Search Results for author:
Found 4 papers, 1 papers with code
Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection
The model learns semantic evolvement information of events by capturing local semantic changes and global semantic evolvement information through specific graph autoencoder and reconstruction strategies.
Out-of-distribution Rumor Detection via Test-Time Adaptation
This method models the propagation of news in the form of a propagation graph, and builds propagation graph test-time adaptation framework, enhancing the model's adaptability and robustness when facing OOD problems.
Rethinking Graph Masked Autoencoders through Alignment and Uniformity
Based on our theoretical analysis, we further identify the limitations of the GraphMAE from the perspectives of alignment and uniformity, which have been considered as two key properties of high-quality representations in GCL.
Can Large Language Models Detect Rumors on Social Media?
In this work, we investigate to use Large Language Models (LLMs) for rumor detection on social media.
