74 citations · 82 across the 17 of their papers we have counts for
18 papers
Comprehensive, Efficient Large-Scale Community Detection via Structural Entropy Game
Pu Li, Yantuan Xian, Hao Peng +4
Community detection is a critical task in graph theory, social network analysis, and bioinformatics, where communities are defined as clusters of densely interconnected nodes. Howe…
Breaking Structural Isolation: Scalable Graph Clustering via Community-Aware Sampling and Structural Entropy
Jingyun Zhang, Hao Peng, Jianxin Li +2
Unsupervised graph clustering is a fundamental technique for uncovering underlying semantic patterns in large-scale networks. Although Graph Contrastive Learning has demonstrated p…
Effective and Unsupervised Social Event Detection and Evolution via RAG and Structural Entropy
Qitong Liu, Hao Peng, Zuchen Li +5
With the growing scale of social media, social event detection and evolution modeling have attracted increasing attention. Graph neural networks (GNNs) and transformer-based pre-tr…
Hyperbolic Continuous Structural Entropy for Hierarchical Clustering
Guangjie Zeng, Hao Peng, Angsheng Li +5
Hierarchical clustering is a fundamental machine-learning technique for grouping data points into dendrograms. However, existing hierarchical clustering methods encounter two prima…
SeSE: Black-Box Uncertainty Quantification for Large Language Models Based on Structural Information Theory
Xingtao Zhao, Hao Peng, Dingli Su +4
Reliable uncertainty quantification (UQ) is essential for deploying large language models (LLMs) in safety-critical scenarios, as it enables them to abstain from responding when un…
RoBCtrl: Attacking GNN-Based Social Bot Detectors via Reinforced Manipulation of Bots Control Interaction
Yingguang Yang, Xianghua Zeng, Qi Wu +5
Social networks have become a crucial source of real-time information for individuals. The influence of social bots within these platforms has garnered considerable attention from…
Community Detection in Large-Scale Complex Networks via Structural Entropy Game
Yantuan Xian, Pu Li, Hao Peng +3
Community detection is a critical task in graph theory, social network analysis, and bioinformatics, where communities are defined as clusters of densely interconnected nodes. Howe…
Hierarchical Superpixel Segmentation via Structural Information Theory
Minhui Xie, Hao Peng, Pu Li +5
Superpixel segmentation is a foundation for many higher-level computer vision tasks, such as image segmentation, object recognition, and scene understanding. Existing graph-based s…
SocialED: A Python Library for Social Event Detection
Kun Zhang, Xiaoyan Yu, Pu Li +2
SocialED is a comprehensive, open-source Python library designed to support social event detection (SED) tasks, integrating 19 detection algorithms and 14 diverse datasets. It prov…
Towards Effective, Efficient and Unsupervised Social Event Detection in the Hyperbolic Space
Xiaoyan Yu, Yifan Wei, Shuaishuai Zhou +5
The vast, complex, and dynamic nature of social message data has posed challenges to social event detection (SED). Despite considerable effort, these challenges persist, often resu…
Multi-View Incongruity Learning for Multimodal Sarcasm Detection
Diandian Guo, Cong Cao, Fangfang Yuan +5
Multimodal sarcasm detection (MSD) is essential for various downstream tasks. Existing MSD methods tend to rely on spurious correlations. These methods often mistakenly prioritize…
DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism
Xiaoyan Yu, Yifan Wei, Pu Li +5
Training social event detection models through federated learning (FedSED) aims to improve participants' performance on the task. However, existing federated learning paradigms are…
GC-Bench: An Open and Unified Benchmark for Graph Condensation
Qingyun Sun, Ziying Chen, Beining Yang +6
Graph condensation (GC) has recently garnered considerable attention due to its ability to reduce large-scale graph datasets while preserving their essential properties. The core c…
IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning
Jiawen Qin, Haonan Yuan, Qingyun Sun +8
Deep graph learning has gained grand popularity over the past years due to its versatility and success in representing graph data across a wide range of domains. However, the perva…
Multi-Relational Structural Entropy
Yuwei Cao, Hao Peng, Angsheng Li +3
Structural Entropy (SE) measures the structural information contained in a graph. Minimizing or maximizing SE helps to reveal or obscure the intrinsic structural patterns underlyin…
Unsupervised Social Bot Detection via Structural Information Theory
Hao Peng, Jingyun Zhang, Xiang Huang +4
Research on social bot detection plays a crucial role in maintaining the order and reliability of information dissemination while increasing trust in social interactions. The curre…
Relational Prompt-based Pre-trained Language Models for Social Event Detection
Pu Li, Xiaoyan Yu, Hao Peng +5
Social Event Detection (SED) aims to identify significant events from social streams, and has a wide application ranging from public opinion analysis to risk management. In recent…
Hierarchical and Incremental Structural Entropy Minimization for Unsupervised Social Event Detection
Yuwei Cao, Hao Peng, Zhengtao Yu +1
As a trending approach for social event detection, graph neural network (GNN)-based methods enable a fusion of natural language semantics and the complex social network structural…