3 citations · 5 across the 6 of their papers we have counts for
6 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…
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…
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…
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…