prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the GloGNN++ model in the Finding Global Homophily in Graph Neural Networks When Meeting Heterophily paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the ACMII-GCN+ model in the Revisiting Heterophily For Graph Neural Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the Ordered GNN model in the Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the UniG-Encoder model in the UniG-Encoder: A Universal Feature Encoder for Graph and Hypergraph Node Classification paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the GCNH model in the GCNH: A Simple Method For Representation Learning On Heterophilous Graphs paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the UDGNN (GCN) model in the Universal Deep GNNs: Rethinking Residual Connection in GNNs from a Path Decomposition Perspective for Preventing the Over-smoothing paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the ACMII-GCN model in the Revisiting Heterophily For Graph Neural Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the NLMLP model in the Non-Local Graph Neural Networks paper on the Wisconsin 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 Wisconsin dataset? | Accuracy |
What metrics were used to measure the WRGAT model in the Beyond Low-frequency Information in Graph Convolutional Networks paper on the Wisconsin 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 Wisconsin dataset? | Accuracy |
What metrics were used to measure the GGCN model in the Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the HLP Concat model in the Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the CNMPGNN model in the CN-Motifs Perceptive Graph Neural Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the ACM-SGC-1 model in the Revisiting Heterophily For Graph Neural Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the ACM-SGC-2 model in the Revisiting Heterophily For Graph Neural Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the FDGATII model in the FDGATII : Fast Dynamic Graph Attention with Initial Residual and Identity Mapping paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the TDGNN-w model in the Tree Decomposed Graph Neural Network paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the H2GCN DHGR model in the Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the H2GCN-1 model in the Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the Graph ESN model in the Beyond Homophily with Graph Echo State Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the H2GCN-2 model in the Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the GPRGCN model in the Adaptive Universal Generalized PageRank Graph Neural Network paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the UGT model in the Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the GCNII model in the Simple and Deep Graph Convolutional Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the FAGCN model in the Beyond Low-frequency Information in Graph Convolutional Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the CT-Layer model in the DiffWire: Inductive Graph Rewiring via the Lovász Bound paper on the Wisconsin dataset? | 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 Wisconsin 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 Wisconsin dataset? | Accuracy |
What metrics were used to measure the CT-Layer (PE) model in the DiffWire: Inductive Graph Rewiring via the Lovász Bound paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the Geom-GCN-P model in the Geom-GCN: Geometric Graph Convolutional Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the NLGCN model in the Non-Local Graph Neural Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the Geom-GCN-I model in the Geom-GCN: Geometric Graph Convolutional Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the NLGAT model in the Non-Local Graph Neural Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the Geom-GCN-S model in the Geom-GCN: Geometric Graph Convolutional Networks paper on the Wisconsin dataset? | Accuracy |
What metrics were used to measure the SDRF model in the Understanding over-squashing and bottlenecks on graphs via curvature paper on the Wisconsin 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 pokec dataset? | Accuracy |
What metrics were used to measure the OptBasisGNN model in the Graph Neural Networks with Learnable and Optimal Polynomial Bases paper on the pokec 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 pokec 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 pokec dataset? | Accuracy |
What metrics were used to measure the SDSS-APPNP model in the Multi-task Self-distillation for Graph-based Semi-Supervised Learning paper on the Pubmed: fixed 20 node per class dataset? | Accuracy |
What metrics were used to measure the ACMII-GCN++ model in the Revisiting Heterophily For Graph Neural Networks paper on the Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (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 Squirrel (60%/20%/20% random splits) dataset? | 1:1 Accuracy |
What metrics were used to measure the 3ference model in the Inferring from References with Differences for Semi-Supervised Node Classification on Graphs paper on the Coauthor CS 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 Coauthor CS 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 Coauthor CS 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 Coauthor CS 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 Coauthor CS dataset? | 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 Coauthor CS dataset? | Accuracy |
What metrics were used to measure the GraphSAGE model in the Half-Hop: A graph upsampling approach for slowing down message passing paper on the Coauthor CS dataset? | Accuracy |
What metrics were used to measure the Exphormer model in the Exphormer: Sparse Transformers for Graphs paper on the Coauthor CS dataset? | Accuracy |
What metrics were used to measure the GCN-LPA model in the Unifying Graph Convolutional Neural Networks and Label Propagation paper on the Coauthor CS dataset? | 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 Coauthor CS dataset? | Accuracy |
What metrics were used to measure the GCN model in the Half-Hop: A graph upsampling approach for slowing down message passing paper on the Coauthor CS dataset? | Accuracy |
What metrics were used to measure the GCN (PPR Diffusion) model in the Diffusion Improves Graph Learning paper on the Coauthor CS dataset? | Accuracy |
What metrics were used to measure the DAGNN (Ours) model in the Towards Deeper Graph Neural Networks paper on the Coauthor CS dataset? | Accuracy |
What metrics were used to measure the SIGN model in the SIGN: Scalable Inception Graph Neural Networks paper on the Coauthor CS 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 Coauthor CS dataset? | Accuracy |
What metrics were used to measure the Graph InfoClust (GIC) model in the Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning paper on the Coauthor CS dataset? | Accuracy |
What metrics were used to measure the SNoRe model in the SNoRe: Scalable Unsupervised Learning of Symbolic Node Representations paper on the Coauthor CS dataset? | Accuracy |
What metrics were used to measure the GREAD-F model in the GREAD: Graph Neural Reaction-Diffusion Networks paper on the Texas (48%/32%/20% fixed splits) dataset? | Accuracy, 1:1 Accuracy |
What metrics were used to measure the GREAD-BS model in the GREAD: Graph Neural Reaction-Diffusion Networks paper on the Texas (48%/32%/20% fixed splits) dataset? | Accuracy, 1:1 Accuracy |
What metrics were used to measure the GESN model in the Addressing Heterophily in Node Classification with Graph Echo State Networks paper on the Texas (48%/32%/20% fixed splits) dataset? | Accuracy, 1:1 Accuracy |
What metrics were used to measure the ACM-Snowball-3 model in the Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? paper on the Pubmed dataset? | Accuracy, Training Split, F1, Validation |
What metrics were used to measure the ACMII-Snowball-3 model in the Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? paper on the Pubmed dataset? | Accuracy, Training Split, F1, Validation |
What metrics were used to measure the ACM-Snowball-2 model in the Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? paper on the Pubmed dataset? | Accuracy, Training Split, F1, Validation |
What metrics were used to measure the ACM-GCN model in the Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? paper on the Pubmed dataset? | Accuracy, Training Split, F1, Validation |
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