Papers Community Detection
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Learning and Clustering on Temporal Graphs: Principles, Primitives, and Pooling
This work focuses on the problem of learning on temporal graphs, with particular emphasis on the task of clustering: obtaining coarse-grained representations by aggregating information from nodes, edges, and temporal dyn…
Community DetectionGraph LearningAccelerating Dynamic Graph Clustering on GPU Architectures with cuGraph
This work addresses community detection in temporal networks through GPU-accelerated extensions of spectral clustering and modularity-based algorithms originally designed for static graphs. Built on the NVIDIA RAPIDS eco…
Community DetectionGraph ClusteringRegularized Optimization on Grassmann Manifold: Theory, Algorithm and Applications
Spectral methods are among the most widely used techniques for community detection, clustering, and graph learning. Their performance, however, critically depends on the accurate estimation of the underlying spectral sub…
Community DetectionGraph LearningTransient State Reorganization and Cell Differentiation in the Developmental Dynamics of Growing Neural Cellular Automata
Growing Neural Cellular Automata (GNCA) develop complex morphologies from a single seed cell through shared local rules, yet the internal dynamics of this process remain poorly understood. To investigate how GNCA grows, …
Community DetectionRAGU: A Multi-Step GraphRAG Engine with a Compact Domain-Adapted LLM
Graph retrieval-augmented generation (GraphRAG) enhances large language models with structured knowledge, yet existing systems construct knowledge graphs in a single extraction pass, producing noisy entities and brittle …
Community DetectionKnowledge GraphsConceptual Networks for Cross-Linguistic Idiomatic Expressions:A Feature-Based Graph Approach
We present an interpretable network-based framework for representing idiomatic and figurative meaning across eight typologically diverse languages, totaling 160 conventional expressions, the large majority of which are i…
Cross-Lingual TransferCommunity DetectionCurvature-Guided Sheaf Diffusion for Unsupervised Community Detection on Heterophilic Graphs
Detecting communities in heterophilic graphs -- where connected nodes often belong to different classes -- is hard for unsupervised methods: classical modularity and spectral methods are feature agnostic, while deep grap…
Community DetectionIntrinsic 4D Gaussian Segmentation from Scene Cues
Dynamic 4D Gaussian Splatting reconstructs deforming scenes with high fidelity and is increasingly adopted as a representation for dynamic 3D scenes. Putting such a scene to use, for editing, manipulation or motion analy…
Community DetectionAI Supply Chain Galaxy: 3D Visual Analytics for License Compliance
The rapid proliferation of machine learning model reuse has transformed the AI ecosystem into a highly interconnected supply chain. Traditional compliance tools and static reports struggle to navigate these massive, mult…
Community DetectionGraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs
Graph analysis underlies many applications whose answers cannot be looked up in a single record or retrieved along a path: laundering rings, drug repurposing, user preference, and scientific theme are all inferred from a…
Node ClassificationCommunity DetectionOutlier DetectionAlcmean's: Unsupervised community detection using local Laplacian, automatic detection of the number of centers
Community detection is a fundamental problem in the analysis of complex networks. It has applications across social, biological, and financial domains. Traditional algorithms such as Louvain, LPA, and modularity optimiza…
Representation LearningCommunity DetectionFlexible Online Representation Learning Based on Similarity Matching
Sparse high-dimensional representations are conducive to uncovering nontrivial structures in unsupervised exploration of data. Such a representation can deal with the dense connectivity in graphs relevant to community de…
Representation LearningCommunity DetectionWhen Parallelism Pays Off: Cohesion-Aware Task Partitioning for Multi-Agent Coding
Multi-agent Large Language Model (LLM) systems offer a way to decompose complex tasks, such as coding, through parallelization and context isolation. However, adding agents in practice introduces inter-agent communicatio…
Community Detectiongraph partitioningHidden in Plain Tokens: Simply Robust, Gradient-Free Watermark for Synthetic Audio
As policy catches up with the capabilities of generative AI, watermarking is central to content provenance efforts. Inference-time watermarks for autoregressive models are unfit for continuous modalities due to discretiz…
Representation LearningCommunity DetectionST-SimDiff: Balancing Spatiotemporal Similarity and Difference for Efficient Video Understanding with MLLMs
Multimodal Large Language Models (MLLMs) face significant computational overhead when processing long videos due to the massive number of visual tokens required. To improve efficiency, existing methods primarily reduce r…
Community DetectionDynamic Hypergraph Representation Learning for Multivariate Time Series without Prior Knowledge
Hypergraphs have the capacity to capture higher-dimensional relationships among entities across various domains, making them a subject of growing interest within the research community for understanding the structure and…
Representation LearningCommunity DetectionGraph Neural Networks for Community Detection in Graph Signal Analysis
Community detection is a central problem in graph analysis, with applications ranging from network science to graph signal processing. In recent years, Graph Neural Networks (GNNs) have emerged as effective tools for lea…
Community DetectionPrism: Structural Symmetry Scanning via Duality-Constrained Laplacian Projection
We introduce \textbf{Prism}, a framework for structural symmetry diagnosis in complex networks. Given a graph Laplacian $L$ and a duality operator $P$ (a symmetric involution), Prism computes the \emph{duality defect} $δ…
Community DetectionConditional Entropy of Heat Diffusion on Temporal Networks
Diffusion-based information-theoretic approaches provide new theoretical and practical tools to study complex networks. So far, they have not been generalized to temporal networks. In this work, we show that common entro…
Community DetectionAutomatic Construction of a Legal Citation Graph from 100 Million Ukrainian Court Decisions: Large-Scale Extraction, Topological Analysis, and Ontology-Driven Clustering
Half a billion citation edges extracted from 100.7 million Ukrainian court decisions reveal that judicial citation structure encodes legal domain boundaries without supervision and predicts future legislative importance …
Community Detection