26 citations · 33 across the 6 of their papers we have counts for
6 papers
SINCon: Mitigate LLM-Generated Malicious Message Injection Attack for Rumor Detection
Mingqing Zhang, Qiang Liu, Xiang Tao +2
In the era of rapidly evolving large language models (LLMs), state-of-the-art rumor detection systems, particularly those based on Message Propagation Trees (MPTs), which represent…
Bi-Level Graph Structure Learning for Next POI Recommendation
Liang Wang, Shu Wu, Qiang Liu +3
Next point-of-interest (POI) recommendation aims to predict a user's next destination based on sequential check-in history and a set of POI candidates. Graph neural networks (GNNs)…
Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection
Xiang Tao, Liang Wang, Qiang Liu +1
Due to the rapid spread of rumors on social media, rumor detection has become an extremely important challenge. Recently, numerous rumor detection models which utilize textual info…
Out-of-distribution Rumor Detection via Test-Time Adaptation
Xiang Tao, Mingqing Zhang, Qiang Liu +2
Due to the rapid spread of rumors on social media, rumor detection has become an extremely important challenge. Existing methods for rumor detection have achieved good performance,…
Rethinking Graph Masked Autoencoders through Alignment and Uniformity
Liang Wang, Xiang Tao, Qiang Liu +1
Self-supervised learning on graphs can be bifurcated into contrastive and generative methods. Contrastive methods, also known as graph contrastive learning (GCL), have dominated gr…
Can Large Language Models Detect Rumors on Social Media?
Qiang Liu, Xiang Tao, Junfei Wu +2
In this work, we investigate to use Large Language Models (LLMs) for rumor detection on social media. However, it is challenging for LLMs to reason over the entire propagation info…