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Few-shot classification on Meta-Dataset (test)

94.4OmniglotURT
34.776850.255965.73581.2141Mar 7, 2019Feb 22, 2020Feb 9, 2021Jan 27, 2022Jan 15, 2023Jan 2, 2024Dec 20, 2024

Evaluation results

MethodLinks
URT2020.0694.455.785.876.371.8—63.588.269.452.21.6————————
SUR2020.0693.156.385.471.471.5—63.182.870.452.42.5————————
Simple CNAPS2019.1291.7—82.474.967.877.746.990.7———58.6———————
SimpleCNAPS2020.0691.758.682.474.967.8—46.990.773.546.22.4————————
Simple AR-CNAPS2019.1291.1—81.874.372.875.245.690.3———56.5———————
TaskNorm2020.0690.750.683.874.662.1—48.789.66743.43.8————————
AR-CNAPS2019.1288.4—80.572.258.372.547.486———52.3———————
CNAPS2020.0688.452.380.572.258.3—47.48660.242.65.1————————
CNAPS2019.1288—76.871.462.571.94689.2———51.3———————
RelationNet2019.1286.6—69.754.156.661.832.676.1———30.9———————
RelationNetTraining Data Source=all datasets2019.0386.5730.8969.7154.1456.5661.7532.5676.0837.4827.415.8————————
TSPapplied on=TA2-Net2024.1285.2—73.576.678.371.54792.288.758.61.260.6—95.383.272.860.676.975.7
fo-MAMLTraining Data Source=all datasets2019.0383.9237.8376.4162.4364.1659.7333.5479.9442.9129.374.25————————
MAML2020.0683.937.876.462.464.1—33.579.942.929.48————————
TSPapplied on=TSA2024.1283.3—73.27678.270.846.691.887.559.4260.1—94.583.171.260.176.375
ProtoMAML2019.1282.9—74.27067.966.64288.5———47.9———————
ProtoMAML2020.0682.746.575.269.968.3—4288.752.441.75.4————————
fo-Proto-MAMLTraining Data Source=all datasets2019.0382.6946.5275.2369.8868.2566.8441.9988.7252.4241.741.5————————
TA2-Net2024.1281.1—72.675.176.868.445.39184.1583.459.3—94.98270.859.37573.8
ProtoNet2019.1279.6—71.16765.264.940.386.9———44.5———————
ProtoNet2020.0679.644.571.16765.2—40.386.946.539.97.3————————
ProtoNetTraining Data Source=all datasets2019.0379.5644.571.1467.0165.1864.8840.2686.8546.4839.872.85————————
MatchingNet2019.1278.3—69.256.461.860.833.781.9———36.1———————
MatchingNetTraining Data Source=all datasets2019.0378.2536.0869.1756.461.860.8133.781.955.5728.794.95————————
TSA2024.1278.2—72.274.977.367.644.790.982.5593.759.5—93.982.170.759.574.573.3
GAP+ Proto-MAML2024.1277.6—68.573.571.465.438.686.866.946.86.156.7—9474.563.256.768.968
BOHB-E2020.0677.555.460.973.672.8—44.590.657.551.94.4————————
k-NNTraining Data Source=all datasets2019.0374.638.5564.9866.3563.5844.8837.1283.4740.1129.555.05————————
k-NN2019.1274.6—6566.463.644.937.183.5———38.6———————
MAML2019.1271.9—52.847.256.750.52170.9———32.4———————
FinetuneTraining Data Source=all datasets2019.0371.1143.0872.0359.8269.1447.0538.1685.2866.7435.173.6————————
Finetune2019.1271.1—7259.869.147.138.285.3———43.1———————
MOKD2024.1270.9—59.873.676.161.24788.561.655.35.157.3—88.372.263.157.368.167.3
BOHB2024.1267.6—54.170.768.350.341.487.351.8487.551.9————51.959.959.1
OursDistillation=false, Backbone=ResNet-12, Evaluation protocol=Variable ways and shots2021.0365.5560.6465.6577.8481.0757.9149.2692.0678.9255.07——68.4——————
Ours-DistillDistillation=true, Backbone=ResNet-12, Evaluation protocol=Variable ways and shots2021.0365.5361.3666.5878.2380.4259.0249.592.6679.9255.68——68.89——————
RFS-SimpleDistillation=false, Backbone=ResNet-12, Evaluation protocol=Variable ways and shots2021.0364.9260.1463.1277.6978.5962.4847.1291.677.5157——68.02——————
RFS-DistillDistillation=true, Backbone=ResNet-12, Evaluation protocol=Variable ways and shots2021.0364.3161.4862.3279.4779.2860.8348.539176.3359.28——68.28——————
fo-Proto-MAMLTraining Data Source=ILSVRC-2012 only2019.0363.3749.5355.9568.6666.4951.5239.9687.1548.8343.741.85————————
fo-Proto-MAMLDistillation=false, Evaluation protocol=Variable ways and shots2021.0363.3749.5355.9568.6666.4951.5239.9687.1548.8343.74——57.52——————
ALFA+ Proto-MAML2024.1261.9—63.469.870.859.241.58660.848.1752.8————52.862.461.4
FLUTE2024.1261.6—48.547.963.857.531.880.146.541.48.946.9—80.865.452.746.956.555.8
FinetuneTraining Data Source=ILSVRC-2012 only2019.0360.8545.7868.6957.3169.0542.638.285.5166.7934.862.9————————
ProtoNetTraining Data Source=ILSVRC-2012 only2019.0359.9850.553.168.7966.5648.9639.7185.2747.12412.65————————
fo-MAMLTraining Data Source=ILSVRC-2012 only2019.0355.5545.5156.2463.6168.0443.9632.181.7450.9335.33.7————————
MatchingNetTraining Data Source=ILSVRC-2012 only2019.0352.274548.9762.2164.1542.8733.9780.1347.834.994.65————————
RelationNetTraining Data Source=ILSVRC-2012 only2019.0345.3534.6940.7349.5152.9743.330.5568.7633.6729.156.55————————
k-NNTraining Data Source=ILSVRC-2012 only2019.0337.0741.0346.8150.1366.3632.0636.1683.144.5930.385.7————————
EXP3-FLADBase Model=T5-XL, Auxiliary Data=T0Mix, Reward Function=GA2023.02————————————61.5——————
EXP3-FLADBase Model=T5-XL, Auxiliary Data=P3, Reward Function=GA2023.02————————————64.07——————
EXP3-FLADBase Model=T0-3B, Auxiliary Data=T0Mix, Reward Function=GA2023.02————————————62.87——————
EXP3-FLADBase Model=T0-3B, Auxiliary Data=P3, Reward Function=GA2023.02————————————65.98——————
EXP3-FLADBase Model=T5-XL, Auxiliary Data=T0Mix, Reward Function=GMS2023.02————————————61.72——————
EXP3-FLADBase Model=T5-XL, Auxiliary Data=P3, Reward Function=GMS2023.02————————————65.57——————
EXP3-FLADBase Model=T0-3B, Auxiliary Data=T0Mix, Reward Function=GMS2023.02————————————62.78——————
EXP3-FLADBase Model=T0-3B, Auxiliary Data=P3, Reward Function=GMS2023.02————————————65.51——————
EXP3-FLADBase Model=T5-XL, Auxiliary Data=T0Mix, Reward Function=AGG2023.02————————————62.05——————
EXP3-FLADBase Model=T5-XL, Auxiliary Data=P3, Reward Function=AGG2023.02————————————65.47——————
EXP3-FLADBase Model=T0-3B, Auxiliary Data=T0Mix, Reward Function=AGG2023.02————————————62.84——————
EXP3-FLADBase Model=T0-3B, Auxiliary Data=P3, Reward Function=AGG2023.02————————————66.84——————
Exploit-OnlyBase Model=T5-XL, Auxiliary Data=T0Mix2023.02————————————59.79——————
Exploit-OnlyBase Model=T5-XL, Auxiliary Data=P32023.02————————————60.49——————
Exploit-OnlyBase Model=T0-3B, Auxiliary Data=T0Mix2023.02————————————60.87——————
Exploit-OnlyBase Model=T0-3B, Auxiliary Data=P32023.02————————————62.87——————
Explore-OnlyBase Model=T5-XL, Auxiliary Data=T0Mix2023.02————————————59.18——————
Explore-OnlyBase Model=T5-XL, Auxiliary Data=P32023.02————————————60.61——————
Explore-OnlyBase Model=T0-3B, Auxiliary Data=T0Mix2023.02————————————61.17——————
Explore-OnlyBase Model=T0-3B, Auxiliary Data=P32023.02————————————62.77——————
Loss-ScalingBase Model=T5-XL, Auxiliary Data=T0Mix, Variant=GA2023.02————————————53.22——————
Loss-ScalingBase Model=T5-XL, Auxiliary Data=P3, Variant=GA2023.02————————————55.19——————
Loss-ScalingBase Model=T0-3B, Auxiliary Data=T0Mix, Variant=GA2023.02————————————59.47——————
Loss-ScalingBase Model=T0-3B, Auxiliary Data=P3, Variant=GA2023.02————————————60.66——————
Loss-ScalingBase Model=T5-XL, Auxiliary Data=T0Mix, Variant=GMS2023.02————————————55.98——————
Loss-ScalingBase Model=T5-XL, Auxiliary Data=P3, Variant=GMS2023.02————————————56.4——————
Loss-ScalingBase Model=T0-3B, Auxiliary Data=T0Mix, Variant=GMS2023.02————————————60.47——————
Loss-ScalingBase Model=T0-3B, Auxiliary Data=P3, Variant=GMS2023.02————————————60.7——————
Target-OnlyBase Model=T5-XL, Auxiliary Data=T0Mix2023.02————————————52.82——————
Target-OnlyBase Model=T0-3B, Auxiliary Data=T0Mix2023.02————————————56.44——————
UCB1-FLADBase Model=T5-XL, Auxiliary Data=T0Mix, Reward Function=GA2023.02————————————62.01——————
UCB1-FLADBase Model=T5-XL, Auxiliary Data=P3, Reward Function=GA2023.02————————————65.52——————
UCB1-FLADBase Model=T0-3B, Auxiliary Data=T0Mix, Reward Function=GA2023.02————————————62.35——————
UCB1-FLADBase Model=T0-3B, Auxiliary Data=P3, Reward Function=GA2023.02————————————66.29——————
UCB1-FLADBase Model=T5-XL, Auxiliary Data=T0Mix, Reward Function=GMS2023.02————————————61.67——————
UCB1-FLADBase Model=T5-XL, Auxiliary Data=P3, Reward Function=GMS2023.02————————————65.21——————
UCB1-FLADBase Model=T0-3B, Auxiliary Data=T0Mix, Reward Function=GMS2023.02————————————62.85——————
UCB1-FLADBase Model=T0-3B, Auxiliary Data=P3, Reward Function=GMS2023.02————————————66——————
UCB1-FLADBase Model=T5-XL, Auxiliary Data=T0Mix, Reward Function=AGG2023.02————————————62.08——————
UCB1-FLADBase Model=T5-XL, Auxiliary Data=P3, Reward Function=AGG2023.02————————————65.63——————
UCB1-FLADBase Model=T0-3B, Auxiliary Data=T0Mix, Reward Function=AGG2023.02————————————62.93——————
UCB1-FLADBase Model=T0-3B, Auxiliary Data=P3, Reward Function=AGG2023.02————————————66.29——————