Graph Neural Networks Need Cluster-Normalize-Activate Modules | Paper Citation Record

Observation 05b6efff-137b-43e3-a26b-667a18c4423b · outbound

This paper cites On the Bottleneck of Graph Neural Networks and its Practical Implications.

Graph Neural Networks Need Cluster-Normalize-Activate Modules On the Bottleneck of Graph Neural Networks and its Practical Implications

Reference 1

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This paper cites A survey on modern trainable activation functions.

Graph Neural Networks Need Cluster-Normalize-Activate Modules A survey on modern trainable activation functions

Reference 2

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Graph Neural Networks Need Cluster-Normalize-Activate Modules Unresolved cited work

Reference 3

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This paper cites Relational inductive biases, deep learning, and graph networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Relational inductive biases, deep learning, and graph networks

Reference 4

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This paper cites Diffusion-Jump GNNs: Homophiliation via Learnable Metric Filters.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Diffusion-Jump GNNs: Homophiliation via Learnable Metric Filters

Reference 5

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This paper cites Stability of k- Means Clustering.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Stability of k- Means Clustering

Reference 6

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Graph Neural Networks Need Cluster-Normalize-Activate Modules Unresolved cited work

Reference 7

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Observation 37092e1c-4a9e-4888-86f6-6245a0ad74e1 · outbound

This paper cites Learnable Extended Activation Function for Deep Neural Networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Learnable Extended Activation Function for Deep Neural Networks

Reference 8

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Observation 8d41980b-64ca-4933-b8dc-a3990bb07087 · outbound

This paper cites Deep Gaussian Embedding of Graphs : Unsupervised Inductive Learning via Ranking.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Deep Gaussian Embedding of Graphs : Unsupervised Inductive Learning via Ranking

Reference 9

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Observation 303c9e82-1f27-4918-bd92-deac70cb700f · outbound

This paper cites Borgwardt, Cheng Soon Ong, Stefan Schönauer, S.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Borgwardt, Cheng Soon Ong, Stefan Schönauer, S

Reference 10

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This paper cites Rational neural networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Rational neural networks

Reference 11

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Observation fa4596ba-ae53-428c-86bc-cf882b122cf7 · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 12

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Observation 44ca6d69-c4ec-4d84-aaaf-18e0d50b33d3 · outbound

This paper cites GraphNorm : A Principled Approach to Accelerating Graph Neural Network Training.

Graph Neural Networks Need Cluster-Normalize-Activate Modules GraphNorm : A Principled Approach to Accelerating Graph Neural Network Training

Reference 13

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Observation 42c6ba91-9fe2-47b3-b72d-d0bdf51da38b · outbound

This paper cites Renormalized Graph Neural Networks , June 2023.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Renormalized Graph Neural Networks , June 2023

Reference 14

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Observation 5412672b-3dc5-4816-8015-6416291e6d4a · outbound

This paper cites Learning graph normalization for graph neural networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Learning graph normalization for graph neural networks

Reference 15

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Observation 405b0e96-6144-43b3-9957-da2d6e537eae · outbound

This paper cites Cluster- GCN : An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Cluster- GCN : An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

Reference 16

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Observation 84ae78ac-a0b1-4182-9ed7-6776feb1231a · outbound

This paper cites Lopez de Compadre, Gargi Debnath, Alan J.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Lopez de Compadre, Gargi Debnath, Alan J

Reference 17

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Observation 9b2f97bd-519b-43b1-a262-260c643decfd · outbound

This paper cites Adaptive Rational Activations to Boost Deep Reinforcement Learning.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Adaptive Rational Activations to Boost Deep Reinforcement Learning

Reference 18

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Observation 47c3d9ba-995b-4e9b-9da2-1a72ba34476a · outbound

This paper cites SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning.

Graph Neural Networks Need Cluster-Normalize-Activate Modules SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning

Reference 19

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This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Fast Graph Representation Learning with PyTorch Geometric

Reference 20

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Observation 79c7ba85-f531-4f96-8d88-3b6a95272a60 · outbound

This paper cites Schoenholz, Patrick F.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Schoenholz, Patrick F

Reference 21

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Graph Neural Networks Need Cluster-Normalize-Activate Modules Unresolved cited work

Reference 22

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Observation 1334bfcd-41b4-4ed4-b8b9-16e499a291e7 · outbound

This paper cites Inductive Representation Learning on Large Graphs.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Inductive Representation Learning on Large Graphs

Reference 23

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This paper cites Harnessing Explanations : LLM -to- LM Interpreter for Enhanced Text - Attributed Graph Representation Learning.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Harnessing Explanations : LLM -to- LM Interpreter for Enhanced Text - Attributed Graph Representation Learning

Reference 24

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Observation 5f9e3611-2d27-4a1d-8649-dfe99254e80e · outbound

This paper cites Mitigating Degree Biases in Message Passing Mechanism by Utilizing Community Structures.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Mitigating Degree Biases in Message Passing Mechanism by Utilizing Community Structures

Reference 25

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This paper cites Open Graph Benchmark : Datasets for Machine Learning on Graphs.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Open Graph Benchmark : Datasets for Machine Learning on Graphs

Reference 26

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This paper cites Normalization Techniques in Training DNNs : Methodology , Analysis and Application.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Normalization Techniques in Training DNNs : Methodology , Analysis and Application

Reference 27

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This paper cites Higher-order Graph Convolutional Network with Flower - Petals Laplacians on Simplicial Complexes.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Higher-order Graph Convolutional Network with Flower - Petals Laplacians on Simplicial Complexes

Reference 28

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This paper cites Batch normalization: accelerating deep network training by reducing internal covariate shift.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Batch normalization: accelerating deep network training by reducing internal covariate shift

Reference 29

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This paper cites Optimization of Graph Neural Networks with Natural Gradient Descent.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Optimization of Graph Neural Networks with Natural Gradient Descent

Reference 30

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This paper cites Graph neural network for traffic forecasting: A survey.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Graph neural network for traffic forecasting: A survey

Reference 31

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This paper cites Reducing Oversmoothing in Graph Neural Networks by Changing the Activation Function.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Reducing Oversmoothing in Graph Neural Networks by Changing the Activation Function

Reference 32

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This paper cites On the power of graph neural networks and the role of the activation function, May 2024.

Graph Neural Networks Need Cluster-Normalize-Activate Modules On the power of graph neural networks and the role of the activation function, May 2024

Reference 33

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This paper cites Kipf and Max Welling.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Kipf and Max Welling

Reference 34

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This paper cites Mathematical Expressiveness of Graph Neural Networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Mathematical Expressiveness of Graph Neural Networks

Reference 35

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Observation 00b52efc-a946-4e65-ac6e-00245dbdfbf3 · outbound

This paper cites Lin, Allan Pinkus, and Shimon Schocken.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Lin, Allan Pinkus, and Shimon Schocken

Reference 36

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This paper cites Training Graph Neural Networks with 1000 Layers.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Training Graph Neural Networks with 1000 Layers

Reference 37

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Observation 52174277-0e74-492a-8818-7cb067969564 · outbound

This paper cites Deeper Insights Into Graph Convolutional Networks for Semi - Supervised Learning.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Deeper Insights Into Graph Convolutional Networks for Semi - Supervised Learning

Reference 38

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Observation 028e1aed-faa0-4f2a-b1b1-51cb54a6b8f8 · outbound

This paper cites Revisiting Heterophily For Graph Neural Networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Revisiting Heterophily For Graph Neural Networks

Reference 39

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This paper cites Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages

Reference 40

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This paper cites MacQueen.

Graph Neural Networks Need Cluster-Normalize-Activate Modules MacQueen

Reference 41

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Observation 4e33a99e-fb07-4a7c-86a9-10345b0b9100 · outbound

This paper cites Introduction to Information Retrieval.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Introduction to Information Retrieval

Reference 42

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Observation ee52b7bd-ddd8-4137-ab6d-7ac8609f646b · outbound

This paper cites Automating the Construction of Internet Portals with Machine Learning.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Automating the Construction of Internet Portals with Machine Learning

Reference 43

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This paper cites Padé Activation Units : End -to-end Learning of Flexible Activation Functions in Deep Networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Padé Activation Units : End -to-end Learning of Flexible Activation Functions in Deep Networks

Reference 44

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Observation e2e0346c-f8af-4e35-9539-f395ce46f676 · outbound

This paper cites Very Fast EM - Based Mixture Model Clustering Using Multiresolution Kd - Trees.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Very Fast EM - Based Mixture Model Clustering Using Multiresolution Kd - Trees

Reference 45

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This paper cites TUDataset : A collection of benchmark datasets for learning with graphs.

Graph Neural Networks Need Cluster-Normalize-Activate Modules TUDataset : A collection of benchmark datasets for learning with graphs

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:52:07.776241Z

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Observation 52997836-d353-4446-af77-0b10896dc367 · outbound

This paper cites Predicting basin stability of power grids using graph neural networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Predicting basin stability of power grids using graph neural networks

Reference 47

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This paper cites Revisiting over-smoothing and over-squashing using ollivier-ricci curvature.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Revisiting over-smoothing and over-squashing using ollivier-ricci curvature

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:52:07.765048Z

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This paper cites Revisiting Graph Neural Networks: All We Have is Low-Pass Filters.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Revisiting Graph Neural Networks: All We Have is Low-Pass Filters

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T21:52:06.870386Z

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This paper cites Geom- GCN : Geometric Graph Convolutional Networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Geom- GCN : Geometric Graph Convolutional Networks

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:52:07.753850Z

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Observation 461a3cae-e980-4b49-aa38-df87ae8355b6 · outbound

This paper cites Edge Directionality Improves Learning on Heterophilic Graphs.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Edge Directionality Improves Learning on Heterophilic Graphs

Reference 51

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This paper cites Multi- Scale attributed node embedding.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Multi- Scale attributed node embedding

Reference 52

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This paper cites Graph- Coupled Oscillator Networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Graph- Coupled Oscillator Networks

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:52:07.742630Z

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Observation 9dd77b13-90f7-4eac-abee-4926e1e73be1 · outbound

This paper cites A Survey on Oversmoothing in Graph Neural Networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules A Survey on Oversmoothing in Graph Neural Networks

Reference 54

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Observation 32c8a9ec-5693-4c40-8a03-e6a44fe4e16a · outbound

This paper cites Konstantin Rusch, Benjamin Paul Chamberlain, Michael W.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Konstantin Rusch, Benjamin Paul Chamberlain, Michael W

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:52:07.730930Z

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Observation f5dfcd72-6628-4314-bbb1-9ac2ba97417b · outbound

This paper cites The Graph Neural Network Model.

Graph Neural Networks Need Cluster-Normalize-Activate Modules The Graph Neural Network Model

Reference 56

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Graph Neural Networks Need Cluster-Normalize-Activate Modules Collective Classification in Network Data

Reference 57

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This paper cites Pitfalls of Graph Neural Network Evaluation.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Pitfalls of Graph Neural Network Evaluation

Reference 58

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Graph Neural Networks Need Cluster-Normalize-Activate Modules Unresolved cited work

Reference 59

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This paper cites Masked Label Prediction : Unified Message Passing Model for Semi - Supervised Classification.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Masked Label Prediction : Unified Message Passing Model for Semi - Supervised Classification

Reference 60

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This paper cites Exphormer: Sparse Transformers for Graphs.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Exphormer: Sparse Transformers for Graphs

Reference 61

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Graph Neural Networks Need Cluster-Normalize-Activate Modules ArnetMiner : extraction and mining of academic social networks

Reference 62

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Graph Neural Networks Need Cluster-Normalize-Activate Modules Neural Networks and Rational Functions

Reference 63

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This paper cites Bronstein.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Bronstein

Reference 64

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This paper cites ERA : Enhanced Rational Activations.

Graph Neural Networks Need Cluster-Normalize-Activate Modules ERA : Enhanced Rational Activations

Reference 65

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This paper cites Attention is All you Need.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Attention is All you Need

Reference 66

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This paper cites Graph Attention Networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Graph Attention Networks

Reference 67

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This paper cites A survey of graph neural networks in various learning paradigms: methods, applications, and challenges.

Graph Neural Networks Need Cluster-Normalize-Activate Modules A survey of graph neural networks in various learning paradigms: methods, applications, and challenges

Reference 68

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This paper cites Graph Neural Networks for Molecules.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Graph Neural Networks for Molecules

Reference 69

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Graph Neural Networks Need Cluster-Normalize-Activate Modules Simplifying Graph Convolutional Networks

Reference 70

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This paper cites Link Prediction Based on Graph Neural Networks.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Link Prediction Based on Graph Neural Networks

Reference 71

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This paper cites PairNorm : Tackling Oversmoothing in GNNs.

Graph Neural Networks Need Cluster-Normalize-Activate Modules PairNorm : Tackling Oversmoothing in GNNs

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:52:07.585387Z

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This paper cites Graph neural networks: A review of methods and applications.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Graph neural networks: A review of methods and applications

Reference 73

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This paper cites Towards deeper graph neural networks with differentiable group normalization.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Towards deeper graph neural networks with differentiable group normalization

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:52:07.573777Z

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Observation 0dfdd7a2-a02e-4ae2-ac6d-9e30da30c4e8 · outbound

This paper cites Deep Graph Contrastive Representation Learning , 2020.

Graph Neural Networks Need Cluster-Normalize-Activate Modules Deep Graph Contrastive Representation Learning , 2020

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:52:07.560883Z

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