prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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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 Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the MMA model in the Multi-Mask Aggregators for Graph Neural Networks paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the AdaGCN model in the AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
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 Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the PPNP model in the Predict then Propagate: Graph Neural Networks meet Personalized PageRank paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
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 Citeseer dataset? | Accuracy, Training Split, Validation |
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 Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the APPNP model in the Predict then Propagate: Graph Neural Networks meet Personalized PageRank paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the Cleora model in the Cleora: A Simple, Strong and Scalable Graph Embedding Scheme paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the PairE model in the Graph Representation Learning Beyond Node and Homophily paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
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 Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the LDS-GNN model in the Learning Discrete Structures for Graph Neural Networks paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
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 Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the DFNet-ATT model in the DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the G3NN model in the A Flexible Generative Framework for Graph-based Semi-supervised Learning paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the DNAConv model in the Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the TREE-G model in the TREE-G: Decision Trees Contesting Graph Neural Networks paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GResNet(LoopyNet) model in the GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GraphVAT model in the Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the SPF-GCN model in the Structure fusion based on graph convolutional networks for semi-supervised classification paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GResNet(GAT) model in the GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the SF-GCN model in the Structure fusion based on graph convolutional networks for semi-supervised classification paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GCN (PPR Diffusion) model in the Diffusion Improves Graph Learning paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the Graph U-Nets model in the Graph U-Nets paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GraphNAS model in the GraphNAS: Graph Neural Architecture Search with Reinforcement Learning paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the LGCN sub model in the Large-Scale Learnable Graph Convolutional Networks paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the hpGAT model in the hpGAT: High-order Proximity Informed Graph Attention Network paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GResNet(GCN) model in the GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the DifNet model in the Get Rid of Suspended Animation Problem: Deep Diffusive Neural Network on Graph Semi-Supervised Classification paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the SDRF model in the Understanding over-squashing and bottlenecks on graphs via curvature paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GAT model in the Graph Attention Networks paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the CT-Layer (PE) model in the DiffWire: Inductive Graph Rewiring via the Lovász Bound paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the N-GCN model in the N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GRACE model in the Deep Graph Contrastive Representation Learning paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
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 Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the MTGAE model in the Multi-Task Graph Autoencoders paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the DGI model in the Deep Graph Infomax paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GOCN model in the Robust Graph Data Learning via Latent Graph Convolutional Representation paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GLNN model in the Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GWNN model in the Graph Wavelet Neural Network paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the alpha-LoNGAE model in the Learning to Make Predictions on Graphs with Autoencoders paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the LoopyNet model in the GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the MixHop model in the MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the Graph-Bert model in the Graph-Bert: Only Attention is Needed for Learning Graph Representations paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GraphStar model in the Graph Star Net for Generalized Multi-Task Learning paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the Graphite model in the Graphite: Iterative Generative Modeling of Graphs paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GCN model in the Semi-Supervised Classification with Graph Convolutional Networks paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the APPNP model in the Fast Graph Representation Learning with PyTorch Geometric paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the ChebNet model in the Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GCN + AdaGraph (AG) model in the Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the GNN RH-U model in the Certifiable Robustness and Robust Training for Graph Convolutional Networks paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the CT-Layer model in the DiffWire: Inductive Graph Rewiring via the Lovász Bound paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the SNoRe model in the SNoRe: Scalable Unsupervised Learning of Symbolic Node Representations paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the Planetoid* model in the Revisiting Semi-Supervised Learning with Graph Embeddings paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the TGCL+ResNet model in the Deeper-GXX: Deepening Arbitrary GNNs paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the AttentionWalk model in the Watch Your Step: Learning Node Embeddings via Graph Attention paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the DANMF model in the Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection paper on the Citeseer dataset? | Accuracy, Training Split, Validation |
What metrics were used to measure the R-GraphSAGE (NS) model in the OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs paper on the MAG240M-LSC dataset? | Test Accuracy, Validation Accuracy |
What metrics were used to measure the GAT (NS) model in the OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs paper on the MAG240M-LSC dataset? | Test Accuracy, Validation Accuracy |
What metrics were used to measure the GraphSAGE (NS) model in the OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs paper on the MAG240M-LSC dataset? | Test Accuracy, Validation Accuracy |
What metrics were used to measure the SIGN model in the OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs paper on the MAG240M-LSC dataset? | Test Accuracy, Validation 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 CiteSeer 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 CiteSeer 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 CiteSeer with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the Graph-MLP + PGN model in the The Split Matters: Flat Minima Methods for Improving the Performance of GNNs paper on the CiteSeer with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the CPF-tra-APPNP model in the Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework paper on the CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the SSGC model in the Simple Spectral Graph Convolution paper on the CiteSeer with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the OKDEEM model in the Graph Entropy Minimization for Semi-supervised Node Classification paper on the CiteSeer 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 CiteSeer with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the SEGCN model in the Every Node Counts: Self-Ensembling Graph Convolutional Networks for Semi-Supervised Learning paper on the CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the IncepGCN+DropEdge model in the paper on the CiteSeer with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the EEM model in the Graph Entropy Minimization for Semi-supervised Node Classification paper on the CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer 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 CiteSeer with Public Split: fixed 20 nodes per class dataset? | Accuracy |
What metrics were used to measure the MPNN model in the Neural Message Passing for Quantum Chemistry paper on the CiteSeer 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 CiteSeer with Public Split: fixed 20 nodes per class dataset? | Accuracy |
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