021) contains 7 variates of power transformers”
arxiv.org · paper · Appendix B.2, Forecasting · retrieved 2026-10-15

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

Evidence (2)
“All the downstream datasets are not included in the pre-training stage to prevent data leakage.”
arxiv.org · paper · Section 4 (Experiments) · retrieved 2026-10-15
“(1) ETT (Zhou et al., 2021) contains 7 variates of power transformers”
arxiv.org · paper · Appendix B.2, Forecasting · retrieved 2026-10-15

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

Evidence (2)
“All the downstream datasets are not included in the pre-training stage to prevent data leakage.”
arxiv.org · paper · Section 4 (Experiments) · retrieved 2026-10-15
“(1) ETT (Zhou et al., 2021) contains 7 variates of power transformers”
arxiv.org · paper · Appendix B.2, Forecasting · retrieved 2026-10-15

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

Evidence (2)
“All the downstream datasets are not included in the pre-training stage to prevent data leakage.”
arxiv.org · paper · Section 4 (Experiments) · retrieved 2026-10-15
“(1) ETT (Zhou et al., 2021) contains 7 variates of power transformers”
arxiv.org · paper · Appendix B.2, Forecasting · retrieved 2026-10-15

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

Evidence (2)
“All the downstream datasets are not included in the pre-training stage to prevent data leakage.”
arxiv.org · paper · Section 4 (Experiments) · retrieved 2026-10-15
“(2) ECL (Wu et al., 2021) mainly consists of hourly electricity consumption data from 321 customers”
arxiv.org · paper · Appendix B.2, Forecasting · 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)); this contradicts a statement that the data was excluded

Evidence (5)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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
“All the downstream datasets are not included in the pre-training stage to prevent data leakage.”
arxiv.org · paper · Section 4 (Experiments) · retrieved 2026-10-15
“(3) Traffic (Wu et al., 2021) collected hourly road occupancy rates measured by 862 sensors”
arxiv.org · paper · Appendix B.2, Forecasting · retrieved 2026-10-15

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

Evidence (2)
“All the downstream datasets are not included in the pre-training stage to prevent data leakage.”
arxiv.org · paper · Section 4 (Experiments) · retrieved 2026-10-15
“(4) Weather (Wu et al., 2021) consists of 21 meteorological variates collected every 10 minutes”
arxiv.org · paper · Appendix B.2, Forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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 (5)
“Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · 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)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

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

Evidence (2)
“UTSD encompasses 29 individual datasets as listed with the asterisk mark in Table 2, intricately representative of a wide range of domains.”
arxiv.org · paper · Appendix A.1 · retrieved 2026-10-15
“Timer-1B is pre-trained on UTSD; Timer-16B is pre-trained on UTSD and Buildings900K (Emami et al., 2023); and Timer-28B is pre-trained on UTSD and LOTSA.”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15

Time-series classification

Seen, split unclear UCR Time Series Classification Archive (2018) · the dataset was used; the source does not say which part (via Unified Time Series Dataset (UTSD))

Evidence (5)
“Timer-1B is pre-trained on UTSD”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15
“PigArtPressure | 0.62M”
huggingface.co · dataset card · Dataset Description table · retrieved 2026-10-15
“PigArtPressure | 0.62M”
huggingface.co · dataset card · Dataset Description table (source column [3]) · retrieved 2026-10-15
“[3]: [The UCR Time Series Archive](https://arxiv.org/abs/1810.07758)”
huggingface.co · dataset card · Dataset Description references · retrieved 2026-10-15
“Each series representing a variate will be divided into training and validation splits at a ratio of 9:1 for pre-training.”
arxiv.org · paper · Section 3 (pre-training strategy) · retrieved 2026-10-15

Seen, split unclear UEA Multivariate Time Series Classification Archive (2018) · the dataset was used; the source does not say which part (via Unified Time Series Dataset (UTSD))

Evidence (5)
“Timer-1B is pre-trained on UTSD”
arxiv.org · paper · Appendix B.2, Zero-shot forecasting · retrieved 2026-10-15
“MotorImagery | 72.58M”
huggingface.co · dataset card · Dataset Description table · retrieved 2026-10-15
“MotorImagery | 72.58M”
huggingface.co · dataset card · Dataset Description table (source column [3]) · retrieved 2026-10-15
“[3]: [The UCR Time Series Archive](https://arxiv.org/abs/1810.07758)”
huggingface.co · dataset card · Dataset Description references · retrieved 2026-10-15
“Each series representing a variate will be divided into training and validation splits at a ratio of 9:1 for pre-training.”
arxiv.org · paper · Section 3 (pre-training strategy) · retrieved 2026-10-15

Notes

Timer-1B/16B/28B are names for pre-training data scale (time points), not parameter counts. Checkpoints are distributed via Google Drive/Baidu links in scripts/README; which variant(s) they correspond to is not stated. The downstream-exclusion statement covers ETT, ECL, Traffic, Weather and PEMS, yet the zero-shot appendix says 'PEMS datasets are not included, as they have already appeared in the LOSTA dataset for pre-training' -- i.e. PEMS is in Timer-28B's data. The released HF checkpoint thuml/timer-base-84m belongs to the Timer-XL entry. Other stated exclusions, not tracked here: PEMS (all).

Sources