prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the RLC-GNN model in the RLC-GNN: An Improved Deep Architecture for Spatial-Based Graph Neural Network with Application to Fraud Detection paper on the Amazon-Fraud dataset? | AUC-ROC |
What metrics were used to measure the RioGNN model in the Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks paper on the Amazon-Fraud dataset? | AUC-ROC |
What metrics were used to measure the PC-GNN model in the Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection paper on the Amazon-Fraud dataset? | AUC-ROC |
What metrics were used to measure the CARE-GNN model in the Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters paper on the Amazon-Fraud dataset? | AUC-ROC |
What metrics were used to measure the ACMII-GCN model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACMII-Snowball-2 model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACM-Snowball-2 model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACM-GCN+ model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACM-GCN model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACM-Snowball-3 model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACM-GCN++ model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACMII-GCN+ model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACM-SGC-1 model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACM-SGC-2 model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACMII-Snowball-3 model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACM-GCNII* model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACM-GCNII model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the ACMII-GCN++ model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the BernNet model in the BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the APPNP model in the Predict then Propagate: Graph Neural Networks meet Personalized PageRank paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the GPRGNN model in the Adaptive Universal Generalized PageRank Graph Neural Network paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the MLP-2 model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the GCNII* model in the Simple and Deep Graph Convolutional Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the GCNII model in the Simple and Deep Graph Convolutional Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the FAGCN model in the Beyond Low-frequency Information in Graph Convolutional Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the H2GCN model in the Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the Snowball-3 model in the Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the Snowball-2 model in the Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the GCN model in the Semi-Supervised Classification with Graph Convolutional Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the GAT model in the Graph Attention Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the HH-GraphSAGE model in the Half-Hop: A graph upsampling approach for slowing down message passing paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the GAT+JK model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the HH-GAT model in the Half-Hop: A graph upsampling approach for slowing down message passing paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the SGC-2 model in the Simplifying Graph Convolutional Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the GraphSAGE model in the Inductive Representation Learning on Large Graphs paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the SGC-1 model in the Simplifying Graph Convolutional Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the GCN+JK model in the Revisiting Heterophily For Graph Neural Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the HH-GCN model in the Half-Hop: A graph upsampling approach for slowing down message passing paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the Geom-GCN* model in the Geom-GCN: Geometric Graph Convolutional Networks paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the MixHop model in the MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing paper on the Cornell (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the CPF-tra-GCNII model in the Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the VCHN model in the View-Consistent Heterogeneous Network on Graphs With Few Labeled Nodes paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the Truncated Krylov model in the Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the Snowball (linear) model in the Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the Snowball (tanh) model in the Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the Snowball (linear + tanh) model in the Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the MT-GCN model in the Mutual Teaching for Graph Convolutional Networks paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the AdaLanczosNet model in the LanczosNet: Multi-Scale Deep Graph Convolutional Networks paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the DCNN model in the Diffusion-Convolutional Neural Networks paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the LanczosNet model in the LanczosNet: Multi-Scale Deep Graph Convolutional Networks paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the GGNN model in the Gated Graph Sequence Neural Networks paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the GCN-FP model in the Convolutional Networks on Graphs for Learning Molecular Fingerprints paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the GraphSAGE model in the Inductive Representation Learning on Large Graphs paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the ChebyNet model in the Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the GAT model in the Graph Attention Networks paper on the Cora (3%) dataset? | Accuracy |
What metrics were used to measure the OGC model in the From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GCNII model in the Simple and Deep Graph Convolutional Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GRAND model in the Graph Random Neural Network for Semi-Supervised Learning on Graphs paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the CPF-ind-APPNP model in the Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the AIR-GCN model in the GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the H-GCN model in the Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the DAGNN (Ours) model in the Towards Deeper Graph Neural Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the G-APPNP model in the Pre-train and Learn: Preserve Global Information for Graph Neural Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the SuperGAT MX model in the How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the DSGCN model in the Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the LDS-GNN model in the Learning Discrete Structures for Graph Neural Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GraphMix model in the GraphMix: Improved Training of GNNs for Semi-Supervised Learning paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GraphMix (GCN) model in the GraphMix: Improved Training of GNNs for Semi-Supervised Learning paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GCN+GAugO model in the Data Augmentation for Graph Neural Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GGCM model in the From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the Snowball (linear) model in the Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GAT+PGN model in the The Split Matters: Flat Minima Methods for Improving the Performance of GNNs paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the Snowball (tanh) model in the Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the Truncated Krylov model in the Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GEM model in the Graph Entropy Minimization for Semi-supervised Node Classification paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GAT model in the Graph Attention Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the G3NN model in the A Flexible Generative Framework for Graph-based Semi-supervised Learning paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the SSP model in the Optimization of Graph Neural Networks with Natural Gradient Descent paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the CoLinkDist model in the Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the CoLinkDistMLP model in the Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the LinkDist model in the Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the LinkDistMLP model in the Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the AdaLanczosNet model in the LanczosNet: Multi-Scale Deep Graph Convolutional Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the DCNN model in the Diffusion-Convolutional Neural Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the LanczosNet model in the LanczosNet: Multi-Scale Deep Graph Convolutional Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the ChebyNet model in the Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GGNN model in the Gated Graph Sequence Neural Networks paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GCN-FP model in the Convolutional Networks on Graphs for Learning Molecular Fingerprints paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the GraphSAGE model in the Inductive Representation Learning on Large Graphs paper on the Cora with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the Dir-GNN model in the Edge Directionality Improves Learning on Heterophilic Graphs paper on the arXiv-year dataset? | Accuracy |
What metrics were used to measure the G^2-GraphSAGE model in the Gradient Gating for Deep Multi-Rate Learning on Graphs paper on the arXiv-year dataset? | Accuracy |
What metrics were used to measure the Dual-Net GNN model in the Feature Selection: Key to Enhance Node Classification with Graph Neural Networks paper on the arXiv-year dataset? | Accuracy |
What metrics were used to measure the OGNN model in the Uplifting Message Passing Neural Network with Graph Original Information paper on the arXiv-year dataset? | Accuracy |
What metrics were used to measure the LINKX model in the Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods paper on the arXiv-year dataset? | Accuracy |
What metrics were used to measure the LW-GCN model in the Label-Wise Graph Convolutional Network for Heterophilic Graphs paper on the arXiv-year dataset? | Accuracy |
What metrics were used to measure the GloGNN++ model in the Finding Global Homophily in Graph Neural Networks When Meeting Heterophily paper on the arXiv-year dataset? | Accuracy |
What metrics were used to measure the IIE-GNN model in the Enhancing Intra-class Information Extraction for Heterophilous Graphs: One Neural Architecture Search Approach paper on the arXiv-year dataset? | Accuracy |
What metrics were used to measure the DJ-GNN model in the Diffusion-Jump GNNs: Homophiliation via Learnable Metric Filters paper on the arXiv-year dataset? | Accuracy |
What metrics were used to measure the 2-HiGCN model in the Higher-order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes paper on the Actor dataset? | Accuracy |
What metrics were used to measure the IIE-GNN model in the Enhancing Intra-class Information Extraction for Heterophilous Graphs: One Neural Architecture Search Approach paper on the Actor dataset? | Accuracy |
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