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Shuzhi Gong
Observed name:
Gong, Shuzhi
Institution:
The University of Melbourne
Observed institutions:
The University of Melbourne,
Data61
ORCID:
0009-0007-9289-9015
Observed ORCID:
0009-0007-9289-9015
OpenAlex ID:
A5023747190
Fake News Detection through Graph-based Neural Networks: A Survey
2023
·
Shuzhi Gong
, Richard Sinnott
, et al.
·
Research Square
·
59
PDF
Fake News Detection Through Temporally Evolving User Interactions
2023
·
Shuzhi Gong
, Richard O. Sinnott
, et al.
·
Lecture notes in computer science
·
14
Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking
2026
·
Shuzhi Gong
, Richard Sinnott
, et al.
·
International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
·
8
Unseen Fake News Detection Through Casual Debiasing
2025
·
Shuzhi Gong
, Richard Sinnott
, et al.
·
International World Wide Web Conference (WWW)
·
6
PDF
Social Media Rumour Detection Through Graph Attention Networks
2021
·
Xinpeng Zhang
, Shuzhi Gong
, et al.
·
IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)
·
2
Why Prompt Optimization Works, and Why It Sometimes Doesn't: A Causal-Inspired Edit-Level Analysis
2026
·
Gong, Shuzhi
, Wen, Hechuan
·
arXiv (Cornell University)
·
1
PDF
Less is More: Unseen Domain Fake News Detection via Causal Propagation Substructures
2024
·
Gong, Shuzhi
, Sinnott, Richard O.
, et al.
·
arXiv (Cornell University)
·
1
PDF
Beneath the Scores: Rethinking Hallucination Evaluation for Video Understanding Models
2026
·
Gong, Shuzhi
, Sun, Fengze
, et al.
·
arXiv (Cornell University)
PDF
Graph-based Fake News Detection in the Era of Large Language Models: A Survey
2026
·
Gong, Shuzhi
, Nakov, Preslav
, et al.
·
HAL
Invariant Subgraphs for Cross-Domain Fake News Detection via Causal Disentanglement
2026
·
Shuzhi Gong
, Richard O. Sinnott
, et al.
·
Proceedings of the International AAAI Conference on Web and Social Media
Fake News Detection Through Graph-Based Neural Networks
2026
·
Gong, Shuzhi
·
Minerva Access (University of Melbourne)
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Works count:
11
Citation count:
91
H-index:
4
I10-index:
2
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