Hanghang Tong

About Hanghang Tong

Hanghang Tong, With an exceptional h-index of 66 and a recent h-index of 47 (since 2020), a distinguished researcher at University of Illinois at Urbana-Champaign, specializes in the field of Large Scale Data Mining, Graph Mining, Social Networks, Healthcare, Multimedia.

His recent articles reflect a diverse array of research interests and contributions to the field:

Bemap: Balanced message passing for fair graph neural network

Heterogeneous Contrastive Learning for Foundation Models and Beyond

Hierarchical Multi-Marginal Optimal Transport for Network Alignment

Sterling: Synergistic representation learning on bipartite graphs

Trustworthy Graph Neural Networks: Aspects, Methods, and Trends

Logic Query of Thoughts: Guiding Large Language Models to Answer Complex Logic Queries with Knowledge Graphs

Ginkgo-P: General Illustrations of Knowledge Graphs for Openness as a Platform

Soft Reasoning on Uncertain Knowledge Graphs

Hanghang Tong Information

University

Position

___

Citations(all)

78287

Citations(since 2020)

27962

Cited By

14043

hIndex(all)

66

hIndex(since 2020)

47

i10Index(all)

234

i10Index(since 2020)

188

Email

University Profile Page

Google Scholar

Hanghang Tong Skills & Research Interests

Large Scale Data Mining

Graph Mining

Social Networks

Healthcare

Multimedia

Top articles of Hanghang Tong

Bemap: Balanced message passing for fair graph neural network

2024/4/17

Heterogeneous Contrastive Learning for Foundation Models and Beyond

arXiv preprint arXiv:2404.00225

2024/3/30

Hierarchical Multi-Marginal Optimal Transport for Network Alignment

Proceedings of the AAAI Conference on Artificial Intelligence

2024/3/24

Sterling: Synergistic representation learning on bipartite graphs

Proceedings of the AAAI Conference on Artificial Intelligence

2024/3/24

Trustworthy Graph Neural Networks: Aspects, Methods, and Trends

Proceedings of the IEEE

2024/3/21

Logic Query of Thoughts: Guiding Large Language Models to Answer Complex Logic Queries with Knowledge Graphs

arXiv preprint arXiv:2404.04264

2024/3/17

Ginkgo-P: General Illustrations of Knowledge Graphs for Openness as a Platform

2024/3/4

Lihui Liu
Lihui Liu

H-Index: 4

Hanghang Tong
Hanghang Tong

H-Index: 43

Soft Reasoning on Uncertain Knowledge Graphs

arXiv preprint arXiv:2403.01508

2024/3/3

Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?

arXiv preprint arXiv:2402.18272

2024/2/28

On the Generalization Capability of Temporal Graph Learning Algorithms: Theoretical Insights and a Simpler Method

arXiv preprint arXiv:2402.16387

2024/2/26

differential PINO-CDE

MECHANICAL SYSTEMS AND SIGNAL PROCESSING

2024/2/15

Solving coupled differential equation groups using PINO-CDE

Mechanical Systems and Signal Processing

2024/2/15

From trainable negative depth to edge heterophily in graphs

Advances in Neural Information Processing Systems

2024/2/13

Reconciling Competing Sampling Strategies of Network Embedding

Advances in Neural Information Processing Systems

2024/2/13

ArieL: Adversarial Graph Contrastive Learning

ACM Transactions on Knowledge Discovery from Data

2024/2/12

Generalized few-shot node classification: toward an uncertainty-based solution

Knowledge and Information Systems (KAIS)

2023/10/1

Genius: Subteam Replacement with Clustering-based Graph Neural Networks

2024

Qinghai Zhou
Qinghai Zhou

H-Index: 2

Hanghang Tong
Hanghang Tong

H-Index: 43

Generate-on-Graph: Treat LLM as both Agent and KG in Incomplete Knowledge Graph Question Answering

arXiv preprint arXiv:2404.14741

2024/4/23

Neural Active Learning Beyond Bandits

arXiv preprint arXiv:2404.12522

2024/4/18

Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning

arXiv preprint arXiv:2305.12738

2023/5/22

See List of Professors in Hanghang Tong University(University of Illinois at Urbana-Champaign)

Co-Authors

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