Community Detection

225 papers with code • 13 benchmarks • 11 datasets

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

Libraries

Use these libraries to find Community Detection models and implementations

"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models

verazuo/jailbreak_llms 7 Aug 2023

The misuse of large language models (LLMs) has garnered significant attention from the general public and LLM vendors.

160
07 Aug 2023

Random Walk on Multiple Networks

flyingdoog/rwm 4 Jul 2023

To take advantage of rich information in multiple networks and make better inferences on entities, in this study, we propose random walk on multiple networks, RWM.

12
04 Jul 2023

A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks

kvignesh1420/gnn_collapse NeurIPS 2023

We start with an empirical study that shows that a decrease in within-class variability is also prevalent in the node-wise classification setting, however, not to the extent observed in the instance-wise case.

4
04 Jul 2023

Boosting Multitask Learning on Graphs through Higher-Order Task Affinities

neu-statsml-research/boosting-multitask-learning-on-graphs 24 Jun 2023

Lastly, we provide a theoretical analysis to show that under a planted block model of tasks on graphs, our affinity scores can provably separate tasks into groups.

7
24 Jun 2023

Fast Maximum $k$-Plex Algorithms Parameterized by Small Degeneracy Gaps

joey001/kplex_degen_gap 23 Jun 2023

We define a novel parameter of the input instance, $g_k(G)$, the gap between the degeneracy bound and the size of the maximum $k$-plex in the given graph, and present an exact algorithm parameterized by this $g_k(G)$, which has a worst-case running time polynomial in the size of the input graph and exponential in $g_k(G)$.

2
23 Jun 2023

Learning the Right Layers: a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs

saraventurini/learning-the-right-layers-on-multilayer-graphs 31 May 2023

Clustering (or community detection) on multilayer graphs poses several additional complications with respect to standard graphs as different layers may be characterized by different structures and types of information.

2
31 May 2023

Matrix tri-factorization over the tropical semiring

ejmric/trifaststmf 11 May 2023

We show that triFastSTMF performs similarly to Fast-NMTF in terms of approximation and prediction performance when fitted on the whole network.

0
11 May 2023

Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Dataset Augmented by ChatGPT

jwzhanggy/Graph_Toolformer Preprint 2023

Inspired by the latest ChatGPT and Toolformer models, we propose the Graph-ToolFormer (Graph Reasoning oriented Toolformer) framework to teach LLMs themselves with prompts augmented by ChatGPT to use external graph reasoning API tools.

212
10 Apr 2023

Genetic Analysis of Prostate Cancer with Computer Science Methods

zcablii/master_cancer_project 28 Mar 2023

Metastatic prostate cancer is one of the most common cancers in men.

1
28 Mar 2023

Effective Hierarchical Information Threading Using Network Community Detection

hitt08/HINT European Conference on Information Retrieval 2023

With the tremendous growth in the volume of information produced online every day (e. g. news articles), there is a need for automatic methods to identify related information about events as the events evolve over time (i. e., information threads).

0
17 Mar 2023