Add breakdown by task type

pages/fev_bench.py

@@ -19,6 +19,7 @@ from src.task_groups import (
     DOMAIN_GROUPS,
     FREQUENCY_GROUPS,
     MINI_TASKS,
+    TASK_TYPE_GROUPS,
 )
 from src.utils import (
     COLORS,
@@ -38,9 +39,10 @@ SORT_COL = "win_rate"
 AVAILABLE_METRICS = ["SQL", "MASE", "WQL", "WAPE"]
 
 # Group type options
-GROUP_TYPES = ["Full (100 tasks)", "Mini (20 tasks)", "By frequency", "By domain"]
+GROUP_TYPES = ["Full (100 tasks)", "Mini (20 tasks)", "By frequency", "By domain", "By task type"]
 FREQUENCY_OPTIONS = list(FREQUENCY_GROUPS.keys())
 DOMAIN_OPTIONS = list(DOMAIN_GROUPS.keys())
+TASK_TYPE_OPTIONS = list(TASK_TYPE_GROUPS.keys())
 
 def get_subset_description(group_type: str, subgroup: str | None, num_tasks: int) -> str:
     """Generate a description of the current subset."""
@@ -51,6 +53,8 @@ def get_subset_description(group_type: str, subgroup: str | None, num_tasks: int
         subset_desc = "from the **fev-bench-mini** subset"
     elif group_type == "By frequency":
         subset_desc = f"with **{subgroup.lower()}** frequency"
+    elif group_type == "By task type":
+        subset_desc = f"of type **{subgroup.lower()}**"
     else:  # By domain
         subset_desc = f"from the **{subgroup}** domain"
     paper_link = "[fev-bench: A Realistic Benchmark for Time Series Forecasting](https://arxiv.org/abs/2509.26468)"
@@ -73,6 +77,9 @@ GROUP_DIR_MAPPING = {
     "Econ": "domain_econ",
     "Health": "domain_health",
     "Retail": "domain_retail",
+    "Univariate": "task_type_univariate",
+    "Covariate-informed": "task_type_covariate_informed",
+    "Multivariate": "task_type_multivariate",
 }
 
 
@@ -104,6 +111,8 @@ with st.sidebar:
         selected_subgroup = st.selectbox("Frequency", options=FREQUENCY_OPTIONS)
     elif selected_group_type == "By domain":
         selected_subgroup = st.selectbox("Domain", options=DOMAIN_OPTIONS)
+    elif selected_group_type == "By task type":
+        selected_subgroup = st.selectbox("Task type", options=TASK_TYPE_OPTIONS)
 
     # Determine the directory to load tables from
     if selected_group_type in ["Full (100 tasks)", "Mini (20 tasks)"]:
@@ -113,6 +122,8 @@ with st.sidebar:
         group_dir = GROUP_DIR_MAPPING[selected_subgroup]
         if selected_group_type == "By frequency":
             task_list = FREQUENCY_GROUPS[selected_subgroup]
+        elif selected_group_type == "By task type":
+            task_list = TASK_TYPE_GROUPS[selected_subgroup]
         else:
             task_list = DOMAIN_GROUPS[selected_subgroup]
 

save_tables.py

@@ -13,7 +13,7 @@ sys.path.append(str(Path(__file__).parent))
 import fev
 import pandas as pd
 
-from src.task_groups import ALL_TASKS, DOMAIN_GROUPS, FREQUENCY_GROUPS, MINI_TASKS
+from src.task_groups import ALL_TASKS, DOMAIN_GROUPS, FREQUENCY_GROUPS, MINI_TASKS, TASK_TYPE_GROUPS
 
 GITHUB_REPO = "autogluon/fev"
 RESULTS_PATH = "benchmarks/fev_bench/results"
@@ -56,6 +56,9 @@ TASK_GROUPS = {
     "domain_econ": DOMAIN_GROUPS["Econ"],
     "domain_health": DOMAIN_GROUPS["Health"],
     "domain_retail": DOMAIN_GROUPS["Retail"],
+    "task_type_univariate": TASK_TYPE_GROUPS["Univariate"],
+    "task_type_covariate_informed": TASK_TYPE_GROUPS["Covariate-informed"],
+    "task_type_multivariate": TASK_TYPE_GROUPS["Multivariate"],
 }
 
 

src/task_groups.py

@@ -181,14 +181,67 @@ DOMAIN_GROUPS = {
         "SZ_TAXI_15T", "SZ_TAXI_1H",
     ],
 }
+# Task type groupings (overlapping: a multivariate task with covariates
+# belongs to both "Covariate-informed" and "Multivariate").
+# - Multivariate: target is a list of columns
+# - Covariate-informed: known_dynamic_columns or past_dynamic_columns is non-empty
+# - Univariate: neither of the above
+TASK_TYPE_GROUPS = {
+    "Univariate": [
+        "LOOP_SEATTLE_1D", "LOOP_SEATTLE_1H", "LOOP_SEATTLE_5T",
+        "M_DENSE_1D", "M_DENSE_1H",
+        "SZ_TAXI_15T", "SZ_TAXI_1H",
+        "australian_tourism", "ecdc_ili",
+        "ercot_1D", "ercot_1H", "ercot_1M", "ercot_1W",
+        "hierarchical_sales_1D", "hierarchical_sales_1W",
+        "hospital", "hospital_admissions_1D", "hospital_admissions_1W",
+        "redset_15T", "redset_1H", "redset_5T",
+        "restaurant",
+        "solar_1D", "solar_1W",
+        "uk_covid_utla_1D/new", "uk_covid_utla_1W/cumulative",
+        "us_consumption_1M", "us_consumption_1Q", "us_consumption_1Y",
+        "world_co2_emissions", "world_life_expectancy", "world_tourism",
+    ],
+    "Covariate-informed": [
+        "entsoe_15T", "entsoe_1H", "entsoe_30T",
+        "epf_be", "epf_de", "epf_fr", "epf_np", "epf_pjm",
+        "favorita_stores_1D", "favorita_stores_1M", "favorita_stores_1W",
+        "favorita_transactions_1D", "favorita_transactions_1M", "favorita_transactions_1W",
+        "fred_md_2025/cee", "fred_qd_2025/cee",
+        "gvar", "hermes",
+        "kdd_cup_2022_10T", "kdd_cup_2022_1D", "kdd_cup_2022_30T",
+        "m5_1D", "m5_1M", "m5_1W",
+        "proenfo_gfc12", "proenfo_gfc14", "proenfo_gfc17",
+        "rohlik_orders_1D", "rohlik_orders_1W", "rohlik_sales_1D", "rohlik_sales_1W",
+        "rossmann_1D", "rossmann_1W",
+        "solar_with_weather_15T", "solar_with_weather_1H",
+        "uci_air_quality_1D", "uci_air_quality_1H",
+        "uk_covid_nation_1D/cumulative", "uk_covid_nation_1D/new",
+        "uk_covid_nation_1W/cumulative", "uk_covid_nation_1W/new",
+        "walmart",
+    ],
+    "Multivariate": [
+        "ETT_15T", "ETT_1D", "ETT_1H", "ETT_1W",
+        "bizitobs_l2c_1H", "bizitobs_l2c_5T",
+        "boomlet_1062", "boomlet_1209", "boomlet_1225", "boomlet_1230", "boomlet_1282",
+        "boomlet_1487", "boomlet_1631", "boomlet_1676", "boomlet_1855", "boomlet_1975",
+        "boomlet_2187", "boomlet_285", "boomlet_619", "boomlet_772", "boomlet_963",
+        "fred_md_2025/cee", "fred_md_2025/macro", "fred_qd_2025/cee", "fred_qd_2025/macro",
+        "gvar",
+        "jena_weather_10T", "jena_weather_1D", "jena_weather_1H",
+        "uci_air_quality_1D", "uci_air_quality_1H",
+        "uk_covid_nation_1D/cumulative", "uk_covid_nation_1D/new",
+        "uk_covid_nation_1W/cumulative", "uk_covid_nation_1W/new",
+    ],
+}
 
 
 def get_task_group(group_type: str, group_value: str | None = None) -> list[str]:
     """Get the list of tasks for a given group type and value.
 
     Args:
-        group_type: One of "full", "mini", "frequency", "domain"
-        group_value: Required for "frequency" and "domain" types
+        group_type: One of "full", "mini", "frequency", "domain", "task_type"
+        group_value: Required for "frequency", "domain", and "task_type" types
 
     Returns:
         List of task names belonging to the group
@@ -205,5 +258,9 @@ def get_task_group(group_type: str, group_value: str | None = None) -> list[str]
         if group_value is None:
             raise ValueError("group_value required for domain grouping")
         return DOMAIN_GROUPS[group_value]
+    elif group_type == "task_type":
+        if group_value is None:
+            raise ValueError("group_value required for task_type grouping")
+        return TASK_TYPE_GROUPS[group_value]
     else:
         raise ValueError(f"Unknown group_type: {group_type}")

tables/task_type_covariate_informed/leaderboard_MASE.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Chronos-2,85.25641025641025,37.85799069972645,0.0,1.2462164325,0.0,0.0
+Toto-2.0-1B,71.7032967032967,29.050115763331195,0.0,2.9384434409375,0.0,0.0
+TabPFN-TS-3,71.06227106227107,34.106843589937796,0.0,233.19124419048612,0.0,0.0
+Toto-2.0-2.5B,70.97069597069597,29.325569671639194,0.0,6.392388657648901,0.0,0.0
+Toto-2.0-313m,69.87179487179488,28.75756667123792,0.0,1.415961499111262,0.0,0.0
+TabPFN-TS,67.35347985347985,33.645363857682895,0.0,94.5240759370583,0.0,2.380952380952381
+TiRex,67.03296703296702,28.470636641084333,0.0,0.6630511256654228,0.023809523809523808,0.0
+TimesFM-2.5,66.11721611721612,27.784643347991,0.0,1.6456731042857142,0.21428571428571427,0.0
+Toto-2.0-22m,64.1025641025641,27.746780910077852,0.0,0.5999408045710785,0.0,0.0
+FlowState,63.827838827838825,27.18964779800085,0.0,3.149809327083334,0.16666666666666666,0.0
+Moirai-2.0,57.32600732600732,27.011208854073608,0.0,0.8126894325,0.16666666666666666,0.0
+CatBoost,55.12820512820513,27.450740665065144,28.452690788739496,0.5293052348809524,0.0,0.0
+Toto-1.0,52.83882783882784,25.062514275946356,0.0,21.010914669873948,0.16666666666666666,0.0
+Chronos-Bolt,52.65567765567766,25.633108331049936,0.0,0.7454693648227612,0.0,0.0
+LightGBM,52.28937728937729,26.138069870715697,2.7357501468749996,0.4490329255357143,0.0,0.0
+Toto-2.0-4m,51.00732600732599,25.059586999925887,0.0,0.5331319968382353,0.0,0.0
+Sundial-Base,46.062271062271066,23.050755938875334,0.0,8.6058723475,0.023809523809523808,0.0
+Stat. Ensemble,43.63553113553114,17.07188261534265,0.0,238.7019323257143,0.0,2.380952380952381
+TFT,38.00366300366299,16.610547189801082,840.0363191524633,2.784774613627451,0.0,0.0
+PatchTST,34.70695970695971,13.580115395669367,1025.4073311141667,1.489614424754902,0.0,0.0
+AutoTheta,31.959706959706956,11.019039468741898,0.0,3.78152038,0.0,0.0
+DeepAR,31.5018315018315,14.551541760519592,1785.5292291445587,1.8718095706431082,0.0,4.761904761904762
+AutoETS,29.67032967032967,-6.726032194167697,0.0,4.6384753278664625,0.0,0.0
+AutoARIMA,25.77838827838828,7.194406163199618,0.0,95.12863658364125,0.0,2.380952380952381
+Seasonal Naive,19.871794871794872,0.0,0.0,0.470381465,0.0,0.0
+Naive,16.254578754578752,-18.492832604363784,0.0,0.47363605499999994,0.0,0.0
+Drift,14.01098901098901,-17.92857450946139,0.0,0.4627528775,0.0,0.0

tables/task_type_covariate_informed/leaderboard_SQL.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Chronos-2,89.74358974358974,47.03439239650638,0.0,1.2462164325,0.0,0.0
+TiRex,75.36630036630036,38.67793124651509,0.0,0.6630511256654228,0.023809523809523808,0.0
+Toto-2.0-1B,74.72527472527474,38.89265863808164,0.0,2.9384434409375,0.0,0.0
+Toto-2.0-2.5B,74.72527472527472,38.77117816788853,0.0,6.392388657648901,0.0,0.0
+TabPFN-TS-3,72.89377289377289,43.34821010942925,0.0,233.19124419048612,0.0,0.0
+Toto-2.0-313m,72.89377289377289,38.74850022403288,0.0,1.415961499111262,0.0,0.0
+TabPFN-TS,71.56593406593407,42.46951390177763,0.0,94.5240759370583,0.0,2.380952380952381
+TimesFM-2.5,69.59706959706959,37.356310446995735,0.0,1.6456731042857142,0.21428571428571427,0.0
+Toto-2.0-22m,68.13186813186813,37.59770290848886,0.0,0.5999408045710785,0.0,0.0
+FlowState,67.94871794871793,36.65564931062223,0.0,3.149809327083334,0.16666666666666666,0.0
+Moirai-2.0,61.996336996337,36.59258743049962,0.0,0.8126894325,0.16666666666666666,0.0
+Chronos-Bolt,59.98168498168499,35.87139576468958,0.0,0.7454693648227612,0.0,0.0
+Toto-1.0,58.699633699633694,35.17359783525491,0.0,21.010914669873948,0.16666666666666666,0.0
+Toto-2.0-4m,58.05860805860805,35.40744128959241,0.0,0.5331319968382353,0.0,0.0
+TFT,42.765567765567766,25.24922731698379,840.0363191524633,2.784774613627451,0.0,0.0
+Sundial-Base,40.56776556776556,27.96144140268967,0.0,8.6058723475,0.023809523809523808,0.0
+Stat. Ensemble,39.14835164835164,21.00789975438786,0.0,238.7019323257143,0.0,2.380952380952381
+PatchTST,35.66849816849816,21.575077599958682,1025.4073311141667,1.489614424754902,0.0,0.0
+DeepAR,33.928571428571416,22.083135288368496,1785.5292291445587,1.8718095706431082,0.0,4.761904761904762
+CatBoost,32.78388278388278,23.128137800086222,28.452690788739496,0.5293052348809524,0.0,0.0
+AutoARIMA,30.265567765567763,15.177379671415093,0.0,95.12863658364125,0.0,2.380952380952381
+LightGBM,30.21978021978022,21.737255944887302,2.7357501468749996,0.4490329255357143,0.0,0.0
+AutoETS,27.93040293040293,-25.161340235868156,0.0,4.6384753278664625,0.0,0.0
+AutoTheta,26.831501831501832,8.37504381956522,0.0,3.78152038,0.0,0.0
+Seasonal Naive,15.613553113553113,0.0,0.0,0.470381465,0.0,0.0
+Naive,10.439560439560438,-33.03620398638194,0.0,0.47363605499999994,0.0,0.0
+Drift,7.509157509157507,-31.75596044124429,0.0,0.4627528775,0.0,0.0

tables/task_type_covariate_informed/leaderboard_WAPE.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Chronos-2,82.60073260073261,39.97910055229871,0.0,1.2462164325,0.0,0.0
+Toto-2.0-1B,76.37362637362638,32.1259584298953,0.0,2.9384434409375,0.0,0.0
+TabPFN-TS-3,73.62637362637362,37.24548801189469,0.0,233.19124419048612,0.0,0.0
+Toto-2.0-2.5B,73.44322344322343,31.798726646474805,0.0,6.392388657648901,0.0,0.0
+Toto-2.0-313m,72.34432234432234,31.547170325205375,0.0,1.415961499111262,0.0,0.0
+TabPFN-TS,70.83333333333334,36.035457638526424,0.0,94.5240759370583,0.0,2.380952380952381
+TiRex,66.30036630036629,30.37469958526301,0.0,0.6630511256654228,0.023809523809523808,0.0
+Toto-2.0-22m,63.91941391941393,29.777759860762497,0.0,0.5999408045710785,0.0,0.0
+TimesFM-2.5,63.827838827838825,29.478887305815647,0.0,1.6456731042857142,0.21428571428571427,0.0
+FlowState,60.34798534798536,28.91770981196896,0.0,3.149809327083334,0.16666666666666666,0.0
+Moirai-2.0,56.684981684981686,28.783939901885137,0.0,0.8126894325,0.16666666666666666,0.0
+LightGBM,53.38827838827839,28.026675823648763,2.7357501468749996,0.4490329255357143,0.0,0.0
+CatBoost,53.205128205128204,27.596357187205513,28.452690788739496,0.5293052348809524,0.0,0.0
+Toto-1.0,51.73992673992673,26.4221714932126,0.0,21.010914669873948,0.16666666666666666,0.0
+Chronos-Bolt,50.732600732600744,26.172791737408396,0.0,0.7454693648227612,0.0,0.0
+Toto-2.0-4m,47.71062271062271,25.500630381090716,0.0,0.5331319968382353,0.0,0.0
+Sundial-Base,46.978021978021985,24.560922790508542,0.0,8.6058723475,0.023809523809523808,0.0
+Stat. Ensemble,42.53663003663003,18.65248010325733,0.0,238.7019323257143,0.0,2.380952380952381
+TFT,39.1941391941392,17.55129235888411,840.0363191524633,2.784774613627451,0.0,0.0
+PatchTST,32.05128205128205,12.082418084936153,1025.4073311141667,1.489614424754902,0.0,0.0
+AutoETS,30.586080586080588,-2.7290136569638745,0.0,4.6384753278664625,0.0,0.0
+DeepAR,29.48717948717949,14.30320734363062,1785.5292291445587,1.8718095706431082,0.0,4.761904761904762
+AutoTheta,29.120879120879117,12.238855032317774,0.0,3.78152038,0.0,0.0
+AutoARIMA,26.968864468864467,11.608332472472217,0.0,95.12863658364125,0.0,2.380952380952381
+Naive,22.023809523809522,-9.55304348683621,0.0,0.47363605499999994,0.0,0.0
+Seasonal Naive,17.03296703296703,0.0,0.0,0.470381465,0.0,0.0
+Drift,16.941391941391938,-11.985879428309133,0.0,0.4627528775,0.0,0.0

tables/task_type_covariate_informed/leaderboard_WQL.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Chronos-2,86.53846153846155,50.25077498745439,0.0,1.2462164325,0.0,0.0
+TabPFN-TS-3,77.56410256410258,47.84852116161721,0.0,233.19124419048612,0.0,0.0
+Toto-2.0-1B,77.56410256410257,43.86639294767475,0.0,2.9384434409375,0.0,0.0
+Toto-2.0-2.5B,75.64102564102565,43.37032468187005,0.0,6.392388657648901,0.0,0.0
+Toto-2.0-313m,75.54945054945054,43.447102168825424,0.0,1.415961499111262,0.0,0.0
+TabPFN-TS,73.48901098901098,46.57775946986645,0.0,94.5240759370583,0.0,2.380952380952381
+TiRex,71.33699633699634,42.05271803405567,0.0,0.6630511256654228,0.023809523809523808,0.0
+Toto-2.0-22m,67.94871794871794,41.7421059135865,0.0,0.5999408045710785,0.0,0.0
+TimesFM-2.5,67.76556776556775,41.339265283988716,0.0,1.6456731042857142,0.21428571428571427,0.0
+FlowState,66.20879120879121,40.63664377134849,0.0,3.149809327083334,0.16666666666666666,0.0
+Moirai-2.0,64.01098901098901,40.57999071515723,0.0,0.8126894325,0.16666666666666666,0.0
+Chronos-Bolt,58.79120879120878,38.93740380330451,0.0,0.7454693648227612,0.0,0.0
+Toto-1.0,58.33333333333333,38.88016049043232,0.0,21.010914669873948,0.16666666666666666,0.0
+Toto-2.0-4m,54.76190476190476,38.1771523471722,0.0,0.5331319968382353,0.0,0.0
+Sundial-Base,43.13186813186813,32.41302088995285,0.0,8.6058723475,0.023809523809523808,0.0
+TFT,41.57509157509158,27.0102097648108,840.0363191524633,2.784774613627451,0.0,0.0
+Stat. Ensemble,37.95787545787545,23.762019047847925,0.0,238.7019323257143,0.0,2.380952380952381
+LightGBM,35.53113553113552,26.455638284100015,2.7357501468749996,0.4490329255357143,0.0,0.0
+PatchTST,34.478021978021964,23.070595231883427,1025.4073311141667,1.489614424754902,0.0,0.0
+DeepAR,34.2032967032967,24.509565155499104,1785.5292291445587,1.8718095706431082,0.0,4.761904761904762
+CatBoost,33.79120879120879,26.015926682282032,28.452690788739496,0.5293052348809524,0.0,0.0
+AutoARIMA,29.807692307692307,20.163225583931876,0.0,95.12863658364125,0.0,2.380952380952381
+AutoETS,25.732600732600737,-22.25262533609125,0.0,4.6384753278664625,0.0,0.0
+AutoTheta,25.091575091575084,10.95860098159448,0.0,3.78152038,0.0,0.0
+Seasonal Naive,14.697802197802195,0.0,0.0,0.470381465,0.0,0.0
+Naive,11.17216117216117,-27.38359153519554,0.0,0.47363605499999994,0.0,0.0
+Drift,7.326007326007325,-29.07226056551304,0.0,0.4627528775,0.0,0.0

tables/task_type_covariate_informed/pairwise_MASE.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
+Chronos-2,Chronos-2,0.5,0.5,0.5,0.0,0.0,0.0
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+Chronos-2,Toto-2.0-2.5B,0.81,0.69,0.929,0.121,0.075,0.176
+Chronos-2,TabPFN-TS,0.69,0.548,0.833,0.063,0.018,0.113
+Chronos-2,Toto-2.0-313m,0.81,0.69,0.929,0.128,0.078,0.188
+Chronos-2,TiRex,0.762,0.619,0.881,0.131,0.081,0.191
+Chronos-2,TimesFM-2.5,0.833,0.714,0.929,0.139,0.085,0.202
+Chronos-2,FlowState,0.857,0.761,0.952,0.147,0.098,0.205
+Chronos-2,Toto-2.0-22m,0.833,0.714,0.929,0.14,0.091,0.195
+Chronos-2,CatBoost,0.786,0.667,0.905,0.143,0.087,0.197
+Chronos-2,Moirai-2.0,0.905,0.81,0.976,0.149,0.097,0.202
+Chronos-2,LightGBM,0.762,0.643,0.881,0.159,0.101,0.213
+Chronos-2,Toto-1.0,0.857,0.762,0.952,0.171,0.119,0.226
+Chronos-2,Chronos-Bolt,0.976,0.929,1.0,0.164,0.12,0.216
+Chronos-2,Seasonal Naive,0.976,0.929,1.0,0.379,0.315,0.439
+TabPFN-TS-3,Chronos-2,0.357,0.238,0.5,-0.06,-0.107,-0.017
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+Toto-2.0-2.5B,Chronos-2,0.19,0.071,0.31,-0.137,-0.213,-0.081
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+Toto-2.0-313m,Seasonal Naive,0.929,0.833,1.0,0.288,0.22,0.357
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+TimesFM-2.5,Chronos-Bolt,0.679,0.559,0.81,0.029,0.005,0.055
+TimesFM-2.5,Seasonal Naive,0.952,0.881,1.0,0.278,0.215,0.344
+FlowState,Chronos-2,0.143,0.048,0.239,-0.172,-0.258,-0.108
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+Moirai-2.0,FlowState,0.512,0.369,0.643,-0.002,-0.037,0.032
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+Moirai-2.0,Seasonal Naive,0.833,0.738,0.929,0.27,0.204,0.339
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+LightGBM,Moirai-2.0,0.452,0.31,0.595,-0.012,-0.073,0.047
+LightGBM,LightGBM,0.5,0.5,0.5,0.0,0.0,0.0
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+Toto-1.0,Chronos-Bolt,0.488,0.357,0.631,-0.008,-0.046,0.024
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+Seasonal Naive,Toto-2.0-1B,0.071,0.0,0.167,-0.409,-0.557,-0.294
+Seasonal Naive,Toto-2.0-2.5B,0.071,0.0,0.167,-0.415,-0.565,-0.296
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+Seasonal Naive,Toto-2.0-22m,0.095,0.024,0.19,-0.384,-0.544,-0.264
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+Seasonal Naive,Moirai-2.0,0.167,0.071,0.262,-0.37,-0.512,-0.256
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+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0

tables/task_type_covariate_informed/pairwise_SQL.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
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+Chronos-2,Toto-2.0-4m,0.905,0.81,0.976,0.18,0.129,0.233
+Chronos-2,TFT,0.881,0.786,0.952,0.291,0.211,0.362
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+TimesFM-2.5,Seasonal Naive,1.0,1.0,1.0,0.374,0.309,0.436
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+Seasonal Naive,Toto-2.0-22m,0.024,0.0,0.071,-0.603,-0.795,-0.446
+Seasonal Naive,Moirai-2.0,0.048,0.0,0.119,-0.577,-0.744,-0.425
+Seasonal Naive,Chronos-Bolt,0.024,0.0,0.071,-0.559,-0.715,-0.417
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+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0

tables/task_type_covariate_informed/pairwise_WAPE.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
+Chronos-2,Chronos-2,0.5,0.5,0.5,0.0,0.0,0.0
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+Chronos-2,Toto-2.0-22m,0.714,0.571,0.857,0.145,0.096,0.205
+Chronos-2,FlowState,0.833,0.714,0.952,0.156,0.095,0.212
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+Chronos-2,Moirai-2.0,0.833,0.714,0.929,0.157,0.103,0.212
+Chronos-2,LightGBM,0.786,0.667,0.905,0.166,0.111,0.22
+Chronos-2,Toto-1.0,0.833,0.714,0.929,0.184,0.136,0.242
+Chronos-2,Chronos-Bolt,0.952,0.881,1.0,0.187,0.134,0.243
+Chronos-2,Seasonal Naive,0.952,0.881,1.0,0.4,0.33,0.461
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+TabPFN-TS,Toto-1.0,0.738,0.595,0.881,0.131,0.053,0.209
+TabPFN-TS,Chronos-Bolt,0.762,0.642,0.881,0.134,0.061,0.204
+TabPFN-TS,Seasonal Naive,0.964,0.905,1.0,0.36,0.288,0.427
+TiRex,Chronos-2,0.19,0.071,0.333,-0.16,-0.246,-0.096
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+TiRex,TimesFM-2.5,0.56,0.405,0.702,0.013,-0.017,0.038
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+Toto-2.0-22m,Chronos-Bolt,0.667,0.524,0.81,0.049,0.006,0.099
+Toto-2.0-22m,Seasonal Naive,0.976,0.929,1.0,0.298,0.223,0.368
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+FlowState,Toto-2.0-313m,0.333,0.19,0.476,-0.038,-0.106,0.022
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+FlowState,CatBoost,0.5,0.357,0.643,0.018,-0.064,0.091
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+Moirai-2.0,TimesFM-2.5,0.393,0.262,0.524,-0.01,-0.047,0.028
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+Moirai-2.0,Moirai-2.0,0.5,0.5,0.5,0.0,0.0,0.0
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+Moirai-2.0,Toto-1.0,0.536,0.405,0.679,0.032,0.002,0.065
+Moirai-2.0,Chronos-Bolt,0.56,0.429,0.69,0.035,0.0,0.077
+Moirai-2.0,Seasonal Naive,0.857,0.738,0.952,0.288,0.211,0.358
+LightGBM,Chronos-2,0.214,0.095,0.333,-0.199,-0.283,-0.124
+LightGBM,Toto-2.0-1B,0.262,0.119,0.405,-0.06,-0.144,0.018
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+LightGBM,FlowState,0.476,0.333,0.619,-0.013,-0.089,0.062
+LightGBM,CatBoost,0.357,0.214,0.5,0.006,-0.036,0.046
+LightGBM,Moirai-2.0,0.452,0.31,0.619,-0.011,-0.076,0.049
+LightGBM,LightGBM,0.5,0.5,0.5,0.0,0.0,0.0
+LightGBM,Toto-1.0,0.524,0.381,0.667,0.022,-0.038,0.083
+LightGBM,Chronos-Bolt,0.595,0.429,0.738,0.025,-0.038,0.084
+LightGBM,Seasonal Naive,0.881,0.762,0.976,0.28,0.202,0.356
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+Toto-1.0,Toto-2.0-313m,0.19,0.071,0.31,-0.075,-0.12,-0.035
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+Toto-1.0,CatBoost,0.476,0.333,0.643,-0.016,-0.086,0.042
+Toto-1.0,Moirai-2.0,0.464,0.321,0.595,-0.033,-0.069,-0.002
+Toto-1.0,LightGBM,0.476,0.333,0.619,-0.022,-0.091,0.037
+Toto-1.0,Toto-1.0,0.5,0.5,0.5,0.0,0.0,0.0
+Toto-1.0,Chronos-Bolt,0.488,0.345,0.631,0.003,-0.043,0.048
+Toto-1.0,Seasonal Naive,0.881,0.762,0.976,0.264,0.186,0.337
+Chronos-Bolt,Chronos-2,0.048,0.0,0.119,-0.23,-0.322,-0.155
+Chronos-Bolt,Toto-2.0-1B,0.19,0.071,0.31,-0.088,-0.15,-0.034
+Chronos-Bolt,Toto-2.0-2.5B,0.119,0.024,0.214,-0.082,-0.139,-0.032
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+Chronos-Bolt,Toto-2.0-313m,0.143,0.048,0.262,-0.079,-0.139,-0.025
+Chronos-Bolt,TabPFN-TS,0.238,0.119,0.358,-0.154,-0.256,-0.065
+Chronos-Bolt,TiRex,0.274,0.143,0.405,-0.06,-0.103,-0.025
+Chronos-Bolt,TimesFM-2.5,0.345,0.226,0.476,-0.047,-0.084,-0.012
+Chronos-Bolt,Toto-2.0-22m,0.333,0.19,0.476,-0.051,-0.11,-0.006
+Chronos-Bolt,FlowState,0.393,0.262,0.524,-0.039,-0.086,0.004
+Chronos-Bolt,CatBoost,0.476,0.333,0.619,-0.02,-0.1,0.051
+Chronos-Bolt,Moirai-2.0,0.44,0.31,0.571,-0.037,-0.084,-0.0
+Chronos-Bolt,LightGBM,0.405,0.262,0.571,-0.026,-0.092,0.037
+Chronos-Bolt,Toto-1.0,0.512,0.369,0.655,-0.003,-0.051,0.041
+Chronos-Bolt,Chronos-Bolt,0.5,0.5,0.5,0.0,0.0,0.0
+Chronos-Bolt,Seasonal Naive,0.881,0.762,0.976,0.262,0.194,0.326
+Seasonal Naive,Chronos-2,0.048,0.0,0.119,-0.666,-0.856,-0.493
+Seasonal Naive,Toto-2.0-1B,0.024,0.0,0.071,-0.473,-0.641,-0.322
+Seasonal Naive,Toto-2.0-2.5B,0.048,0.0,0.119,-0.466,-0.629,-0.313
+Seasonal Naive,TabPFN-TS-3,0.024,0.0,0.071,-0.594,-0.765,-0.45
+Seasonal Naive,Toto-2.0-313m,0.048,0.0,0.119,-0.461,-0.633,-0.309
+Seasonal Naive,TabPFN-TS,0.036,0.0,0.095,-0.563,-0.746,-0.404
+Seasonal Naive,TiRex,0.071,0.0,0.167,-0.436,-0.594,-0.296
+Seasonal Naive,TimesFM-2.5,0.071,0.0,0.167,-0.418,-0.563,-0.298
+Seasonal Naive,Toto-2.0-22m,0.024,0.0,0.071,-0.424,-0.582,-0.286
+Seasonal Naive,FlowState,0.071,0.0,0.143,-0.407,-0.53,-0.297
+Seasonal Naive,CatBoost,0.167,0.071,0.286,-0.381,-0.542,-0.239
+Seasonal Naive,Moirai-2.0,0.143,0.048,0.262,-0.404,-0.558,-0.268
+Seasonal Naive,LightGBM,0.119,0.024,0.238,-0.389,-0.553,-0.253
+Seasonal Naive,Toto-1.0,0.119,0.024,0.238,-0.359,-0.508,-0.229
+Seasonal Naive,Chronos-Bolt,0.119,0.024,0.238,-0.355,-0.484,-0.241
+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0

tables/task_type_covariate_informed/pairwise_WQL.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
+Chronos-2,Chronos-2,0.5,0.5,0.5,0.0,0.0,0.0
+Chronos-2,Toto-2.0-1B,0.667,0.524,0.81,0.114,0.062,0.174
+Chronos-2,TabPFN-TS-3,0.548,0.405,0.69,0.046,-0.004,0.09
+Chronos-2,Toto-2.0-2.5B,0.69,0.548,0.833,0.121,0.071,0.18
+Chronos-2,Toto-2.0-313m,0.738,0.595,0.858,0.12,0.068,0.181
+Chronos-2,TabPFN-TS,0.738,0.595,0.857,0.069,0.019,0.124
+Chronos-2,TiRex,0.81,0.69,0.929,0.141,0.093,0.199
+Chronos-2,Toto-2.0-22m,0.738,0.595,0.857,0.146,0.096,0.204
+Chronos-2,TimesFM-2.5,0.833,0.714,0.929,0.152,0.098,0.213
+Chronos-2,FlowState,0.857,0.762,0.952,0.162,0.105,0.22
+Chronos-2,Moirai-2.0,0.833,0.714,0.929,0.163,0.111,0.217
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+Toto-2.0-4m,Chronos-2,0.095,0.024,0.19,-0.243,-0.331,-0.172
+Toto-2.0-4m,Toto-2.0-1B,0.119,0.047,0.214,-0.101,-0.144,-0.063
+Toto-2.0-4m,TabPFN-TS-3,0.238,0.119,0.357,-0.185,-0.293,-0.101
+Toto-2.0-4m,Toto-2.0-2.5B,0.214,0.095,0.333,-0.092,-0.133,-0.056
+Toto-2.0-4m,Toto-2.0-313m,0.071,0.0,0.167,-0.093,-0.13,-0.059
+Toto-2.0-4m,TabPFN-TS,0.19,0.071,0.31,-0.157,-0.269,-0.059
+Toto-2.0-4m,TiRex,0.19,0.071,0.31,-0.067,-0.102,-0.037
+Toto-2.0-4m,Toto-2.0-22m,0.167,0.071,0.286,-0.061,-0.092,-0.033
+Toto-2.0-4m,TimesFM-2.5,0.381,0.238,0.524,-0.054,-0.106,-0.012
+Toto-2.0-4m,FlowState,0.286,0.143,0.405,-0.041,-0.108,0.017
+Toto-2.0-4m,Moirai-2.0,0.405,0.262,0.548,-0.04,-0.082,-0.003
+Toto-2.0-4m,Toto-1.0,0.381,0.238,0.524,-0.012,-0.038,0.018
+Toto-2.0-4m,Chronos-Bolt,0.405,0.262,0.548,-0.012,-0.063,0.032
+Toto-2.0-4m,Toto-2.0-4m,0.5,0.5,0.5,0.0,0.0,0.0
+Toto-2.0-4m,Sundial-Base,0.738,0.595,0.857,0.085,-0.002,0.163
+Toto-2.0-4m,Seasonal Naive,0.976,0.929,1.0,0.382,0.303,0.452
+Sundial-Base,Chronos-2,0.048,0.0,0.119,-0.359,-0.463,-0.261
+Sundial-Base,Toto-2.0-1B,0.095,0.024,0.19,-0.204,-0.315,-0.098
+Sundial-Base,TabPFN-TS-3,0.143,0.048,0.262,-0.296,-0.407,-0.202
+Sundial-Base,Toto-2.0-2.5B,0.119,0.024,0.238,-0.193,-0.3,-0.083
+Sundial-Base,Toto-2.0-313m,0.095,0.024,0.19,-0.195,-0.309,-0.087
+Sundial-Base,TabPFN-TS,0.143,0.048,0.262,-0.265,-0.397,-0.135
+Sundial-Base,TiRex,0.155,0.06,0.274,-0.166,-0.259,-0.074
+Sundial-Base,Toto-2.0-22m,0.19,0.071,0.31,-0.16,-0.271,-0.06
+Sundial-Base,TimesFM-2.5,0.179,0.071,0.298,-0.152,-0.24,-0.071
+Sundial-Base,FlowState,0.202,0.095,0.321,-0.139,-0.211,-0.059
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+Sundial-Base,Toto-1.0,0.321,0.19,0.464,-0.106,-0.21,-0.01
+Sundial-Base,Chronos-Bolt,0.202,0.095,0.321,-0.107,-0.186,-0.025
+Sundial-Base,Toto-2.0-4m,0.262,0.143,0.405,-0.093,-0.194,0.002
+Sundial-Base,Sundial-Base,0.5,0.5,0.5,0.0,0.0,0.0
+Sundial-Base,Seasonal Naive,0.929,0.833,1.0,0.324,0.255,0.393
+Seasonal Naive,Chronos-2,0.024,0.0,0.071,-1.01,-1.263,-0.779
+Seasonal Naive,Toto-2.0-1B,0.024,0.0,0.071,-0.781,-1.023,-0.572
+Seasonal Naive,TabPFN-TS-3,0.024,0.0,0.071,-0.917,-1.16,-0.715
+Seasonal Naive,Toto-2.0-2.5B,0.024,0.0,0.071,-0.766,-1.007,-0.55
+Seasonal Naive,Toto-2.0-313m,0.024,0.0,0.071,-0.768,-1.007,-0.558
+Seasonal Naive,TabPFN-TS,0.036,0.0,0.095,-0.872,-1.115,-0.648
+Seasonal Naive,TiRex,0.024,0.0,0.071,-0.726,-0.949,-0.537
+Seasonal Naive,Toto-2.0-22m,0.024,0.0,0.071,-0.717,-0.94,-0.522
+Seasonal Naive,TimesFM-2.5,0.0,0.0,0.0,-0.705,-0.911,-0.529
+Seasonal Naive,FlowState,0.024,0.0,0.071,-0.685,-0.863,-0.53
+Seasonal Naive,Moirai-2.0,0.048,0.0,0.119,-0.683,-0.882,-0.507
+Seasonal Naive,Toto-1.0,0.024,0.0,0.071,-0.636,-0.842,-0.458
+Seasonal Naive,Chronos-Bolt,0.024,0.0,0.095,-0.638,-0.823,-0.473
+Seasonal Naive,Toto-2.0-4m,0.024,0.0,0.071,-0.618,-0.825,-0.434
+Seasonal Naive,Sundial-Base,0.071,0.0,0.167,-0.48,-0.647,-0.343
+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0

tables/task_type_multivariate/leaderboard_MASE.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Toto-2.0-2.5B,84.61538461538463,42.37962809390597,0.0,5.4132902212121214,0.0,0.0
+Toto-2.0-313m,83.40659340659342,42.20523827207805,0.0,1.0077612054761904,0.0,0.0
+Toto-2.0-1B,82.63736263736264,42.006798813920796,0.0,2.558476265800866,0.0,0.0
+Toto-2.0-22m,78.35164835164835,41.19031821593736,0.0,0.23064212619047622,0.0,0.0
+Chronos-2,72.52747252747253,40.47703024635902,0.0,1.1849748603,0.0,0.0
+Toto-1.0,72.52747252747253,39.81314672865939,0.0,44.222308597403845,0.05714285714285714,0.0
+TiRex,72.19780219780218,38.70507938155933,0.0,0.32911286958333336,0.0,0.0
+Toto-2.0-4m,71.53846153846153,39.82701860526772,0.0,0.19324943976190476,0.0,0.0
+TimesFM-2.5,66.8131868131868,38.48001468455288,0.0,5.895658940000001,0.05714285714285714,0.0
+FlowState,59.56043956043957,35.39038084875803,0.0,4.2874189791,0.05714285714285714,0.0
+Moirai-2.0,58.73626373626373,36.61629177551803,0.0,0.431608325,0.3142857142857143,0.0
+Chronos-Bolt,56.31868131868131,35.002811549465626,0.0,0.41097235624999995,0.0,0.0
+TabPFN-TS-3,50.0,34.03615459868672,0.0,296.51637025115633,0.0,0.0
+Sundial-Base,48.68131868131867,32.62962647463809,0.0,8.009474041714286,0.0,0.0
+TabPFN-TS,47.03296703296703,34.56355030672918,0.0,272.2124274120408,0.0,0.0
+CatBoost,41.208791208791204,30.421636182713975,85.04530864050001,0.5953758560714286,0.0,0.0
+Stat. Ensemble,40.43956043956044,25.799072425986303,0.0,191.30953815208332,0.0,2.857142857142857
+LightGBM,39.23076923076923,27.664714643052324,5.0175009462,0.4638569017857143,0.0,0.0
+PatchTST,35.16483516483516,26.58823462824348,1166.9339861665383,0.8156210857142857,0.0,0.0
+TFT,32.08791208791209,24.074542520238907,1175.3819149861429,1.1615856007142857,0.0,0.0
+AutoTheta,29.230769230769226,20.18219419387095,0.0,3.600769502857143,0.0,0.0
+AutoETS,28.846153846153843,14.94665084779918,0.0,3.970462877558334,0.0,2.857142857142857
+DeepAR,26.26373626373626,20.17693379420851,1929.7692648929808,1.66941923475,0.0,0.0
+AutoARIMA,25.274725274725274,18.076754194913157,0.0,18.755229074642855,0.0,2.857142857142857
+Naive,19.17582417582417,8.938030239814665,0.0,0.9265094010869566,0.0,0.0
+Drift,17.58241758241758,10.236281397576896,0.0,0.9685240114285714,0.0,0.0
+Seasonal Naive,10.549450549450547,0.0,0.0,0.9125925713043479,0.0,0.0

tables/task_type_multivariate/leaderboard_SQL.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Toto-2.0-2.5B,87.69230769230771,56.24594683677972,0.0,5.4132902212121214,0.0,0.0
+Toto-2.0-313m,85.16483516483517,56.153039055320534,0.0,1.0077612054761904,0.0,0.0
+Toto-2.0-1B,84.72527472527473,56.008529924072505,0.0,2.558476265800866,0.0,0.0
+Toto-2.0-22m,79.78021978021978,55.1331402332338,0.0,0.23064212619047622,0.0,0.0
+Chronos-2,78.24175824175825,54.956049957217616,0.0,1.1849748603,0.0,0.0
+Toto-1.0,75.7142857142857,54.15563623568822,0.0,44.222308597403845,0.05714285714285714,0.0
+TiRex,74.50549450549448,53.071981977564405,0.0,0.32911286958333336,0.0,0.0
+Toto-2.0-4m,73.73626373626372,53.962013710251625,0.0,0.19324943976190476,0.0,0.0
+TimesFM-2.5,69.89010989010987,52.79391261932832,0.0,5.895658940000001,0.05714285714285714,0.0
+FlowState,61.3186813186813,50.37345891984082,0.0,4.2874189791,0.05714285714285714,0.0
+Moirai-2.0,61.26373626373625,50.95532629740666,0.0,0.431608325,0.3142857142857143,0.0
+Chronos-Bolt,56.97802197802198,49.44557468666984,0.0,0.41097235624999995,0.0,0.0
+TabPFN-TS-3,56.263736263736256,49.813403234908485,0.0,296.51637025115633,0.0,0.0
+TabPFN-TS,50.439560439560424,48.15956039754633,0.0,272.2124274120408,0.0,0.0
+Sundial-Base,42.30769230769231,45.65760722577821,0.0,8.009474041714286,0.0,0.0
+PatchTST,39.67032967032967,43.12812641312074,1166.9339861665383,0.8156210857142857,0.0,0.0
+TFT,36.7032967032967,40.55122516723462,1175.3819149861429,1.1615856007142857,0.0,0.0
+Stat. Ensemble,35.16483516483516,28.823634833572388,0.0,191.30953815208332,0.0,2.857142857142857
+DeepAR,32.08791208791209,37.56325937155223,1929.7692648929808,1.66941923475,0.0,0.0
+AutoETS,28.846153846153843,-13.587078390469642,0.0,3.970462877558334,0.0,2.857142857142857
+LightGBM,28.13186813186813,33.00191912776389,5.0175009462,0.4638569017857143,0.0,0.0
+AutoARIMA,27.8021978021978,29.200998362644015,0.0,18.755229074642855,0.0,2.857142857142857
+CatBoost,27.8021978021978,35.55542329051369,85.04530864050001,0.5953758560714286,0.0,0.0
+AutoTheta,20.439560439560438,14.938651834571226,0.0,3.600769502857143,0.0,0.0
+Seasonal Naive,12.197802197802197,0.0,0.0,0.9125925713043479,0.0,0.0
+Naive,11.703296703296703,-24.141881005489306,0.0,0.9265094010869566,0.0,0.0
+Drift,11.428571428571429,-21.43004900644645,0.0,0.9685240114285714,0.0,0.0

tables/task_type_multivariate/leaderboard_WAPE.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Toto-2.0-1B,85.16483516483517,45.64380153509545,0.0,2.558476265800866,0.0,0.0
+Toto-2.0-2.5B,84.94505494505495,46.07175559172698,0.0,5.4132902212121214,0.0,0.0
+Toto-2.0-313m,84.50549450549451,45.49656398580171,0.0,1.0077612054761904,0.0,0.0
+Toto-2.0-22m,79.34065934065934,43.976482848629104,0.0,0.23064212619047622,0.0,0.0
+Toto-1.0,73.5164835164835,42.766138549210844,0.0,44.222308597403845,0.05714285714285714,0.0
+Chronos-2,70.54945054945054,44.34184922951903,0.0,1.1849748603,0.0,0.0
+Toto-2.0-4m,69.56043956043956,42.28603186556402,0.0,0.19324943976190476,0.0,0.0
+TiRex,68.68131868131867,41.644068882649776,0.0,0.32911286958333336,0.0,0.0
+TimesFM-2.5,66.8131868131868,42.06152219112852,0.0,5.895658940000001,0.05714285714285714,0.0
+Moirai-2.0,61.04395604395604,40.61852164348273,0.0,0.431608325,0.3142857142857143,0.0
+FlowState,56.92307692307691,39.58186553887033,0.0,4.2874189791,0.05714285714285714,0.0
+Chronos-Bolt,55.87912087912088,37.95787313736294,0.0,0.41097235624999995,0.0,0.0
+TabPFN-TS-3,52.96703296703296,40.353645428709726,0.0,296.51637025115633,0.0,0.0
+TabPFN-TS,50.0,38.547278765276026,0.0,272.2124274120408,0.0,0.0
+Sundial-Base,42.19780219780219,34.35604853400894,0.0,8.009474041714286,0.0,0.0
+PatchTST,40.43956043956044,32.22451376950516,1166.9339861665383,0.8156210857142857,0.0,0.0
+Stat. Ensemble,39.34065934065934,26.656189157155087,0.0,191.30953815208332,0.0,2.857142857142857
+CatBoost,36.153846153846146,30.3363690234262,85.04530864050001,0.5953758560714286,0.0,0.0
+LightGBM,34.94505494505494,24.144419239287817,5.0175009462,0.4638569017857143,0.0,0.0
+TFT,33.51648351648351,25.518118709758486,1175.3819149861429,1.1615856007142857,0.0,0.0
+DeepAR,30.43956043956043,24.540387510587635,1929.7692648929808,1.66941923475,0.0,0.0
+AutoETS,29.61538461538461,17.598567846659442,0.0,3.970462877558334,0.0,2.857142857142857
+AutoTheta,27.47252747252747,21.013255167194846,0.0,3.600769502857143,0.0,0.0
+Naive,22.58241758241758,13.99112565126096,0.0,0.9265094010869566,0.0,0.0
+AutoARIMA,22.527472527472526,16.45553689708581,0.0,18.755229074642855,0.0,2.857142857142857
+Drift,19.010989010989007,10.971858113653743,0.0,0.9685240114285714,0.0,0.0
+Seasonal Naive,11.868131868131865,0.0,0.0,0.9125925713043479,0.0,0.0

tables/task_type_multivariate/leaderboard_WQL.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Toto-2.0-2.5B,86.92307692307692,61.12488612662447,0.0,5.4132902212121214,0.0,0.0
+Toto-2.0-1B,86.48351648351648,60.99353902913318,0.0,2.558476265800866,0.0,0.0
+Toto-2.0-313m,86.26373626373626,60.918796028667344,0.0,1.0077612054761904,0.0,0.0
+Toto-2.0-22m,81.53846153846153,59.957413683613666,0.0,0.23064212619047622,0.0,0.0
+Toto-1.0,76.5934065934066,58.85524417940593,0.0,44.222308597403845,0.05714285714285714,0.0
+Chronos-2,74.83516483516482,59.9945361042916,0.0,1.1849748603,0.0,0.0
+Toto-2.0-4m,72.96703296703296,58.32177026876002,0.0,0.19324943976190476,0.0,0.0
+TiRex,71.53846153846153,57.57875059562707,0.0,0.32911286958333336,0.0,0.0
+TimesFM-2.5,70.76923076923075,58.140880584922364,0.0,5.895658940000001,0.05714285714285714,0.0
+Moirai-2.0,64.67032967032966,56.60363357702494,0.0,0.431608325,0.3142857142857143,0.0
+FlowState,63.4065934065934,56.46151176362224,0.0,4.2874189791,0.05714285714285714,0.0
+TabPFN-TS-3,60.54945054945055,57.33556321837573,0.0,296.51637025115633,0.0,0.0
+Chronos-Bolt,57.1978021978022,54.39269754289919,0.0,0.41097235624999995,0.0,0.0
+TabPFN-TS,50.32967032967033,53.38177631854182,0.0,272.2124274120408,0.0,0.0
+PatchTST,44.06593406593406,50.110970512146395,1166.9339861665383,0.8156210857142857,0.0,0.0
+Sundial-Base,41.64835164835165,50.12690699864979,0.0,8.009474041714286,0.0,0.0
+TFT,35.27472527472527,43.04581202805166,1175.3819149861429,1.1615856007142857,0.0,0.0
+DeepAR,34.83516483516483,43.43420693962238,1929.7692648929808,1.66941923475,0.0,0.0
+Stat. Ensemble,31.0989010989011,26.514107240222685,0.0,191.30953815208332,0.0,2.857142857142857
+CatBoost,28.241758241758237,38.8350615663292,85.04530864050001,0.5953758560714286,0.0,0.0
+LightGBM,26.483516483516485,33.398505642559904,5.0175009462,0.4638569017857143,0.0,0.0
+AutoARIMA,25.4945054945055,30.90771158984613,0.0,18.755229074642855,0.0,2.857142857142857
+AutoETS,24.89010989010989,-16.00702788254289,0.0,3.970462877558334,0.0,2.857142857142857
+AutoTheta,17.91208791208791,10.999807424594232,0.0,3.600769502857143,0.0,0.0
+Naive,13.02197802197802,-25.39025550566012,0.0,0.9265094010869566,0.0,0.0
+Seasonal Naive,12.747252747252746,0.0,0.0,0.9125925713043479,0.0,0.0
+Drift,10.219780219780219,-26.642604521337976,0.0,0.9685240114285714,0.0,0.0

tables/task_type_multivariate/pairwise_MASE.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
+Toto-2.0-2.5B,Toto-2.0-2.5B,0.5,0.5,0.5,0.0,0.0,0.0
+Toto-2.0-2.5B,Toto-2.0-313m,0.629,0.486,0.771,0.003,-0.013,0.02
+Toto-2.0-2.5B,Toto-2.0-1B,0.6,0.429,0.743,0.006,-0.003,0.017
+Toto-2.0-2.5B,Toto-2.0-22m,0.771,0.629,0.914,0.02,0.002,0.041
+Toto-2.0-2.5B,Chronos-2,0.743,0.6,0.886,0.032,-0.005,0.069
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+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0

tables/task_type_multivariate/pairwise_SQL.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
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tables/task_type_multivariate/pairwise_WAPE.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
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+Seasonal Naive,FlowState,0.057,0.0,0.143,-0.655,-0.926,-0.439
+Seasonal Naive,Chronos-Bolt,0.057,0.0,0.143,-0.612,-0.834,-0.418
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+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0

tables/task_type_multivariate/pairwise_WQL.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
+Toto-2.0-2.5B,Toto-2.0-2.5B,0.5,0.5,0.5,0.0,0.0,0.0
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+Toto-2.0-2.5B,Toto-2.0-313m,0.686,0.543,0.829,0.005,-0.018,0.03
+Toto-2.0-2.5B,Toto-2.0-22m,0.8,0.657,0.914,0.029,-0.003,0.063
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+Toto-2.0-2.5B,Chronos-2,0.8,0.657,0.943,0.028,-0.013,0.065
+Toto-2.0-2.5B,Toto-2.0-4m,0.771,0.629,0.886,0.067,0.026,0.118
+Toto-2.0-2.5B,TiRex,0.771,0.629,0.914,0.084,0.021,0.149
+Toto-2.0-2.5B,TimesFM-2.5,0.771,0.629,0.886,0.071,0.009,0.123
+Toto-2.0-2.5B,FlowState,0.829,0.686,0.943,0.107,0.024,0.179
+Toto-2.0-2.5B,Moirai-2.0,0.771,0.629,0.886,0.104,0.026,0.17
+Toto-2.0-2.5B,TabPFN-TS-3,0.829,0.686,0.943,0.089,0.022,0.148
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+TabPFN-TS,Toto-2.0-1B,0.086,0.0,0.2,-0.195,-0.283,-0.11
+TabPFN-TS,Toto-2.0-313m,0.114,0.029,0.229,-0.193,-0.281,-0.109
+TabPFN-TS,Toto-2.0-22m,0.114,0.029,0.229,-0.164,-0.241,-0.091
+TabPFN-TS,Toto-1.0,0.143,0.057,0.286,-0.133,-0.203,-0.069
+TabPFN-TS,Chronos-2,0.057,0.0,0.143,-0.165,-0.242,-0.103
+TabPFN-TS,Toto-2.0-4m,0.171,0.057,0.314,-0.119,-0.183,-0.055
+TabPFN-TS,TiRex,0.143,0.029,0.286,-0.099,-0.158,-0.044
+TabPFN-TS,TimesFM-2.5,0.171,0.057,0.286,-0.114,-0.174,-0.063
+TabPFN-TS,FlowState,0.343,0.2,0.514,-0.071,-0.169,0.016
+TabPFN-TS,Moirai-2.0,0.286,0.143,0.429,-0.074,-0.131,-0.026
+TabPFN-TS,TabPFN-TS-3,0.286,0.143,0.429,-0.093,-0.185,-0.026
+TabPFN-TS,Chronos-Bolt,0.343,0.2,0.514,-0.022,-0.083,0.039
+TabPFN-TS,TabPFN-TS,0.5,0.5,0.5,0.0,0.0,0.0
+TabPFN-TS,PatchTST,0.486,0.314,0.629,0.066,-0.056,0.165
+TabPFN-TS,Seasonal Naive,0.971,0.914,1.0,0.534,0.441,0.617
+PatchTST,Toto-2.0-2.5B,0.057,0.0,0.143,-0.283,-0.407,-0.156
+PatchTST,Toto-2.0-1B,0.057,0.0,0.143,-0.279,-0.403,-0.148
+PatchTST,Toto-2.0-313m,0.057,0.0,0.143,-0.277,-0.406,-0.136
+PatchTST,Toto-2.0-22m,0.057,0.0,0.143,-0.246,-0.377,-0.11
+PatchTST,Toto-1.0,0.114,0.029,0.229,-0.213,-0.36,-0.063
+PatchTST,Chronos-2,0.143,0.056,0.257,-0.247,-0.361,-0.141
+PatchTST,Toto-2.0-4m,0.057,0.0,0.143,-0.197,-0.335,-0.058
+PatchTST,TiRex,0.171,0.057,0.314,-0.176,-0.313,-0.032
+PatchTST,TimesFM-2.5,0.086,0.0,0.2,-0.192,-0.302,-0.081
+PatchTST,FlowState,0.229,0.086,0.371,-0.146,-0.238,-0.054
+PatchTST,Moirai-2.0,0.257,0.142,0.4,-0.15,-0.286,-0.011
+PatchTST,TabPFN-TS-3,0.229,0.086,0.371,-0.169,-0.258,-0.089
+PatchTST,Chronos-Bolt,0.371,0.229,0.543,-0.094,-0.221,0.041
+PatchTST,TabPFN-TS,0.514,0.371,0.686,-0.07,-0.198,0.053
+PatchTST,PatchTST,0.5,0.5,0.5,0.0,0.0,0.0
+PatchTST,Seasonal Naive,0.914,0.8,1.0,0.501,0.396,0.605
+Seasonal Naive,Toto-2.0-2.5B,0.029,0.0,0.086,-1.572,-2.24,-1.096
+Seasonal Naive,Toto-2.0-1B,0.029,0.0,0.086,-1.564,-2.207,-1.09
+Seasonal Naive,Toto-2.0-313m,0.029,0.0,0.086,-1.559,-2.195,-1.085
+Seasonal Naive,Toto-2.0-22m,0.029,0.0,0.086,-1.497,-2.106,-1.046
+Seasonal Naive,Toto-1.0,0.029,0.0,0.086,-1.43,-1.968,-1.008
+Seasonal Naive,Chronos-2,0.029,0.0,0.086,-1.5,-2.081,-1.063
+Seasonal Naive,Toto-2.0-4m,0.029,0.0,0.086,-1.399,-1.95,-0.976
+Seasonal Naive,TiRex,0.029,0.0,0.086,-1.357,-1.845,-0.976
+Seasonal Naive,TimesFM-2.5,0.0,0.0,0.0,-1.389,-1.909,-0.998
+Seasonal Naive,FlowState,0.0,0.0,0.0,-1.297,-1.82,-0.94
+Seasonal Naive,Moirai-2.0,0.0,0.0,0.0,-1.304,-1.774,-0.943
+Seasonal Naive,TabPFN-TS-3,0.029,0.0,0.086,-1.344,-1.892,-0.953
+Seasonal Naive,Chronos-Bolt,0.0,0.0,0.0,-1.193,-1.621,-0.864
+Seasonal Naive,TabPFN-TS,0.029,0.0,0.086,-1.145,-1.61,-0.79
+Seasonal Naive,PatchTST,0.086,0.0,0.2,-1.004,-1.532,-0.656
+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0

tables/task_type_univariate/leaderboard_MASE.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Chronos-2,82.9326923076923,27.99390713883231,0.0,0.21276834204301076,0.0,0.0
+Toto-2.0-1B,77.28365384615384,26.7317219556384,0.0,2.426733271357678,0.0,0.0
+Toto-2.0-2.5B,76.5625,26.534681339191103,0.0,5.326006857917275,0.0,0.0
+Toto-2.0-313m,73.5576923076923,26.313790788283832,0.0,1.0634686123833972,0.0,0.0
+TiRex,73.4375,25.71132197130257,0.0,0.19425185975,0.0,0.0
+TimesFM-2.5,71.63461538461539,26.27899613370557,0.0,0.559727848226858,0.0,0.0
+FlowState,67.42788461538461,22.090684936518613,0.0,1.039144312046837,0.0,0.0
+TabPFN-TS-3,66.46634615384616,22.563323248242327,0.0,215.38034239575552,0.0,0.0
+Toto-2.0-22m,64.54326923076923,24.3703980848735,0.0,0.23846756001861044,0.0,0.0
+TabPFN-TS,57.8125,22.971187048045326,0.0,64.98920974493144,0.0,0.0
+Toto-1.0,53.96634615384615,22.107452063429612,0.0,10.730363198083333,0.0,0.0
+Chronos-Bolt,52.223557692307686,20.7663634347118,0.0,0.20924117567741934,0.0,0.0
+Toto-2.0-4m,51.32211538461539,21.607166213549956,0.0,0.19166024198924733,0.0,0.0
+Moirai-2.0,48.737980769230774,20.291476627842265,0.0,0.25535015816666673,0.34375,0.0
+Stat. Ensemble,45.49278846153847,13.4680243890007,0.0,106.14506022419354,0.0,6.25
+CatBoost,45.19230769230769,16.466986315536523,9.475867548113083,0.08841646971432476,0.0,0.0
+LightGBM,44.11057692307692,15.511460150461742,0.6467891415693146,0.07631481828775127,0.0,0.0
+Sundial-Base,43.62980769230769,18.370018530095255,0.0,7.954820643464173,0.0,0.0
+TFT,40.44471153846153,16.528467051420602,281.18259558108974,0.24915869446443342,0.0,0.0
+AutoARIMA,40.20432692307692,11.681251245201373,0.0,13.951509990514431,0.0,6.25
+AutoETS,37.86057692307692,6.371835454547458,0.0,2.457903827995606,0.0,6.25
+DeepAR,37.199519230769226,16.846504531563646,467.93394356724366,0.5208180233333334,0.0,3.125
+PatchTST,30.16826923076923,13.144855820742507,288.3942907752257,0.3001826822611663,0.0,0.0
+AutoTheta,26.442307692307693,5.9153801345410155,0.0,1.7630840095781735,0.0,0.0
+Seasonal Naive,18.870192307692307,0.0,0.0,0.23815382831046544,0.0,0.0
+Drift,12.740384615384615,-41.376329526852395,0.0,0.217463340720339,0.0,0.0
+Naive,9.735576923076923,-39.61909492922238,0.0,0.20769629459577615,0.0,0.0

tables/task_type_univariate/leaderboard_SQL.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Chronos-2,86.17788461538461,37.0339598769268,0.0,0.21276834204301076,0.0,0.0
+Toto-2.0-1B,80.76923076923077,35.75175890481369,0.0,2.426733271357678,0.0,0.0
+Toto-2.0-2.5B,79.6875,35.627348248727685,0.0,5.326006857917275,0.0,0.0
+Toto-2.0-313m,77.88461538461539,35.286196090295455,0.0,1.0634686123833972,0.0,0.0
+TiRex,77.40384615384616,35.01369078500964,0.0,0.19425185975,0.0,0.0
+TimesFM-2.5,73.79807692307693,34.92408244319366,0.0,0.559727848226858,0.0,0.0
+Toto-2.0-22m,69.35096153846155,33.843246413499806,0.0,0.23846756001861044,0.0,0.0
+TabPFN-TS-3,68.14903846153845,32.682760506952434,0.0,215.38034239575552,0.0,0.0
+FlowState,65.86538461538461,30.464806712356275,0.0,1.039144312046837,0.0,0.0
+TabPFN-TS,62.379807692307686,32.38738295255295,0.0,64.98920974493144,0.0,0.0
+Toto-1.0,57.692307692307686,31.530105413500053,0.0,10.730363198083333,0.0,0.0
+Chronos-Bolt,56.31009615384615,30.12432270033647,0.0,0.20924117567741934,0.0,0.0
+Toto-2.0-4m,56.129807692307686,31.209124473024797,0.0,0.19166024198924733,0.0,0.0
+Moirai-2.0,51.98317307692307,28.97697911952871,0.0,0.25535015816666673,0.34375,0.0
+Stat. Ensemble,44.65144230769231,16.567011147038457,0.0,106.14506022419354,0.0,6.25
+TFT,43.50961538461539,23.706570356059153,281.18259558108974,0.24915869446443342,0.0,0.0
+AutoARIMA,42.00721153846153,18.030570877700292,0.0,13.951509990514431,0.0,6.25
+DeepAR,40.86538461538461,23.555355495413068,467.93394356724366,0.5208180233333334,0.0,3.125
+Sundial-Base,34.855769230769226,22.91486952517109,0.0,7.954820643464173,0.0,0.0
+AutoETS,34.73557692307692,-36.16184103810849,0.0,2.457903827995606,0.0,6.25
+PatchTST,34.43509615384615,20.15355435692837,288.3942907752257,0.3001826822611663,0.0,0.0
+CatBoost,25.120192307692307,9.552459340446495,9.475867548113083,0.08841646971432476,0.0,0.0
+LightGBM,23.557692307692307,8.517838561728631,0.6467891415693146,0.07631481828775127,0.0,0.0
+AutoTheta,23.076923076923077,-4.510352730031664,0.0,1.7630840095781735,0.0,0.0
+Seasonal Naive,18.93028846153846,0.0,0.0,0.23815382831046544,0.0,0.0
+Drift,11.298076923076923,-74.23187160698073,0.0,0.217463340720339,0.0,0.0
+Naive,9.375,-74.54960384295045,0.0,0.20769629459577615,0.0,0.0

tables/task_type_univariate/leaderboard_WAPE.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Chronos-2,80.40865384615384,31.574899293883963,0.0,0.21276834204301076,0.0,0.0
+Toto-2.0-2.5B,80.40865384615384,30.224981323893342,0.0,5.326006857917275,0.0,0.0
+Toto-2.0-1B,76.80288461538461,29.905280904300813,0.0,2.426733271357678,0.0,0.0
+Toto-2.0-313m,75.36057692307693,29.714765414268427,0.0,1.0634686123833972,0.0,0.0
+TimesFM-2.5,73.79807692307693,29.650904955748313,0.0,0.559727848226858,0.0,0.0
+TiRex,71.51442307692307,29.22524679854486,0.0,0.19425185975,0.0,0.0
+TabPFN-TS-3,68.50961538461539,27.214867518163455,0.0,215.38034239575552,0.0,0.0
+FlowState,67.54807692307693,30.09959363932445,0.0,1.039144312046837,0.0,0.0
+Toto-2.0-22m,65.7451923076923,28.604848057546317,0.0,0.23846756001861044,0.0,0.0
+TabPFN-TS,60.69711538461539,28.793683286196813,0.0,64.98920974493144,0.0,0.0
+Toto-1.0,55.88942307692307,25.577740272044245,0.0,10.730363198083333,0.0,0.0
+Chronos-Bolt,54.26682692307693,25.40621225271993,0.0,0.20924117567741934,0.0,0.0
+Toto-2.0-4m,51.32211538461539,24.679707504856008,0.0,0.19166024198924733,0.0,0.0
+Moirai-2.0,49.93990384615385,23.058536180274736,0.0,0.25535015816666673,0.34375,0.0
+Stat. Ensemble,43.68990384615385,17.727727626633715,0.0,106.14506022419354,0.0,6.25
+Sundial-Base,42.90865384615385,20.448180173908913,0.0,7.954820643464173,0.0,0.0
+CatBoost,41.22596153846153,18.76505901842784,9.475867548113083,0.08841646971432476,0.0,0.0
+LightGBM,41.105769230769226,19.037255796555574,0.6467891415693146,0.07631481828775127,0.0,0.0
+TFT,40.08413461538461,18.373603116607807,281.18259558108974,0.24915869446443342,0.0,0.0
+AutoARIMA,39.60336538461539,15.505959555026772,0.0,13.951509990514431,0.0,6.25
+AutoETS,36.29807692307692,2.3580411343619434,0.0,2.457903827995606,0.0,6.25
+DeepAR,34.074519230769226,17.802230426242115,467.93394356724366,0.5208180233333334,0.0,3.125
+PatchTST,30.16826923076923,14.865163123427871,288.3942907752257,0.3001826822611663,0.0,0.0
+AutoTheta,25.360576923076923,10.33674396649873,0.0,1.7630840095781735,0.0,0.0
+Seasonal Naive,18.990384615384613,0.0,0.0,0.23815382831046544,0.0,0.0
+Drift,13.341346153846153,-19.83598592543119,0.0,0.217463340720339,0.0,0.0
+Naive,10.9375,-21.496080116325867,0.0,0.20769629459577615,0.0,0.0

tables/task_type_univariate/leaderboard_WQL.csv

@@ -0,0 +1,28 @@
+model_name,win_rate,skill_score,median_training_time_s_per100,median_inference_time_s_per100,training_corpus_overlap,num_failures
+Chronos-2,83.89423076923077,40.84628843868441,0.0,0.21276834204301076,0.0,0.0
+Toto-2.0-2.5B,81.61057692307693,39.45397727376795,0.0,5.326006857917275,0.0,0.0
+Toto-2.0-1B,80.52884615384616,39.19637123849717,0.0,2.426733271357678,0.0,0.0
+Toto-2.0-313m,77.04326923076923,38.92296866055266,0.0,1.0634686123833972,0.0,0.0
+TiRex,74.8798076923077,38.74983094426454,0.0,0.19425185975,0.0,0.0
+TimesFM-2.5,74.39903846153845,38.69064615813591,0.0,0.559727848226858,0.0,0.0
+TabPFN-TS-3,71.39423076923077,37.13611033754862,0.0,215.38034239575552,0.0,0.0
+Toto-2.0-22m,69.83173076923077,38.14902775423167,0.0,0.23846756001861044,0.0,0.0
+FlowState,66.58653846153845,38.4407958273131,0.0,1.039144312046837,0.0,0.0
+TabPFN-TS,63.70192307692307,37.558463928192396,0.0,64.98920974493144,0.0,0.0
+Toto-1.0,57.09134615384615,35.31379800866229,0.0,10.730363198083333,0.0,0.0
+Chronos-Bolt,56.550480769230774,34.89047194343375,0.0,0.20924117567741934,0.0,0.0
+Toto-2.0-4m,55.168269230769226,34.8855731220096,0.0,0.19166024198924733,0.0,0.0
+Moirai-2.0,52.34375,32.600897327995895,0.0,0.25535015816666673,0.34375,0.0
+TFT,44.35096153846153,26.128622094569508,281.18259558108974,0.24915869446443342,0.0,0.0
+Stat. Ensemble,43.68990384615385,19.950951239142245,0.0,106.14506022419354,0.0,6.25
+AutoARIMA,41.64663461538461,21.949127392355493,0.0,13.951509990514431,0.0,6.25
+DeepAR,36.89903846153847,24.48504899458338,467.93394356724366,0.5208180233333334,0.0,3.125
+AutoETS,34.25480769230769,-38.32028900670734,0.0,2.457903827995606,0.0,6.25
+Sundial-Base,34.01442307692308,25.64948000353725,0.0,7.954820643464173,0.0,0.0
+PatchTST,33.35336538461539,22.348910021170553,288.3942907752257,0.3001826822611663,0.0,0.0
+CatBoost,25.841346153846157,12.786321977838044,9.475867548113083,0.08841646971432476,0.0,0.0
+LightGBM,25.600961538461537,13.078551918444692,0.6467891415693146,0.07631481828775127,0.0,0.0
+AutoTheta,24.759615384615387,3.0725928218514276,0.0,1.7630840095781735,0.0,0.0
+Seasonal Naive,19.411057692307693,0.0,0.0,0.23815382831046544,0.0,0.0
+Drift,11.778846153846153,-53.83576239004797,0.0,0.217463340720339,0.0,0.0
+Naive,9.375,-57.89006471235225,0.0,0.20769629459577615,0.0,0.0

tables/task_type_univariate/pairwise_MASE.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
+Chronos-2,Chronos-2,0.5,0.5,0.5,0.0,0.0,0.0
+Chronos-2,Toto-2.0-1B,0.531,0.375,0.719,0.017,-0.014,0.049
+Chronos-2,Toto-2.0-2.5B,0.594,0.438,0.75,0.02,-0.008,0.05
+Chronos-2,Toto-2.0-313m,0.625,0.469,0.781,0.023,-0.005,0.053
+Chronos-2,TiRex,0.719,0.562,0.875,0.031,0.01,0.054
+Chronos-2,TimesFM-2.5,0.562,0.375,0.719,0.023,0.001,0.046
+Chronos-2,FlowState,0.656,0.469,0.812,0.076,0.004,0.172
+Chronos-2,TabPFN-TS-3,0.656,0.469,0.812,0.07,0.026,0.133
+Chronos-2,Toto-2.0-22m,0.812,0.688,0.938,0.048,0.019,0.081
+Chronos-2,TabPFN-TS,0.812,0.656,0.938,0.065,0.025,0.127
+Chronos-2,Toto-1.0,0.844,0.719,0.969,0.076,0.041,0.114
+Chronos-2,Chronos-Bolt,0.938,0.844,1.0,0.091,0.051,0.136
+Chronos-2,Toto-2.0-4m,0.906,0.812,1.0,0.081,0.049,0.119
+Chronos-2,Moirai-2.0,0.938,0.844,1.0,0.097,0.057,0.141
+Chronos-2,Stat. Ensemble,0.844,0.719,0.969,0.168,0.097,0.242
+Chronos-2,Seasonal Naive,1.0,1.0,1.0,0.28,0.239,0.322
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+Toto-2.0-1B,Stat. Ensemble,0.781,0.656,0.938,0.153,0.079,0.233
+Toto-2.0-1B,Seasonal Naive,0.938,0.844,1.0,0.267,0.223,0.311
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+Toto-2.0-2.5B,Stat. Ensemble,0.75,0.594,0.906,0.151,0.078,0.229
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+Toto-2.0-313m,Stat. Ensemble,0.75,0.594,0.906,0.148,0.074,0.228
+Toto-2.0-313m,Seasonal Naive,0.969,0.906,1.0,0.263,0.22,0.307
+TiRex,Chronos-2,0.281,0.125,0.438,-0.032,-0.057,-0.01
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+TimesFM-2.5,Moirai-2.0,0.781,0.625,0.907,0.075,0.038,0.116
+TimesFM-2.5,Stat. Ensemble,0.781,0.655,0.938,0.148,0.071,0.222
+TimesFM-2.5,Seasonal Naive,0.969,0.906,1.0,0.263,0.219,0.308
+FlowState,Chronos-2,0.344,0.188,0.531,-0.082,-0.208,-0.004
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+FlowState,Toto-2.0-4m,0.656,0.5,0.812,0.006,-0.116,0.081
+FlowState,Moirai-2.0,0.719,0.562,0.875,0.023,-0.092,0.101
+FlowState,Stat. Ensemble,0.688,0.531,0.844,0.1,-0.028,0.193
+FlowState,Seasonal Naive,0.875,0.75,0.969,0.221,0.111,0.294
+TabPFN-TS-3,Chronos-2,0.344,0.188,0.531,-0.075,-0.153,-0.026
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+TabPFN-TS-3,Toto-2.0-2.5B,0.375,0.219,0.531,-0.054,-0.143,0.006
+TabPFN-TS-3,Toto-2.0-313m,0.438,0.281,0.595,-0.051,-0.143,0.009
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+TabPFN-TS-3,Stat. Ensemble,0.781,0.625,0.906,0.105,0.009,0.188
+TabPFN-TS-3,Seasonal Naive,0.938,0.844,1.0,0.226,0.148,0.281
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+Toto-2.0-22m,Toto-2.0-1B,0.188,0.062,0.344,-0.032,-0.055,-0.012
+Toto-2.0-22m,Toto-2.0-2.5B,0.219,0.093,0.375,-0.029,-0.048,-0.011
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+Toto-2.0-22m,TabPFN-TS,0.531,0.344,0.688,0.018,-0.039,0.085
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+Toto-2.0-22m,Toto-2.0-4m,0.812,0.656,0.938,0.035,0.02,0.051
+Toto-2.0-22m,Moirai-2.0,0.75,0.594,0.906,0.051,0.004,0.095
+Toto-2.0-22m,Stat. Ensemble,0.781,0.656,0.938,0.126,0.052,0.205
+Toto-2.0-22m,Seasonal Naive,0.969,0.906,1.0,0.244,0.198,0.288
+TabPFN-TS,Chronos-2,0.188,0.062,0.344,-0.07,-0.146,-0.025
+TabPFN-TS,Toto-2.0-1B,0.25,0.124,0.406,-0.051,-0.143,0.015
+TabPFN-TS,Toto-2.0-2.5B,0.219,0.094,0.375,-0.049,-0.133,0.012
+TabPFN-TS,Toto-2.0-313m,0.219,0.094,0.375,-0.045,-0.131,0.015
+TabPFN-TS,TiRex,0.312,0.156,0.469,-0.037,-0.109,0.009
+TabPFN-TS,TimesFM-2.5,0.312,0.156,0.469,-0.045,-0.13,0.008
+TabPFN-TS,FlowState,0.406,0.219,0.562,0.011,-0.032,0.065
+TabPFN-TS,TabPFN-TS-3,0.406,0.25,0.594,0.005,-0.02,0.03
+TabPFN-TS,Toto-2.0-22m,0.469,0.312,0.656,-0.019,-0.093,0.037
+TabPFN-TS,TabPFN-TS,0.5,0.5,0.5,0.0,0.0,0.0
+TabPFN-TS,Toto-1.0,0.5,0.344,0.688,0.011,-0.074,0.074
+TabPFN-TS,Chronos-Bolt,0.5,0.343,0.688,0.028,-0.025,0.081
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+TabPFN-TS,Moirai-2.0,0.562,0.375,0.72,0.034,-0.046,0.094
+TabPFN-TS,Stat. Ensemble,0.719,0.562,0.875,0.11,0.017,0.191
+TabPFN-TS,Seasonal Naive,0.938,0.844,1.0,0.23,0.155,0.283
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+Toto-1.0,Toto-2.0-2.5B,0.219,0.094,0.344,-0.06,-0.107,-0.023
+Toto-1.0,Toto-2.0-313m,0.281,0.125,0.438,-0.057,-0.101,-0.02
+Toto-1.0,TiRex,0.25,0.094,0.406,-0.049,-0.089,-0.014
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+Toto-1.0,FlowState,0.281,0.125,0.438,0.0,-0.09,0.11
+Toto-1.0,TabPFN-TS-3,0.375,0.218,0.531,-0.006,-0.07,0.072
+Toto-1.0,Toto-2.0-22m,0.25,0.094,0.406,-0.03,-0.07,0.004
+Toto-1.0,TabPFN-TS,0.5,0.312,0.656,-0.011,-0.08,0.069
+Toto-1.0,Toto-1.0,0.5,0.5,0.5,0.0,0.0,0.0
+Toto-1.0,Chronos-Bolt,0.469,0.281,0.656,0.017,-0.041,0.077
+Toto-1.0,Toto-2.0-4m,0.531,0.375,0.688,0.006,-0.028,0.037
+Toto-1.0,Moirai-2.0,0.531,0.344,0.719,0.023,-0.003,0.047
+Toto-1.0,Stat. Ensemble,0.594,0.438,0.75,0.1,0.02,0.179
+Toto-1.0,Seasonal Naive,0.938,0.844,1.0,0.221,0.174,0.269
+Chronos-Bolt,Chronos-2,0.062,0.0,0.156,-0.1,-0.158,-0.054
+Chronos-Bolt,Toto-2.0-1B,0.219,0.094,0.375,-0.081,-0.159,-0.018
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+Chronos-Bolt,TimesFM-2.5,0.281,0.125,0.438,-0.075,-0.136,-0.023
+Chronos-Bolt,FlowState,0.281,0.125,0.438,-0.017,-0.086,0.065
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+Chronos-Bolt,Toto-2.0-22m,0.312,0.156,0.469,-0.048,-0.116,0.01
+Chronos-Bolt,TabPFN-TS,0.5,0.312,0.657,-0.029,-0.088,0.024
+Chronos-Bolt,Toto-1.0,0.531,0.344,0.719,-0.017,-0.083,0.04
+Chronos-Bolt,Chronos-Bolt,0.5,0.5,0.5,0.0,0.0,0.0
+Chronos-Bolt,Toto-2.0-4m,0.562,0.375,0.75,-0.011,-0.072,0.043
+Chronos-Bolt,Moirai-2.0,0.547,0.406,0.688,0.006,-0.051,0.059
+Chronos-Bolt,Stat. Ensemble,0.594,0.438,0.75,0.084,0.008,0.163
+Chronos-Bolt,Seasonal Naive,0.844,0.719,0.938,0.208,0.137,0.269
+Toto-2.0-4m,Chronos-2,0.094,0.0,0.188,-0.089,-0.135,-0.051
+Toto-2.0-4m,Toto-2.0-1B,0.094,0.0,0.188,-0.07,-0.103,-0.039
+Toto-2.0-4m,Toto-2.0-2.5B,0.156,0.062,0.281,-0.067,-0.097,-0.038
+Toto-2.0-4m,Toto-2.0-313m,0.188,0.062,0.344,-0.064,-0.092,-0.038
+Toto-2.0-4m,TiRex,0.219,0.094,0.375,-0.055,-0.091,-0.024
+Toto-2.0-4m,TimesFM-2.5,0.281,0.125,0.438,-0.063,-0.111,-0.023
+Toto-2.0-4m,FlowState,0.344,0.188,0.5,-0.006,-0.088,0.104
+Toto-2.0-4m,TabPFN-TS-3,0.344,0.156,0.5,-0.012,-0.072,0.06
+Toto-2.0-4m,Toto-2.0-22m,0.188,0.062,0.344,-0.037,-0.054,-0.021
+Toto-2.0-4m,TabPFN-TS,0.375,0.219,0.562,-0.018,-0.076,0.052
+Toto-2.0-4m,Toto-1.0,0.469,0.312,0.625,-0.006,-0.038,0.027
+Toto-2.0-4m,Chronos-Bolt,0.438,0.25,0.625,0.011,-0.045,0.067
+Toto-2.0-4m,Toto-2.0-4m,0.5,0.5,0.5,0.0,0.0,0.0
+Toto-2.0-4m,Moirai-2.0,0.562,0.406,0.75,0.017,-0.028,0.059
+Toto-2.0-4m,Stat. Ensemble,0.562,0.406,0.75,0.094,0.02,0.17
+Toto-2.0-4m,Seasonal Naive,0.906,0.781,1.0,0.216,0.169,0.263
+Moirai-2.0,Chronos-2,0.062,0.0,0.156,-0.107,-0.164,-0.06
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+Moirai-2.0,Toto-2.0-2.5B,0.156,0.031,0.282,-0.085,-0.144,-0.034
+Moirai-2.0,Toto-2.0-313m,0.25,0.094,0.406,-0.082,-0.14,-0.029
+Moirai-2.0,TiRex,0.094,0.0,0.188,-0.073,-0.118,-0.037
+Moirai-2.0,TimesFM-2.5,0.219,0.093,0.375,-0.081,-0.132,-0.039
+Moirai-2.0,FlowState,0.281,0.125,0.438,-0.023,-0.113,0.084
+Moirai-2.0,TabPFN-TS-3,0.219,0.094,0.345,-0.029,-0.09,0.041
+Moirai-2.0,Toto-2.0-22m,0.25,0.094,0.406,-0.054,-0.105,-0.004
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+Moirai-2.0,Toto-1.0,0.469,0.281,0.656,-0.023,-0.05,0.003
+Moirai-2.0,Chronos-Bolt,0.453,0.312,0.594,-0.006,-0.063,0.049
+Moirai-2.0,Toto-2.0-4m,0.438,0.25,0.594,-0.017,-0.063,0.027
+Moirai-2.0,Moirai-2.0,0.5,0.5,0.5,0.0,0.0,0.0
+Moirai-2.0,Stat. Ensemble,0.594,0.438,0.75,0.079,-0.007,0.16
+Moirai-2.0,Seasonal Naive,0.844,0.719,0.938,0.203,0.149,0.256
+Stat. Ensemble,Chronos-2,0.156,0.031,0.281,-0.202,-0.318,-0.108
+Stat. Ensemble,Toto-2.0-1B,0.219,0.062,0.344,-0.181,-0.303,-0.086
+Stat. Ensemble,Toto-2.0-2.5B,0.25,0.094,0.406,-0.178,-0.298,-0.085
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+Stat. Ensemble,TiRex,0.281,0.125,0.438,-0.165,-0.268,-0.077
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+Stat. Ensemble,FlowState,0.312,0.156,0.469,-0.111,-0.239,0.027
+Stat. Ensemble,TabPFN-TS-3,0.219,0.094,0.375,-0.117,-0.231,-0.009
+Stat. Ensemble,Toto-2.0-22m,0.219,0.062,0.344,-0.144,-0.258,-0.055
+Stat. Ensemble,TabPFN-TS,0.281,0.125,0.438,-0.123,-0.236,-0.017
+Stat. Ensemble,Toto-1.0,0.406,0.25,0.562,-0.111,-0.218,-0.021
+Stat. Ensemble,Chronos-Bolt,0.406,0.25,0.562,-0.092,-0.194,-0.008
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+Stat. Ensemble,Moirai-2.0,0.406,0.25,0.562,-0.086,-0.191,0.007
+Stat. Ensemble,Stat. Ensemble,0.5,0.5,0.5,0.0,0.0,0.0
+Stat. Ensemble,Seasonal Naive,0.75,0.609,0.891,0.135,0.054,0.199
+Seasonal Naive,Chronos-2,0.0,0.0,0.0,-0.389,-0.476,-0.315
+Seasonal Naive,Toto-2.0-1B,0.062,0.0,0.156,-0.365,-0.452,-0.287
+Seasonal Naive,Toto-2.0-2.5B,0.062,0.0,0.156,-0.361,-0.446,-0.285
+Seasonal Naive,Toto-2.0-313m,0.031,0.0,0.094,-0.357,-0.444,-0.281
+Seasonal Naive,TiRex,0.0,0.0,0.0,-0.346,-0.433,-0.274
+Seasonal Naive,TimesFM-2.5,0.031,0.0,0.094,-0.356,-0.445,-0.28
+Seasonal Naive,FlowState,0.125,0.031,0.25,-0.284,-0.416,-0.124
+Seasonal Naive,TabPFN-TS-3,0.062,0.0,0.156,-0.291,-0.391,-0.174
+Seasonal Naive,Toto-2.0-22m,0.031,0.0,0.094,-0.322,-0.404,-0.246
+Seasonal Naive,TabPFN-TS,0.062,0.0,0.156,-0.298,-0.395,-0.183
+Seasonal Naive,Toto-1.0,0.062,0.0,0.156,-0.284,-0.367,-0.21
+Seasonal Naive,Chronos-Bolt,0.156,0.062,0.281,-0.262,-0.369,-0.159
+Seasonal Naive,Toto-2.0-4m,0.094,0.0,0.219,-0.276,-0.356,-0.203
+Seasonal Naive,Moirai-2.0,0.156,0.062,0.281,-0.255,-0.344,-0.176
+Seasonal Naive,Stat. Ensemble,0.25,0.109,0.391,-0.156,-0.248,-0.057
+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0

tables/task_type_univariate/pairwise_SQL.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
+Chronos-2,Chronos-2,0.5,0.5,0.5,0.0,0.0,0.0
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+Chronos-2,Toto-2.0-2.5B,0.625,0.438,0.781,0.022,-0.005,0.051
+Chronos-2,Toto-2.0-313m,0.594,0.406,0.781,0.027,-0.0,0.056
+Chronos-2,TiRex,0.75,0.594,0.906,0.031,0.011,0.054
+Chronos-2,TimesFM-2.5,0.656,0.499,0.812,0.032,0.01,0.054
+Chronos-2,Toto-2.0-22m,0.75,0.594,0.906,0.048,0.021,0.079
+Chronos-2,TabPFN-TS-3,0.781,0.625,0.938,0.065,0.031,0.101
+Chronos-2,FlowState,0.719,0.562,0.875,0.094,0.024,0.189
+Chronos-2,TabPFN-TS,0.812,0.656,0.938,0.069,0.039,0.105
+Chronos-2,Toto-1.0,0.875,0.75,0.969,0.08,0.047,0.117
+Chronos-2,Chronos-Bolt,0.906,0.781,1.0,0.099,0.058,0.144
+Chronos-2,Toto-2.0-4m,0.906,0.781,1.0,0.085,0.054,0.119
+Chronos-2,Moirai-2.0,0.938,0.844,1.0,0.113,0.072,0.16
+Chronos-2,Stat. Ensemble,0.938,0.844,1.0,0.245,0.163,0.33
+Chronos-2,Seasonal Naive,1.0,1.0,1.0,0.37,0.327,0.414
+Toto-2.0-1B,Chronos-2,0.406,0.25,0.563,-0.02,-0.052,0.011
+Toto-2.0-1B,Toto-2.0-1B,0.5,0.5,0.5,0.0,0.0,0.0
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+Toto-2.0-1B,Seasonal Naive,0.938,0.844,1.0,0.358,0.303,0.406
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+Toto-2.0-2.5B,Moirai-2.0,0.875,0.75,0.969,0.094,0.045,0.141
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+Toto-2.0-2.5B,Seasonal Naive,0.969,0.906,1.0,0.356,0.303,0.402
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+Toto-2.0-313m,Stat. Ensemble,0.812,0.688,0.938,0.224,0.132,0.322
+Toto-2.0-313m,Seasonal Naive,0.969,0.906,1.0,0.353,0.3,0.401
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+TiRex,TiRex,0.5,0.5,0.5,0.0,0.0,0.0
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+TimesFM-2.5,Seasonal Naive,0.969,0.906,1.0,0.349,0.302,0.398
+Toto-2.0-22m,Chronos-2,0.25,0.094,0.406,-0.051,-0.085,-0.021
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+Toto-2.0-22m,TiRex,0.375,0.219,0.531,-0.018,-0.049,0.009
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+Toto-2.0-22m,TabPFN-TS,0.594,0.438,0.75,0.022,-0.024,0.068
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+Toto-2.0-22m,Seasonal Naive,0.969,0.906,1.0,0.338,0.284,0.386
+TabPFN-TS-3,Chronos-2,0.219,0.062,0.375,-0.069,-0.112,-0.032
+TabPFN-TS-3,Toto-2.0-1B,0.312,0.156,0.469,-0.048,-0.114,0.002
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+TabPFN-TS-3,TimesFM-2.5,0.406,0.25,0.562,-0.034,-0.08,0.0
+TabPFN-TS-3,Toto-2.0-22m,0.438,0.281,0.625,-0.018,-0.069,0.029
+TabPFN-TS-3,TabPFN-TS-3,0.5,0.5,0.5,0.0,0.0,0.0
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+TabPFN-TS-3,Toto-1.0,0.656,0.5,0.812,0.017,-0.042,0.068
+TabPFN-TS-3,Chronos-Bolt,0.75,0.594,0.906,0.037,-0.007,0.083
+TabPFN-TS-3,Toto-2.0-4m,0.688,0.531,0.844,0.021,-0.028,0.065
+TabPFN-TS-3,Moirai-2.0,0.75,0.594,0.906,0.052,0.007,0.104
+TabPFN-TS-3,Stat. Ensemble,0.781,0.625,0.906,0.193,0.1,0.283
+TabPFN-TS-3,Seasonal Naive,1.0,1.0,1.0,0.327,0.277,0.375
+FlowState,Chronos-2,0.281,0.125,0.438,-0.104,-0.233,-0.024
+FlowState,Toto-2.0-1B,0.312,0.156,0.469,-0.082,-0.231,0.01
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+FlowState,Chronos-Bolt,0.594,0.438,0.75,0.005,-0.082,0.066
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+FlowState,Moirai-2.0,0.656,0.5,0.812,0.021,-0.087,0.097
+FlowState,Stat. Ensemble,0.719,0.562,0.845,0.167,0.052,0.258
+FlowState,Seasonal Naive,0.938,0.844,1.0,0.305,0.215,0.368
+TabPFN-TS,Chronos-2,0.188,0.062,0.344,-0.074,-0.118,-0.041
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+Moirai-2.0,Seasonal Naive,0.875,0.75,0.969,0.29,0.228,0.347
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+Seasonal Naive,TabPFN-TS,0.031,0.0,0.125,-0.479,-0.584,-0.38
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+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0

tables/task_type_univariate/pairwise_WAPE.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
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+TiRex,Toto-2.0-22m,0.562,0.375,0.75,0.009,-0.02,0.038
+TiRex,TabPFN-TS,0.625,0.469,0.781,0.006,-0.047,0.047
+TiRex,Toto-1.0,0.812,0.688,0.938,0.049,0.016,0.083
+TiRex,Chronos-Bolt,0.781,0.625,0.906,0.051,0.014,0.089
+TiRex,Moirai-2.0,0.812,0.687,0.938,0.08,0.038,0.132
+TiRex,Toto-2.0-4m,0.812,0.656,0.938,0.06,0.029,0.093
+TiRex,Stat. Ensemble,0.781,0.625,0.906,0.14,0.063,0.212
+TiRex,Seasonal Naive,0.969,0.906,1.0,0.292,0.228,0.352
+TabPFN-TS-3,Toto-2.0-2.5B,0.312,0.156,0.5,-0.043,-0.105,0.009
+TabPFN-TS-3,Chronos-2,0.281,0.125,0.438,-0.064,-0.117,-0.016
+TabPFN-TS-3,Toto-2.0-1B,0.406,0.25,0.562,-0.038,-0.103,0.018
+TabPFN-TS-3,Toto-2.0-313m,0.375,0.219,0.531,-0.036,-0.094,0.017
+TabPFN-TS-3,TimesFM-2.5,0.531,0.375,0.688,-0.035,-0.088,0.009
+TabPFN-TS-3,TiRex,0.5,0.344,0.656,-0.028,-0.086,0.021
+TabPFN-TS-3,TabPFN-TS-3,0.5,0.5,0.5,0.0,0.0,0.0
+TabPFN-TS-3,FlowState,0.438,0.281,0.625,-0.041,-0.112,0.013
+TabPFN-TS-3,Toto-2.0-22m,0.5,0.344,0.656,-0.019,-0.083,0.032
+TabPFN-TS-3,TabPFN-TS,0.594,0.406,0.75,-0.022,-0.071,0.018
+TabPFN-TS-3,Toto-1.0,0.656,0.5,0.812,0.022,-0.039,0.084
+TabPFN-TS-3,Chronos-Bolt,0.719,0.562,0.875,0.024,-0.023,0.07
+TabPFN-TS-3,Moirai-2.0,0.781,0.656,0.906,0.054,0.001,0.11
+TabPFN-TS-3,Toto-2.0-4m,0.75,0.594,0.876,0.034,-0.025,0.089
+TabPFN-TS-3,Stat. Ensemble,0.812,0.688,0.938,0.115,0.027,0.198
+TabPFN-TS-3,Seasonal Naive,0.969,0.906,1.0,0.272,0.223,0.317
+FlowState,Toto-2.0-2.5B,0.281,0.156,0.438,-0.002,-0.056,0.061
+FlowState,Chronos-2,0.375,0.219,0.531,-0.022,-0.072,0.039
+FlowState,Toto-2.0-1B,0.375,0.219,0.531,0.003,-0.056,0.069
+FlowState,Toto-2.0-313m,0.344,0.188,0.5,0.005,-0.048,0.065
+FlowState,TimesFM-2.5,0.375,0.219,0.531,0.006,-0.035,0.059
+FlowState,TiRex,0.469,0.281,0.625,0.012,-0.028,0.06
+FlowState,TabPFN-TS-3,0.562,0.375,0.719,0.04,-0.013,0.101
+FlowState,FlowState,0.5,0.5,0.5,0.0,0.0,0.0
+FlowState,Toto-2.0-22m,0.5,0.312,0.656,0.021,-0.022,0.065
+FlowState,TabPFN-TS,0.688,0.531,0.844,0.018,-0.017,0.05
+FlowState,Toto-1.0,0.656,0.5,0.812,0.061,0.005,0.117
+FlowState,Chronos-Bolt,0.719,0.562,0.875,0.063,0.01,0.12
+FlowState,Moirai-2.0,0.656,0.5,0.812,0.092,0.033,0.161
+FlowState,Toto-2.0-4m,0.688,0.531,0.844,0.072,0.023,0.122
+FlowState,Stat. Ensemble,0.781,0.625,0.906,0.15,0.076,0.22
+FlowState,Seasonal Naive,0.906,0.812,1.0,0.301,0.235,0.366
+Toto-2.0-22m,Toto-2.0-2.5B,0.156,0.031,0.281,-0.023,-0.05,0.007
+Toto-2.0-22m,Chronos-2,0.25,0.094,0.406,-0.043,-0.084,-0.004
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+Toto-2.0-22m,Toto-2.0-313m,0.25,0.094,0.406,-0.016,-0.039,0.012
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+Toto-2.0-22m,Chronos-Bolt,0.719,0.562,0.875,0.043,-0.003,0.085
+Toto-2.0-22m,Moirai-2.0,0.781,0.625,0.906,0.072,0.024,0.125
+Toto-2.0-22m,Toto-2.0-4m,0.844,0.719,0.938,0.052,0.034,0.07
+Toto-2.0-22m,Stat. Ensemble,0.719,0.562,0.875,0.132,0.063,0.206
+Toto-2.0-22m,Seasonal Naive,0.938,0.844,1.0,0.286,0.222,0.35
+TabPFN-TS,Toto-2.0-2.5B,0.219,0.094,0.375,-0.021,-0.068,0.037
+TabPFN-TS,Chronos-2,0.188,0.062,0.312,-0.041,-0.082,0.013
+TabPFN-TS,Toto-2.0-1B,0.281,0.125,0.438,-0.016,-0.067,0.047
+TabPFN-TS,Toto-2.0-313m,0.25,0.094,0.406,-0.013,-0.063,0.044
+TabPFN-TS,TimesFM-2.5,0.344,0.188,0.5,-0.012,-0.059,0.039
+TabPFN-TS,TiRex,0.375,0.219,0.531,-0.006,-0.049,0.044
+TabPFN-TS,TabPFN-TS-3,0.406,0.25,0.594,0.022,-0.018,0.066
+TabPFN-TS,FlowState,0.312,0.156,0.469,-0.019,-0.052,0.017
+TabPFN-TS,Toto-2.0-22m,0.438,0.281,0.594,0.003,-0.04,0.047
+TabPFN-TS,TabPFN-TS,0.5,0.5,0.5,0.0,0.0,0.0
+TabPFN-TS,Toto-1.0,0.531,0.374,0.719,0.043,-0.011,0.102
+TabPFN-TS,Chronos-Bolt,0.625,0.469,0.781,0.045,-0.005,0.103
+TabPFN-TS,Moirai-2.0,0.625,0.468,0.781,0.075,0.01,0.145
+TabPFN-TS,Toto-2.0-4m,0.688,0.531,0.844,0.055,0.01,0.104
+TabPFN-TS,Stat. Ensemble,0.688,0.531,0.844,0.135,0.071,0.198
+TabPFN-TS,Seasonal Naive,1.0,1.0,1.0,0.288,0.233,0.341
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+Toto-1.0,Seasonal Naive,0.938,0.844,1.0,0.256,0.185,0.321
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+Chronos-Bolt,Toto-2.0-1B,0.188,0.062,0.312,-0.064,-0.118,-0.012
+Chronos-Bolt,Toto-2.0-313m,0.281,0.125,0.438,-0.061,-0.112,-0.012
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+Chronos-Bolt,TiRex,0.219,0.094,0.375,-0.054,-0.097,-0.014
+Chronos-Bolt,TabPFN-TS-3,0.281,0.125,0.438,-0.025,-0.075,0.022
+Chronos-Bolt,FlowState,0.281,0.125,0.438,-0.067,-0.136,-0.01
+Chronos-Bolt,Toto-2.0-22m,0.281,0.125,0.438,-0.045,-0.093,0.003
+Chronos-Bolt,TabPFN-TS,0.375,0.219,0.531,-0.048,-0.115,0.005
+Chronos-Bolt,Toto-1.0,0.469,0.281,0.656,-0.002,-0.042,0.039
+Chronos-Bolt,Chronos-Bolt,0.5,0.5,0.5,0.0,0.0,0.0
+Chronos-Bolt,Moirai-2.0,0.516,0.375,0.656,0.031,-0.007,0.074
+Chronos-Bolt,Toto-2.0-4m,0.469,0.281,0.626,0.01,-0.029,0.051
+Chronos-Bolt,Stat. Ensemble,0.656,0.5,0.812,0.093,0.009,0.177
+Chronos-Bolt,Seasonal Naive,0.906,0.781,1.0,0.254,0.188,0.321
+Moirai-2.0,Toto-2.0-2.5B,0.156,0.031,0.281,-0.103,-0.173,-0.045
+Moirai-2.0,Chronos-2,0.156,0.031,0.281,-0.124,-0.196,-0.067
+Moirai-2.0,Toto-2.0-1B,0.156,0.062,0.281,-0.098,-0.168,-0.036
+Moirai-2.0,Toto-2.0-313m,0.188,0.062,0.312,-0.095,-0.163,-0.034
+Moirai-2.0,TimesFM-2.5,0.219,0.094,0.375,-0.094,-0.16,-0.04
+Moirai-2.0,TiRex,0.188,0.062,0.313,-0.087,-0.152,-0.039
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+Moirai-2.0,Chronos-Bolt,0.484,0.344,0.625,-0.031,-0.079,0.006
+Moirai-2.0,Moirai-2.0,0.5,0.5,0.5,0.0,0.0,0.0
+Moirai-2.0,Toto-2.0-4m,0.406,0.25,0.594,-0.022,-0.076,0.025
+Moirai-2.0,Stat. Ensemble,0.625,0.469,0.781,0.065,-0.031,0.153
+Moirai-2.0,Seasonal Naive,0.812,0.656,0.938,0.231,0.16,0.294
+Toto-2.0-4m,Toto-2.0-2.5B,0.094,0.0,0.219,-0.079,-0.123,-0.04
+Toto-2.0-4m,Chronos-2,0.125,0.031,0.25,-0.101,-0.154,-0.058
+Toto-2.0-4m,Toto-2.0-1B,0.125,0.031,0.25,-0.075,-0.116,-0.033
+Toto-2.0-4m,Toto-2.0-313m,0.156,0.031,0.281,-0.072,-0.108,-0.033
+Toto-2.0-4m,TimesFM-2.5,0.25,0.094,0.406,-0.071,-0.121,-0.025
+Toto-2.0-4m,TiRex,0.188,0.062,0.344,-0.064,-0.102,-0.03
+Toto-2.0-4m,TabPFN-TS-3,0.25,0.124,0.406,-0.035,-0.097,0.025
+Toto-2.0-4m,FlowState,0.312,0.156,0.469,-0.078,-0.139,-0.024
+Toto-2.0-4m,Toto-2.0-22m,0.156,0.062,0.281,-0.055,-0.075,-0.035
+Toto-2.0-4m,TabPFN-TS,0.312,0.156,0.469,-0.058,-0.116,-0.01
+Toto-2.0-4m,Toto-1.0,0.375,0.219,0.531,-0.012,-0.04,0.021
+Toto-2.0-4m,Chronos-Bolt,0.531,0.374,0.719,-0.01,-0.053,0.028
+Toto-2.0-4m,Moirai-2.0,0.594,0.406,0.75,0.021,-0.026,0.07
+Toto-2.0-4m,Toto-2.0-4m,0.5,0.5,0.5,0.0,0.0,0.0
+Toto-2.0-4m,Stat. Ensemble,0.594,0.438,0.75,0.084,0.009,0.16
+Toto-2.0-4m,Seasonal Naive,0.906,0.812,1.0,0.247,0.182,0.311
+Stat. Ensemble,Toto-2.0-2.5B,0.125,0.031,0.25,-0.179,-0.286,-0.077
+Stat. Ensemble,Chronos-2,0.125,0.031,0.25,-0.202,-0.316,-0.101
+Stat. Ensemble,Toto-2.0-1B,0.156,0.031,0.281,-0.174,-0.285,-0.068
+Stat. Ensemble,Toto-2.0-313m,0.156,0.031,0.281,-0.171,-0.279,-0.071
+Stat. Ensemble,TimesFM-2.5,0.156,0.031,0.281,-0.169,-0.279,-0.069
+Stat. Ensemble,TiRex,0.219,0.094,0.375,-0.162,-0.269,-0.067
+Stat. Ensemble,TabPFN-TS-3,0.188,0.062,0.312,-0.13,-0.247,-0.028
+Stat. Ensemble,FlowState,0.219,0.094,0.375,-0.177,-0.281,-0.082
+Stat. Ensemble,Toto-2.0-22m,0.281,0.125,0.438,-0.152,-0.26,-0.067
+Stat. Ensemble,TabPFN-TS,0.312,0.156,0.469,-0.155,-0.247,-0.076
+Stat. Ensemble,Toto-1.0,0.406,0.25,0.562,-0.105,-0.205,-0.016
+Stat. Ensemble,Chronos-Bolt,0.344,0.188,0.5,-0.103,-0.215,-0.009
+Stat. Ensemble,Moirai-2.0,0.375,0.219,0.531,-0.069,-0.18,0.03
+Stat. Ensemble,Toto-2.0-4m,0.406,0.25,0.562,-0.092,-0.19,-0.01
+Stat. Ensemble,Stat. Ensemble,0.5,0.5,0.5,0.0,0.0,0.0
+Stat. Ensemble,Seasonal Naive,0.781,0.625,0.906,0.177,0.101,0.252
+Seasonal Naive,Toto-2.0-2.5B,0.062,0.0,0.156,-0.433,-0.565,-0.309
+Seasonal Naive,Chronos-2,0.062,0.0,0.156,-0.461,-0.597,-0.342
+Seasonal Naive,Toto-2.0-1B,0.062,0.0,0.156,-0.427,-0.567,-0.296
+Seasonal Naive,Toto-2.0-313m,0.062,0.0,0.156,-0.423,-0.557,-0.299
+Seasonal Naive,TimesFM-2.5,0.031,0.0,0.094,-0.421,-0.554,-0.307
+Seasonal Naive,TiRex,0.031,0.0,0.094,-0.413,-0.544,-0.296
+Seasonal Naive,TabPFN-TS-3,0.031,0.0,0.094,-0.374,-0.465,-0.287
+Seasonal Naive,FlowState,0.094,0.0,0.188,-0.431,-0.577,-0.306
+Seasonal Naive,Toto-2.0-22m,0.062,0.0,0.156,-0.401,-0.539,-0.285
+Seasonal Naive,TabPFN-TS,0.0,0.0,0.0,-0.404,-0.517,-0.303
+Seasonal Naive,Toto-1.0,0.062,0.0,0.156,-0.344,-0.473,-0.226
+Seasonal Naive,Chronos-Bolt,0.094,0.0,0.219,-0.341,-0.472,-0.231
+Seasonal Naive,Moirai-2.0,0.188,0.062,0.344,-0.3,-0.417,-0.19
+Seasonal Naive,Toto-2.0-4m,0.094,0.0,0.188,-0.328,-0.452,-0.223
+Seasonal Naive,Stat. Ensemble,0.219,0.094,0.375,-0.215,-0.337,-0.112
+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0

tables/task_type_univariate/pairwise_WQL.csv

@@ -0,0 +1,257 @@
+model_1,model_2,win_rate,win_rate_lower,win_rate_upper,skill_score,skill_score_lower,skill_score_upper
+Chronos-2,Chronos-2,0.5,0.5,0.5,0.0,0.0,0.0
+Chronos-2,Toto-2.0-2.5B,0.5,0.312,0.688,0.023,-0.002,0.049
+Chronos-2,Toto-2.0-1B,0.469,0.312,0.656,0.027,0.001,0.057
+Chronos-2,Toto-2.0-313m,0.656,0.5,0.812,0.031,0.004,0.059
+Chronos-2,TiRex,0.719,0.562,0.875,0.034,0.009,0.062
+Chronos-2,TimesFM-2.5,0.688,0.531,0.844,0.035,0.013,0.058
+Chronos-2,TabPFN-TS-3,0.75,0.594,0.875,0.059,0.019,0.098
+Chronos-2,Toto-2.0-22m,0.719,0.562,0.875,0.044,0.006,0.078
+Chronos-2,FlowState,0.656,0.5,0.812,0.039,-0.02,0.086
+Chronos-2,TabPFN-TS,0.812,0.688,0.938,0.053,0.011,0.085
+Chronos-2,Toto-1.0,0.844,0.719,0.969,0.086,0.05,0.125
+Chronos-2,Chronos-Bolt,0.844,0.719,0.969,0.091,0.057,0.13
+Chronos-2,Toto-2.0-4m,0.938,0.844,1.0,0.092,0.051,0.131
+Chronos-2,Moirai-2.0,0.875,0.75,0.969,0.122,0.075,0.176
+Chronos-2,TFT,0.938,0.844,1.0,0.199,0.134,0.269
+Chronos-2,Seasonal Naive,0.969,0.906,1.0,0.408,0.346,0.462
+Toto-2.0-2.5B,Chronos-2,0.5,0.312,0.688,-0.024,-0.052,0.002
+Toto-2.0-2.5B,Toto-2.0-2.5B,0.5,0.5,0.5,0.0,0.0,0.0
+Toto-2.0-2.5B,Toto-2.0-1B,0.594,0.438,0.75,0.004,-0.005,0.016
+Toto-2.0-2.5B,Toto-2.0-313m,0.656,0.469,0.812,0.009,-0.001,0.018
+Toto-2.0-2.5B,TiRex,0.594,0.438,0.75,0.011,-0.015,0.037
+Toto-2.0-2.5B,TimesFM-2.5,0.562,0.405,0.719,0.012,-0.017,0.039
+Toto-2.0-2.5B,TabPFN-TS-3,0.625,0.469,0.781,0.037,-0.011,0.086
+Toto-2.0-2.5B,Toto-2.0-22m,0.781,0.625,0.906,0.021,-0.009,0.046
+Toto-2.0-2.5B,FlowState,0.75,0.594,0.875,0.016,-0.049,0.068
+Toto-2.0-2.5B,TabPFN-TS,0.781,0.625,0.906,0.03,-0.017,0.069
+Toto-2.0-2.5B,Toto-1.0,0.844,0.719,0.969,0.064,0.03,0.101
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+Moirai-2.0,Seasonal Naive,0.844,0.719,0.969,0.326,0.251,0.395
+TFT,Chronos-2,0.062,0.0,0.156,-0.249,-0.368,-0.154
+TFT,Toto-2.0-2.5B,0.156,0.062,0.281,-0.22,-0.345,-0.113
+TFT,Toto-2.0-1B,0.125,0.031,0.25,-0.215,-0.337,-0.109
+TFT,Toto-2.0-313m,0.125,0.031,0.25,-0.209,-0.333,-0.105
+TFT,TiRex,0.188,0.062,0.313,-0.206,-0.322,-0.106
+TFT,TimesFM-2.5,0.156,0.031,0.281,-0.205,-0.319,-0.115
+TFT,TabPFN-TS-3,0.219,0.094,0.375,-0.175,-0.28,-0.084
+TFT,Toto-2.0-22m,0.219,0.094,0.375,-0.194,-0.324,-0.081
+TFT,FlowState,0.281,0.156,0.438,-0.2,-0.354,-0.078
+TFT,TabPFN-TS,0.344,0.188,0.5,-0.183,-0.309,-0.083
+TFT,Toto-1.0,0.312,0.156,0.469,-0.142,-0.262,-0.041
+TFT,Chronos-Bolt,0.344,0.188,0.5,-0.135,-0.237,-0.047
+TFT,Toto-2.0-4m,0.344,0.188,0.5,-0.134,-0.256,-0.029
+TFT,Moirai-2.0,0.344,0.188,0.5,-0.096,-0.22,0.006
+TFT,TFT,0.5,0.5,0.5,0.0,0.0,0.0
+TFT,Seasonal Naive,0.812,0.656,0.938,0.261,0.17,0.339
+Seasonal Naive,Chronos-2,0.031,0.0,0.094,-0.691,-0.858,-0.53
+Seasonal Naive,Toto-2.0-2.5B,0.062,0.0,0.156,-0.652,-0.824,-0.476
+Seasonal Naive,Toto-2.0-1B,0.062,0.0,0.156,-0.645,-0.829,-0.459
+Seasonal Naive,Toto-2.0-313m,0.062,0.0,0.156,-0.637,-0.813,-0.464
+Seasonal Naive,TiRex,0.0,0.0,0.0,-0.633,-0.81,-0.465
+Seasonal Naive,TimesFM-2.5,0.031,0.0,0.094,-0.631,-0.801,-0.472
+Seasonal Naive,TabPFN-TS-3,0.0,0.0,0.0,-0.591,-0.737,-0.46
+Seasonal Naive,Toto-2.0-22m,0.062,0.0,0.156,-0.617,-0.793,-0.454
+Seasonal Naive,FlowState,0.094,0.0,0.188,-0.624,-0.806,-0.467
+Seasonal Naive,TabPFN-TS,0.0,0.0,0.0,-0.601,-0.75,-0.462
+Seasonal Naive,Toto-1.0,0.094,0.0,0.219,-0.546,-0.721,-0.386
+Seasonal Naive,Chronos-Bolt,0.062,0.0,0.156,-0.536,-0.698,-0.385
+Seasonal Naive,Toto-2.0-4m,0.062,0.0,0.156,-0.536,-0.693,-0.386
+Seasonal Naive,Moirai-2.0,0.156,0.031,0.281,-0.484,-0.654,-0.335
+Seasonal Naive,TFT,0.188,0.062,0.344,-0.354,-0.513,-0.205
+Seasonal Naive,Seasonal Naive,0.5,0.5,0.5,0.0,0.0,0.0