SOTAVerified

Community Detection

Community Detection is one of the fundamental problems in network analysis, where the goal is to find groups of nodes that are, in some sense, more similar to each other than to the other nodes.

Source: Randomized Spectral Clustering in Large-Scale Stochastic Block Models

Papers

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Showing 1–25 of 919 papers

TitleStatusHype
"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language ModelsCode4
Fast Think-on-Graph: Wider, Deeper and Faster Reasoning of Large Language Model on Knowledge GraphCode2
Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community RetrievalCode2
Modular Boundaries in Recurrent Neural NetworksCode2
Hypergraph Isomorphism ComputationCode2
Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Dataset Augmented by ChatGPTCode2
Speaker Diarization with Overlapping Community Detection Using Graph Attention Networks and Label Propagation AlgorithmCode1
Breaking the Batch Barrier (B3) of Contrastive Learning via Smart Batch MiningCode1
GeoAI-Enhanced Community Detection on Spatial Networks with Graph Deep LearningCode1
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning PerspectiveCode1
Explainable Global Wildfire Prediction Models using Graph Neural NetworksCode1
Hypergraph Contrastive Learning for Drug Trafficking Community DetectionCode1
Contrastive Deep Nonnegative Matrix Factorization for Community DetectionCode1
Random Walk on Multiple NetworksCode1
Boosting Multitask Learning on Graphs through Higher-Order Task AffinitiesCode1
ConGraT: Self-Supervised Contrastive Pretraining for Joint Graph and Text EmbeddingsCode1
Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community DetectionCode1
New Frontiers in Graph Autoencoders: Joint Community Detection and Link PredictionCode1
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research ChallengesCode1
Region2Vec: Community Detection on Spatial Networks Using Graph Embedding with Node Attributes and Spatial InteractionsCode1
Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unlabeled, unannotated pathology slidesCode1
Self-Supervised Learning of Object Parts for Semantic SegmentationCode1
Correlation-based feature selection to identify functional dynamics in proteinsCode1
FaceMap: Towards Unsupervised Face Clustering via Map EquationCode1
Modularity of the ABCD Random Graph Model with Community StructureCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GNNAccuracy-NE2—Unverified
2CommunityGANF1-score0.09—Unverified
3Ego-SplittingF1-score0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1EdMotNMI0.42—Unverified
2CDNMFNMI0.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CDNMFACC0.48—Unverified
#ModelMetricClaimedVerifiedStatus
1CommunityGANF1-Score0.15—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.56—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.69—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.68—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.71—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.86—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1CDNMFACC0.67—Unverified