TTM-R3

Organisation: IBM Research
Family: Tiny Time Mixers (TTM) · version R3
Released: 2026-02-09 (HF repo creation (createdAt) of ibm-research/ttm-r3 (model branches initialised 2026-03-16), https://huggingface.co/api/models/ibm-research/ttm-r3)
Checkpoints: ibm-research/ttm-r3, ibm-research/ttm-r3@1024-48-dec-512-lite-r3, ibm-research/ttm-r3@1024-48-dec-512-r3, ibm-research/ttm-r3@1024-720-lite-r3, ibm-research/ttm-r3@1024-720-r3, ibm-research/ttm-r3@1024-96-lite-r3, ibm-research/ttm-r3@1024-96-r3, ibm-research/ttm-r3@1536-720-lite-r3, ibm-research/ttm-r3@1536-720-r3, ibm-research/ttm-r3@1536-96-lite-r3, ibm-research/ttm-r3@1536-96-r3, ibm-research/ttm-r3@156-16-dec-52-lite-r3, ibm-research/ttm-r3@156-16-dec-52-r3, ibm-research/ttm-r3@180-60-dec-180-lite-r3, ibm-research/ttm-r3@180-60-dec-180-r3, ibm-research/ttm-r3@2048-720-lite-r3, ibm-research/ttm-r3@2048-720-r3, ibm-research/ttm-r3@2048-96-lite-r3, ibm-research/ttm-r3@2048-96-r3, ibm-research/ttm-r3@2560-720-lite-r3, ibm-research/ttm-r3@2560-720-r3, ibm-research/ttm-r3@2560-96-lite-r3, ibm-research/ttm-r3@2560-96-r3, ibm-research/ttm-r3@3072-720-lite-r3, ibm-research/ttm-r3@3072-720-r3, ibm-research/ttm-r3@3072-96-lite-r3, ibm-research/ttm-r3@3072-96-r3, ibm-research/ttm-r3@360-60-dec-360-lite-r3, ibm-research/ttm-r3@360-60-dec-360-r3, ibm-research/ttm-r3@512-30-dec-90-lite-r3, ibm-research/ttm-r3@512-30-dec-90-r3, ibm-research/ttm-r3@512-336-dec-512-lite-r3, ibm-research/ttm-r3@512-336-dec-512-r3, ibm-research/ttm-r3@512-48-dec-512-lite-r3, ibm-research/ttm-r3@512-48-dec-512-r3, ibm-research/ttm-r3@512-96-dec-512-lite-r3, ibm-research/ttm-r3@512-96-dec-512-r3, ibm-research/ttm-r3@52-16-dec-52-lite-r3, ibm-research/ttm-r3@52-16-dec-52-r3, ibm-research/ttm-r3@768-48-dec-512-lite-r3, ibm-research/ttm-r3@768-48-dec-512-r3, ibm-research/ttm-r3@90-30-dec-90-lite-r3, ibm-research/ttm-r3@90-30-dec-90-r3
Weights: Open · cc-by-nc-sa-4.0
Links: Model card Code

Training data disclosure: Partial list

Level determined for 73% of benchmark cells.

TestTest data seen0
SeenSeen, split unclear1
TrainTraining data seen28
Rel.Related data seen7
NoNot seen0
?Unknown13

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Custom synthesized data: Based on [KernelSynth](https://github.com/amazon-science/chronos-forecasting/blob/main/scripts/kernel-synth.py)”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

Training corpora

GIFT-Eval Pretrain (GiftEvalPretrain) · 86 sources (complete list) · pre-training · homepage
Evidence that TTM-R3 uses it

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Contents of this corpus
- BDG-2 Panther · split: unknown
  HF folder(s): bdg-2_panther.
  
  Evidence
  
  “BDG-2 Panther”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- BDG-2 Fox · split: unknown
  HF folder(s): bdg-2_fox.
  
  Evidence
  
  “BDG-2 Fox BDG-2 Rat”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- BDG-2 Rat · split: unknown
  HF folder(s): bdg-2_rat.
  
  Evidence
  
  “BDG-2 Rat BDG-2 Bear”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- BDG-2 Bear · split: unknown
  HF folder(s): bdg-2_bear.
  
  Evidence
  
  “BDG-2 Bear”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Low Carbon London · split: unknown
  HF folder(s): lcl.
  
  Evidence
  
  “Low Carbon London”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- SMART · split: unknown
  HF folder(s): smart.
  
  Evidence
  
  “SMART IDEAL”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- IDEAL · split: unknown
  HF folder(s): ideal.
  
  Evidence
  
  “IDEAL Sceaux”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Sceaux · split: unknown
  HF folder(s): sceaux.
  
  Evidence
  
  “Sceaux Borealis”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Borealis · split: unknown
  HF folder(s): borealis.
  
  Evidence
  
  “Borealis Buildings900K”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Buildings900K · split: unknown
  HF folder(s): buildings_900k.
  
  Evidence
  
  “Buildings900K”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- CMIP6 · split: unknown
  HF folder(s): cmip6_1850 ... cmip6_2010 (33 folders, every 5 years).
  
  Evidence
  
  “CMIP6 ERA5”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- ERA5 · split: unknown
  HF folder(s): era5_1989 ... era5_2018 (30 yearly folders).
  
  Evidence
  
  “ERA5 Azure VM Traces 2017”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Azure VM Traces 2017 · split: unknown
  HF folder(s): azure_vm_traces_2017.
  
  Evidence
  
  “Azure VM Traces 2017”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Borg Cluster Data 2011 · split: unknown
  HF folder(s): borg_cluster_data_2011.
  
  Evidence
  
  “Borg Cluster Data 2011”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Alibaba Cluster Trace 2018 · split: unknown
  HF folder(s): alibaba_cluster_trace_2018.
  
  Evidence
  
  “Alibaba Cluster Trace 2018”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Taxi · split: unknown
  HF folder(s): taxi_30min.
  
  Evidence
  
  “Taxi Uber TLC Daily”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Uber TLC Daily · split: unknown
  HF folder(s): uber_tlc_daily.
  
  Evidence
  
  “Uber TLC Daily”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Uber TLC Hourly · split: unknown
  HF folder(s): uber_tlc_hourly.
  
  Evidence
  
  “Uber TLC Hourly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Wiki-Rolling · split: unknown
  HF folder(s): wiki-rolling_nips.
  
  Evidence
  
  “Wiki-Rolling”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- M5 · split: unknown
  HF folder(s): m5.
  
  Evidence
  
  “M5 LargeST”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- LargeST (PeMS California) · split: unknown
  HF folder(s): largest_2017 ... largest_2021 (5 yearly folders).
  
  Evidence
  
  “LargeST PEMS03”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- PEMS03 · split: unknown
  HF folder(s): PEMS03.
  
  Evidence
  
  “PEMS03 PEMS04”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- PEMS04 · split: unknown
  HF folder(s): PEMS04.
  
  Evidence
  
  “PEMS04 PEMS07”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- PEMS07 · split: unknown
  HF folder(s): PEMS07.
  
  Evidence
  
  “PEMS07 PEMS08”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- PEMS08 · split: unknown
  HF folder(s): PEMS08.
  
  Evidence
  
  “PEMS08 PEMS Bay”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- PEMS Bay · split: unknown
  HF folder(s): PEMS_BAY.
  
  Evidence
  
  “PEMS Bay Los-Loop”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Los-Loop · split: unknown
  HF folder(s): LOS_LOOP.
  
  Evidence
  
  “Los-Loop Beijing Subway”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Beijing Subway · split: unknown
  HF folder(s): BEIJING_SUBWAY_30MIN.
  
  Evidence
  
  “Beijing Subway”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- SHMetro · split: unknown
  HF folder(s): SHMETRO.
  
  Evidence
  
  “SHMetro HZMetro”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- HZMetro · split: unknown
  HF folder(s): HZMETRO.
  
  Evidence
  
  “HZMetro Q-Traffic”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Q-Traffic · split: unknown
  HF folder(s): Q-TRAFFIC.
  
  Evidence
  
  “Q-Traffic Subseasonal”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Subseasonal · split: unknown
  HF folder(s): subseasonal.
  
  Evidence
  
  “Subseasonal”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Subseasonal Precipitation · split: unknown
  HF folder(s): subseasonal_precip.
  
  Evidence
  
  “Subseasonal Precipitation”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Covid19 Energy · split: unknown
  HF folder(s): covid19_energy.
  
  Evidence
  
  “Covid19 Energy”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- GEF12 · split: unknown
  HF folder(s): gfc12_load.
  
  Evidence
  
  “GEF12 GEF14”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- GEF14 · split: unknown
  HF folder(s): gfc14_load.
  
  Evidence
  
  “GEF14 GEF17”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- GEF17 · split: unknown
  HF folder(s): gfc17_load.
  
  Evidence
  
  “GEF17 PDB Spanish”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- PDB · split: unknown
  HF folder(s): pdb.
  
  Evidence
  
  “PDB Spanish”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Spanish · split: unknown
  HF folder(s): spain.
  
  Evidence
  
  “Spanish BDG-2 Hog”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- BDG-2 Hog · split: unknown
  HF folder(s): hog.
  
  Evidence
  
  “BDG-2 Hog BDG-2 Bull”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- BDG-2 Bull · split: unknown
  HF folder(s): bull.
  
  Evidence
  
  “BDG-2 Bull”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- BDG-2 Cockatoo · split: unknown
  HF folder(s): cockatoo.
  
  Evidence
  
  “BDG-2 Cockatoo”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- ELF · split: unknown
  HF folder(s): elf.
  
  Evidence
  
  “ELF London Smart Meters”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- London Smart Meters · split: unknown
  HF folder(s): london_smart_meters_with_missing.
  
  Evidence
  
  “London Smart Meters”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Wind Farms · split: unknown
  HF folder(s): wind_farms_with_missing.
  
  Evidence
  
  “Wind Farms”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Wind Power · split: unknown
  HF folder(s): wind_power.
  
  Evidence
  
  “Wind Power”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Solar Power · split: unknown
  HF folder(s): solar_power. AEMO 4-second solar power (Monash), not the LSTNet Alabama solar dataset in the GIFT-Eval test set.
  
  Evidence
  
  “Solar Power”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Oikolab Weather · split: unknown
  HF folder(s): oikolab_weather.
  
  Evidence
  
  “Oikolab Weather”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Elecdemand · split: unknown
  HF folder(s): elecdemand.
  
  Evidence
  
  “Elecdemand”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Covid Mobility · split: unknown
  HF folder(s): covid_mobility.
  
  Evidence
  
  “Covid Mobility”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Kaggle Web Traffic Weekly · split: unknown
  HF folder(s): kaggle_web_traffic_weekly.
  
  Evidence
  
  “Kaggle Web Traffic Weekly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Extended Web Traffic · split: unknown
  HF folder(s): extended_web_traffic_with_missing.
  
  Evidence
  
  “Extended Web Traffic”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- M1 Yearly · split: unknown
  HF folder(s): m1_yearly.
  
  Evidence
  
  “M1 Yearly M1 Quarterly”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- M1 Quarterly · split: unknown
  HF folder(s): m1_quarterly.
  
  Evidence
  
  “M1 Quarterly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- M1 Monthly · split: unknown
  HF folder(s): m1_monthly.
  
  Evidence
  
  “M1 Monthly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- M3 Yearly · split: unknown
  HF folder(s): monash_m3_yearly.
  
  Evidence
  
  “M3 Yearly M3 Quarterly”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- M3 Quarterly · split: unknown
  HF folder(s): monash_m3_quarterly.
  
  Evidence
  
  “M3 Quarterly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- M3 Monthly · split: unknown
  HF folder(s): monash_m3_monthly.
  
  Evidence
  
  “M3 Monthly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- M3 Other · split: unknown
  HF folder(s): monash_m3_other.
  
  Evidence
  
  “M3 Other NN5 Daily”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- NN5 Daily · split: unknown
  HF folder(s): nn5_daily_with_missing.
  
  Evidence
  
  “NN5 Daily NN5 Weekly”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- NN5 Weekly · split: unknown
  HF folder(s): nn5_weekly.
  
  Evidence
  
  “NN5 Weekly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Tourism Yearly · split: unknown
  HF folder(s): tourism_yearly.
  
  Evidence
  
  “Tourism Yearly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Tourism Quarterly · split: unknown
  HF folder(s): tourism_quarterly.
  
  Evidence
  
  “Tourism Quarterly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Tourism Monthly · split: unknown
  HF folder(s): tourism_monthly.
  
  Evidence
  
  “Tourism Monthly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- CIF 2016 · split: unknown
  HF folder(s): cif_2016_12, cif_2016_6.
  
  Evidence
  
  “CIF 2016 Traffic Weekly”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Traffic Weekly (Monash) · split: unknown
  HF folder(s): traffic_weekly. Monash weekly aggregation of the 862-sensor traffic dataset (registry id monash-traffic-weekly).
  
  Evidence
  
  “Traffic Weekly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Traffic (PeMS San Francisco Bay, 862 sensors) · split: unknown
  HF folder(s): traffic_hourly. Monash 'traffic_hourly' = the 862-sensor San Francisco traffic dataset of LSTNet, i.e. the long-horizon Traffic dataset (registry id traffic-862).
  
  Evidence
  
  “Traffic Hourly”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Australian Electricity Demand · split: unknown
  HF folder(s): australian_electricity_demand.
  
  Evidence
  
  “Australian Electricity Demand”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Rideshare · split: unknown
  HF folder(s): rideshare_with_missing.
  
  Evidence
  
  “Rideshare Sunspot”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Sunspot · split: unknown
  HF folder(s): sunspot_with_missing.
  
  Evidence
  
  “Sunspot Vehicle Trips”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Vehicle Trips · split: unknown
  HF folder(s): vehicle_trips_with_missing.
  
  Evidence
  
  “Vehicle Trips”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Weather · split: unknown
  HF folder(s): weather. Monash 'weather' (Australian BOM, 3,010 daily series; Table 14 source column: Monash), NOT the Jena weather data used in GIFT-Eval and long-horizon.
  
  Evidence
  
  “Weather FRED MD”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- FRED MD · split: unknown
  HF folder(s): fred_md.
  
  Evidence
  
  “FRED MD Pedestrian Counts”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Pedestrian Counts · split: unknown
  HF folder(s): pedestrian_counts.
  
  Evidence
  
  “Pedestrian Counts”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Bitcoin · split: unknown
  HF folder(s): bitcoin_with_missing.
  
  Evidence
  
  “Bitcoin KDD Cup 2022”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- KDD Cup 2022 · split: unknown
  HF folder(s): kdd2022. Not the KDD Cup 2018 air-quality dataset that is in the GIFT-Eval test set.
  
  Evidence
  
  “KDD Cup 2022”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- GoDaddy · split: unknown
  HF folder(s): godaddy.
  
  Evidence
  
  “GoDaddy Favorita Sales”
  
  arxiv.org · paper · Table 14 (dataset column; following row names included to reach the minimum quote length) · retrieved 2026-10-15
- Favorita Sales · split: unknown
  HF folder(s): favorita_sales.
  
  Evidence
  
  “Favorita Sales”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Favorita Transactions · split: unknown
  HF folder(s): favorita_transactions.
  
  Evidence
  
  “Favorita Transactions”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- China Air Quality · split: unknown
  HF folder(s): china_air_quality.
  
  Evidence
  
  “China Air Quality”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Beijing Air Quality · split: unknown
  HF folder(s): beijing_air_quality.
  
  Evidence
  
  “Beijing Air Quality”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Residential Load Power · split: unknown
  HF folder(s): residential_load_power.
  
  Evidence
  
  “Residential Load Power”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Residential PV Power · split: unknown
  HF folder(s): residential_pv_power.
  
  Evidence
  
  “Residential PV Power”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- CDC FluView ILINet (LOTSA) · split: unknown
  HF folder(s): cdc_fluview_ilinet. Same source (CDC FluView) as the long-horizon ILI dataset (registry id cdc-fluview-ilinet).
  
  Evidence
  
  “CDC Fluview ILINet”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- CDC Fluview WHO NREVSS · split: unknown
  HF folder(s): cdc_fluview_who_nrevss.
  
  Evidence
  
  “CDC Fluview WHO NREVSS”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
- Project Tycho · split: unknown
  HF folder(s): project_tycho.
  
  Evidence
  
  “Project Tycho”
  
  arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15

Other declared training data

Jena Weather (GIFT-Eval) · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
BizITObs - Application · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
BizITObs - Service · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
BizITObs - L2C · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Bitbrains - Fast Storage · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Bitbrains - rnd · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Restaurant (Recruit Restaurant Visitor Forecasting) · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
ETT1 (GIFT-Eval) · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
ETT2 (GIFT-Eval) · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Loop Seattle (LibCity) · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
SZ-Taxi (LibCity) · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
M_DENSE (LibCity) · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Solar (LSTNet, 137 Alabama PV plants) · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Hierarchical Sales (Mancuso et al., 2020) · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
M4 Yearly · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
M4 Quarterly · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
M4 Monthly · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
M4 Weekly · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
M4 Daily · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
M4 Hourly · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Hospital · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
COVID Deaths · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
US Births · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Saugeen River Flow · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Temperature Rain · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
KDD Cup 2018 · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
Car Parts · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15
ElectricityLoadDiagrams20112014 (UCI) · split: train of gift-eval
Model card links Salesforce/GiftEval (the GIFT-Eval benchmark dataset) and says only non-leaking historical context was used.

Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

Declared exclusions

Benchmark GIFT-Eval · test portion excluded
Evidence

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Benchmark cells

GIFT-Eval

Training data seen Jena Weather (GIFT-Eval) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen BizITObs - Application · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen BizITObs - Service · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen BizITObs - L2C · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen Bitbrains - Fast Storage · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen Bitbrains - rnd · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen Restaurant (Recruit Restaurant Visitor Forecasting) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen ETT1 (GIFT-Eval) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen ETT2 (GIFT-Eval) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen Loop Seattle (LibCity) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen SZ-Taxi (LibCity) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen M_DENSE (LibCity) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen Solar (LSTNet, 137 Alabama PV plants) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen Hierarchical Sales (Mancuso et al., 2020) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen M4 Yearly · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen M4 Quarterly · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen M4 Monthly · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen M4 Weekly · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen M4 Daily · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen M4 Hourly · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen Hospital · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen COVID Deaths · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen US Births · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen Saugeen River Flow · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen Temperature Rain · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen KDD Cup 2018 · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen Car Parts · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

Training data seen ElectricityLoadDiagrams20112014 (UCI) · only the training split was used, not the benchmark's test data; the test portion was explicitly excluded

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“"model_link": "https://huggingface.co/ibm-research/ttm-r3",”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

“"testdata_leakage": "No"”

raw.githubusercontent.com · leaderboard · results/TTM-R3-PT/config.json · retrieved 2026-10-15

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

Related data seen ETTh1 · related dataset ETT1 (GIFT-Eval) was used

Evidence (3)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“From Informer (Zhou et al., 2021) we utilize ETT1 and ETT2 datasets, which denote electricity transformer temperature”

arxiv.org · paper · Appendix D · retrieved 2026-10-15

“ETTh1&ETTh2 7 17,420”

arxiv.org · paper · Table 1 · retrieved 2026-10-15

Related data seen ETTh2 · related dataset ETT2 (GIFT-Eval) was used

Evidence (3)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“From Informer (Zhou et al., 2021) we utilize ETT1 and ETT2 datasets, which denote electricity transformer temperature”

arxiv.org · paper · Appendix D · retrieved 2026-10-15

“ETTh1&ETTh2 7 17,420”

arxiv.org · paper · Table 1 · retrieved 2026-10-15

Related data seen ETTm1 · related dataset ETT1 (GIFT-Eval) was used

Evidence (3)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“From Informer (Zhou et al., 2021) we utilize ETT1 and ETT2 datasets, which denote electricity transformer temperature”

arxiv.org · paper · Appendix D · retrieved 2026-10-15

“ETTm1 &ETTm2 7 69,680”

arxiv.org · paper · Table 1 · retrieved 2026-10-15

Related data seen ETTm2 · related dataset ETT2 (GIFT-Eval) was used

Evidence (3)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“From Informer (Zhou et al., 2021) we utilize ETT1 and ETT2 datasets, which denote electricity transformer temperature”

arxiv.org · paper · Appendix D · retrieved 2026-10-15

“ETTm1 &ETTm2 7 69,680”

arxiv.org · paper · Table 1 · retrieved 2026-10-15

Related data seen Electricity (ECL, 321 clients) · related dataset ElectricityLoadDiagrams20112014 (UCI) was used

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“The raw dataset is in https://archive.ics.uci.edu/ml/datasets/ElectricityLoadDiagrams20112014.”

raw.githubusercontent.com · readme · Electricity consumption · retrieved 2026-10-15

“Because the some dimensions are equal to 0. So we eliminate the records in 2011. Final we get data contains electircity consumption of 321 clients from 2012 to 2014.”

raw.githubusercontent.com · readme · Electricity consumption · retrieved 2026-10-15

“https://archive.ics.uci.edu/ml/datasets/ElectricityLoadDiagrams20112014”

arxiv.org · paper · Section 4, footnote 1 · retrieved 2026-10-15

Seen, split unclear Traffic (PeMS San Francisco Bay, 862 sensors) · the dataset was used; the source does not say which part (via GIFT-Eval Pretrain (GiftEvalPretrain))

Evidence (2)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“Traffic Hourly”

arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15

Related data seen Weather (Jena, 2020; Autoformer) · related dataset Jena Weather (GIFT-Eval) was used

Evidence (4)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“We incorporate Jena Weather5 dataset following Autoformer (Wu et al., 2021).”

arxiv.org · paper · Appendix D (footnote 5 points to https://www.bgc-jena.mpg.de/wetter/) · retrieved 2026-10-15

“is recorded every 10 minutes for 2020 whole year, which contains 21 meteorological indicators, such as air temperature, humidity, etc.”

arxiv.org · paper · Section 4 (Datasets) · retrieved 2026-10-15

“https://www.bgc-jena.mpg.de/wetter/”

arxiv.org · paper · Section 4, footnote 3 · retrieved 2026-10-15

Unknown Exchange-Rate · training data not disclosed in enough detail

Related data seen ILI (CDC influenza-like illness, national) · related dataset CDC FluView ILINet (LOTSA) was used (via GIFT-Eval Pretrain (GiftEvalPretrain))

Evidence (5)

“Datasets from [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), and [Train](https://huggingface.co/datasets/Salesforce/GiftEval) (Non-leaking historical context).”

huggingface.co · model card · Training Data section · retrieved 2026-10-15

“CDC Fluview ILINet”

arxiv.org · paper · Table 14 (dataset column) · 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

Unknown TSB-AD-U (TSB-AD univariate) · training data not disclosed in enough detail

Unknown TSB-AD-M (TSB-AD multivariate) · training data not disclosed in enough detail

Unknown UCR Time Series Anomaly Archive (Hexagon ML/UCR, KDD Cup 2021) · training data not disclosed in enough detail

Unknown Server Machine Dataset (SMD) · training data not disclosed in enough detail

Unknown Mars Science Laboratory (MSL) telemetry anomaly dataset · training data not disclosed in enough detail

Unknown Soil Moisture Active Passive (SMAP) telemetry anomaly dataset · training data not disclosed in enough detail

Unknown Pooled Server Metrics (PSM) · training data not disclosed in enough detail

Unknown Secure Water Treatment (SWaT) · training data not disclosed in enough detail

Unknown Yahoo S5 Labeled Anomaly Detection Dataset (Yahoo Webscope S5) · training data not disclosed in enough detail

Unknown Numenta Anomaly Benchmark (NAB) · training data not disclosed in enough detail

Time-series classification

Unknown UCR Time Series Classification Archive (2018) · training data not disclosed in enough detail

Unknown UEA Multivariate Time Series Classification Archive (2018) · training data not disclosed in enough detail

Notes

Non-commercial research release; this is the checkpoint linked from the GIFT-Eval leaderboard entries TTM-R3-PT / TTM-R3-FT (both marked testdata_leakage 'No'). Card says data come from GiftEvalPretrain and GIFT-Eval 'Train' with non-leaking historical context, plus KernelSynth synthetic data; which GiftEvalPretrain datasets were used is not listed. No R3 paper yet ('To be released').

Sources

TTM-R3 model card · model card · retrieved 2026-10-15
GIFT-Eval leaderboard config for TTM-R3-PT · leaderboard · retrieved 2026-10-15
GIFT-Eval leaderboard config for TTM-R3-FT · leaderboard · retrieved 2026-10-15
GIFT-Eval TTM-R3 notebook · code · retrieved 2026-10-15