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ResearchFormerly WizWand

Graph Classification on CIFAR10

77.784AccuracyTAU-GRIT
53.1942459.5781265.96272.34588Jun 14, 2020Jun 15, 2021Jun 17, 2022Jun 18, 2023Jun 19, 2024Jun 20, 2025Jun 22, 2026
Updated 4mo ago

Evaluation results

MethodLinks
TAU-GRITTokenizer=TAU, Backbone=GRIT2025.1077.784
GRIT2024.0276.468
GRIT2025.1076.468
GNN-AK+backbone=PNA*, Sampling=SubgraphDrop2021.1074.79
EXPHORMER2023.0374.69
TIGT2024.0273.955
LRGA + GatedGCNParameter Budget=487K2020.0673.48
PNA*2021.1073.11
QUESTAttention=QUEST2026.0372.843
DGN2021.1072.84
DGN2023.0372.84
DGN2024.0272.838
GNN-AK+backbone=GCN2021.1072.7
DGN#Param=≈100K2021.0872.7
PNAedge features=none2022.0572.7
GPS + GFSAGFSA=true2023.1272.44
GNN-AK+backbone=GIN, Sampling=SubgraphDrop2021.1072.39
GraphGPS2023.0372.3
GPSGFSA=false2023.1272.3
GPS2024.0272.298
StandardAttention=Standard2026.0372.298
GraphGPS2025.1072.298
GNN-AK+backbone=GIN2021.1072.19
GIN-AK+2023.0372.19
GIN-AK+2024.0272.19
GNN-AK+backbone=GCN, Sampling=SubgraphDrop2021.1071.93
LRGA + GATParameter Budget=476K2020.0671.57
GatedGCNParameter Budget=500K2020.0671.33
LRGA + GatedGCNParameter Budget=93K2020.0670.65
PNA2021.1070.47
PNA#Param=≈100K2021.0870.35
PNA2023.0370.35
PNA2024.0270.35
Performer + GRF++Graph Features=GRF++2025.1070.21
PHM-GNNedge features=none2022.0570.2
Performer + GRFGraph Features=GRF2025.1070.1
Performer2025.1069.96
Graph-ViT + GFSAGFSA=true2023.1269.87
Graph-ViTGFSA=false2023.1269.67
GatedGCN2021.1069.37
FGN2026.0669.3
GatedGCNedge features=none2022.0569.2
CRaW12024.0269.013
CRaWI2023.0369.01
EGT#Param=≈100K2021.0868.702
EGT2024.0268.702
EGT2025.1068.702
EGT2023.0368.7
tGNNedge features=none2022.0568.4
LRGA + GCNParameter Budget=463K2020.0668.27
LRGA + GATParameter Budget=90K2020.0668
GNN-AKbackbone=GIN2021.1067.51
GatedGCN#Param=≈100K2021.0867.312
GatedGCN2024.0267.312
GatedGCNParameter Budget=104K2020.0667.31
GatedGCN2023.0367.31
GatedGCN2026.0667.3
LoGoGNN2026.0667.3
GATParameter Budget=442K2020.0666.11
Graphormer#Param=≈100K2021.0865.978
LRGA + GCNParameter Budget=91K2020.0665.8
SAGEReference=[36]2024.0765.77
GraphSage#Param=≈100K2021.0865.767
GraphSAGE2026.0665.7
GATedge features=none2022.0565.5
No PromptingQuantization Framework=FP32, Model Architecture=GAT2026.0165.4
Cy2C-GNNs2024.0264.285
GAT#Param=≈100K2021.0864.223
GAT2024.0264.223
GATParameter Budget=110K2020.0664.22
GAT2023.0364.22
GATReference=[36]2024.0764.22
GAT2026.0664.2
GPF-LoRAPQuantization Framework=A2Q, Model Architecture=GAT2026.0162.9
GPF-plusQuantization Framework=A2Q, Model Architecture=GAT2026.0162.3
No PromptingQuantization Framework=A2Q, Model Architecture=GAT2026.0161.9
GHC2024.0759.83
GIN2021.1059.82
GCN2021.1058.39
DiffPooledge features=none2022.0557.9
GPF-LoRAPQuantization Framework=DQ, Model Architecture=GAT2026.0157.5
GPF-LoRAPQuantization Framework=A2Q, Model Architecture=GIN2026.0157.4
GPF-plusQuantization Framework=A2Q, Model Architecture=GIN2026.0156.8
MLP2026.0656.3
MLPedge features=none2022.0556
GPF-LoRAPQuantization Framework=QAT, Model Architecture=GIN2026.0155.8
GCNParameter Budget=101K2020.0655.71
GCN#Param=≈100K2021.0855.71
GCN2023.0355.71
GCN2024.0255.71
GPF-plusQuantization Framework=QAT, Model Architecture=GIN2026.0155.3
GIN2023.0355.26
GIN#Param=≈100K2021.0855.255
GIN2024.0255.255
No PromptingQuantization Framework=A2Q, Model Architecture=GIN2026.0154.9
GCNParameter Budget=504K2020.0654.84
GCNedge features=none2022.0554.5
No PromptingQuantization Framework=FP32, Model Architecture=GCN2026.0154.5
No PromptingQuantization Framework=DQ, Model Architecture=GAT2026.0154.2
GCNReference=[36]2024.0754.14