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ResearchFormerly WizWand

Node Classification on Amazon-ratings heterophilic (test)

54.81AccuracyPolynormer
35.736440.688245.6450.5918May 29, 2025Jul 20, 2025Sep 11, 2025Nov 3, 2025Dec 25, 2025Feb 16, 2026Apr 10, 2026
Updated 6mo ago

Evaluation results

MethodLinks
Polynormer2026.0454.81
NT*variant=GT-augmented NT2026.0454.55
IM-CO-GNNparameters=μ, μ2025.0554.43
NTvariant=vanilla2026.0454.25
CO-GNNparameters=μ, μ2025.0554.17
IM-GatedGCN2025.0554.01
IM-GAT-sep2025.0553.97
SAGE2025.0553.63
Exphormer2025.0553.51
Exphormer2026.0453.51
IM-CO-GNNparameters=Σ, Σ2025.0553.11
GPS2025.0553.1
GraphGPS2026.0453.1
IM-FAGCN2025.0552.81
FSGNN2025.0552.74
GAT-sep2025.0552.7
IM-GCN2025.0552.37
GT-sep2025.0552.18
GATstruct_encoding=DEG2025.0551.65
CO-GNNparameters=Σ, Σ2025.0551.28
NAGphormer2025.0551.26
NAGphormer2026.0451.26
GT2025.0551.17
IM-GAT2025.0551.16
GPSbackbone=GAT, attention=Performer2025.0551.03
GCNstruct_encoding=DEG2025.0550.01
GPSbackbone=GAT, attention=Performer, pos_encoding=RWSE2025.0549.92
GAT2025.0549.09
GPSbackbone=GCN, attention=Performer, struct_encoding=DEG2025.0548.93
GPSbackbone=GAT, attention=Performer, pos_encoding=LapPE2025.0548.86
GCN2025.0548.7
GATpos_encoding=RWSE2025.0548.58
GPSbackbone=GCN, attention=Performer2025.0548.2
GPSbackbone=GCN, attention=Performer, pos_encoding=RWSE2025.0548.08
DIFFormer2026.0447.84
GCNpos_encoding=RWSE2025.0546.4
GBK-GNN2025.0545.98
GATpos_encoding=LapPE2025.0544.9
GPR-GNN2025.0544.88
GOAT2025.0544.61
GOAT2026.0444.61
GCNpos_encoding=LapPE2025.0544.35
FAGCN2025.0544.12
NodeFormer2026.0443.86
JacobiConv2025.0543.55
Gated-GCN2025.0543
CPGNN2025.0539.79
GloGNN2025.0536.89
H2GCN2025.0536.47