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ResearchFormerly WizWand

Node Classification on ogbn-products (Accuracy)

85.11AccuracyC&S
72.442875.731479.0282.3086May 24, 2022Jan 23, 2023Sep 25, 2023May 27, 2024Jan 27, 2025Sep 29, 2025Jun 1, 2026
Updated 5mo ago

Evaluation results

MethodLinks
C&SCategory=Decoupling-based2022.1085.11
GraphSAGE*implementation=this paper2024.0683.89
Polynormer-rActivation=ReLU2024.0383.82
Polynormerimplementation=referenced2024.0683.82
Polynormer*implementation=this paper2024.0683.82
GAMLPCategory=Decoupling-based2022.1083.76
GOAT + HDSE2023.0883.38
SAGELearning Setting=Transductive, Infer. Time=11.9s, Storage Space=1.9GB2024.0583.27
Polynormer2024.0382.97
GNN-as-JudgeShot=10-shot2026.0382.48
FilterMoE2026.0682.36
GCN*implementation=this paper2024.0682.33
PolynormerLearning Setting=Transductive2024.0582.32
GOAT*implementation=this paper2024.0682.27
GOAT2024.0382
GOAT2023.0882
GOATimplementation=referenced2024.0682
GNN-as-JudgeShot=5-shot2026.0381.93
NID_SAGELearning Setting=Transductive, Infer. Time=0.7ms, Storage Space=17.5MB2024.0581.83
tGNN2022.0581.79
SGFormer*implementation=this paper2024.0681.54
GAMLP2026.0681.43
SAGNCategory=Decoupling-based2022.1081.21
AGT2023.0881.15
NFGNNscalable=true2022.1281.02
GNN-as-JudgeShot=3-shot2026.0381.02
GAT*implementation=this paper2024.0680.99
DeeperGCN2022.0580.98
ANS-GT2023.0880.64
GraphSAGECategory=Sampling-based2022.1080.61
SIGN2023.0880.52
SIGN2026.0680.52
HOGA2026.0680.36
GraphMAE22025.1280.09
BernNetscalable=true2022.1280.01
GPRGNNscalable=true2022.1279.93
GraphMAE + COREenhancement=CORE2025.1279.82
GPRGNN2024.0379.76
GPRGNNLearning Setting=Transductive2024.0579.76
GPRGNN2026.0679.76
GraphSAINTGNN Model=GAT2024.0679.71
TAPEShot=10-shot2026.0379.53
GraphMAE2 + COREenhancement=CORE2025.1279.52
GAT2024.0379.45
GAT2023.0879.45
GATimplementation=referenced2024.0679.45
SGFormer2023.0879.38
VQ-GNNGNN Model=GraphSAGE2024.0679.08
GraphMAE2025.1278.89
ClusterGCNCategory=Sampling-based2022.1078.62
GraphSAGE2022.0578.5
GraphSAGE2026.0678.4
GraphSAGEimplementation=referenced2024.0678.29
VQ-GNNGNN Model=GAT2024.0678.23
CoBFormer2023.0878.15
Sketch-GNNGNN Model=GAT, Sketch Ratio (c/n)=0.22024.0678.09
VQ-GNNGNN Model=GCN2024.0677.62
Sketch-GNNGNN Model=GCN, Sketch Ratio (c/n)=0.22024.0677.48
TAPEShot=5-shot2026.0377.44
GP2F2026.0276.91
w. NeighborShot=3-shot2026.0376.88
w. NeighborShot=5-shot2026.0376.88
w. NeighborShot=10-shot2026.0376.88
SIGNCategory=Decoupling-based2022.1076.85
APPNPscalable=false2022.1276.57
AdaGCNCategory=Others2022.1076.41
EnGCN w.o. SLECategory=Ours2022.1076.35
SGC2023.0876.31
GraphSAINTGNN Model=GraphSAGE2024.0676.02
GCN2022.0575.64
GCN2024.0375.64
GCN2023.0875.64
GCNimplementation=referenced2024.0675.64
GCN2026.0675.64
EnGCNCategory=Ours2022.1075.59
GraphSAINTGNN Model=GCN2024.0675.53
Zero-ShotShot=3-shot2026.0375.48
Zero-ShotShot=5-shot2026.0375.48
Zero-ShotShot=10-shot2026.0375.48
GraphSAINTCategory=Sampling-based2022.1075.36
LADIESCategory=Sampling-based2022.1075.31
Sketch-GNNGNN Model=GraphSAGE, Sketch Ratio (c/n)=0.22024.0675.24
ChebNetIIpre-propagation=performed once (no per-epoch message passing)2026.0675.1
GraphLoRA2026.0275.05
NAGphormer*implementation=this paper2024.0674.63
DIFFormer2024.0374.16
SGFormerLearning Setting=Transductive2024.0574.16
SGFormerimplementation=referenced2024.0674.16
Graph-CoTShot=3-shot2026.0374.15
Graph-CoTShot=5-shot2026.0374.15
Graph-CoTShot=10-shot2026.0374.15
GPF2026.0274.04
NodeFormer*implementation=this paper2024.0673.96
NAGphormer2024.0373.55
NAGphormer2023.0873.55
NAGphormerimplementation=referenced2024.0673.55
FastGCNCategory=Sampling-based2022.1073.46
NodeFormer2023.0873.15
NodeFormer2024.0372.93
NodeFormerimplementation=referenced2024.0672.93