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Zhengtao Yu

4 papers hereh-index 7254 citations16 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.SI2
  • cs.CR1
  • cs.LG1
same name
  • Zhengtao Yu — 16 papers, h 2
  • Zhengtao Yu — 5 papers, h 6
  • Zhengtao Yu — 2 papers, h 1
  • Zhengtao Yu — 1 paper, h 1
  • Zhengtao Yu — 1 paper, h 3
  • Zhengtao Yu — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

works on
community detection 1dynamic networks 1large-scale graphs 1overlapping communities 1structural entropy 1

From the 1 of 4 linked papers with an AI index.

collaborators

4 papers

cs.SI2026

Comprehensive, Efficient Large-Scale Community Detection via Structural Entropy Game

Pu Li, Yantuan Xian, Hao Peng +4

The paper introduces CoDeSEG, a heuristic algorithm that detects non‑overlapping, overlapping, and dynamic communities in very large graphs by minimizing a two‑dimensional structur…

cs.CR2026

Activation-Guided Local Editing for Jailbreaking Attacks

Jiecong Wang, Haoran Li, Hao Peng +4

Jailbreaking is an essential adversarial technique for red-teaming these models to uncover and patch security flaws. However, existing jailbreak methods face significant drawbacks.…

cs.LG2025

Unsupervised Graph Clustering with Deep Structural Entropy

Jingyun Zhang, Hao Peng, Li Sun +3

Research on Graph Structure Learning (GSL) provides key insights for graph-based clustering, yet current methods like Graph Neural Networks (GNNs), Graph Attention Networks (GATs),…

cs.SI2025

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…

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