30 citations · 44 across the 16 of their papers we have counts for
8 papers · 1 filter
Transferable Hypergraph Attack via Injecting Nodes into Pivotal Hyperedges
Meixia He, Peican Zhu, Le Cheng +3
Recent studies have demonstrated that hypergraph neural networks (HGNNs) are susceptible to adversarial attacks. However, existing methods rely on the specific information mechanis…
Transferable and Undefendable Point Cloud Attacks via Medial Axis Transform
Keke Tang, Yuze Gao, Weilong Peng +3
Studying adversarial attacks on point clouds is essential for evaluating and improving the robustness of 3D deep learning models. However, most existing attack methods are develope…
SEER: Semantic Enhancement and Emotional Reasoning Network for Multimodal Fake News Detection
Peican Zhu, Yubo Jing, Le Cheng +4
Previous studies on multimodal fake news detection mainly focus on the alignment and integration of cross-modal features, as well as the application of text-image consistency. Howe…
KEN: Knowledge Augmentation and Emotion Guidance Network for Multimodal Fake News Detection
Peican Zhu, Yubo Jing, Le Cheng +2
In recent years, the rampant spread of misinformation on social media has made accurate detection of multimodal fake news a critical research focus. However, previous research has…
Cage-Based Deformation for Transferable and Undefendable Point Cloud Attack
Keke Tang, Ziyong Du, Weilong Peng +4
Adversarial attacks on point clouds often impose strict geometric constraints to preserve plausibility; however, such constraints inherently limit transferability and undefendabili…
SourceDetMamba: A Graph-aware State Space Model for Source Detection in Sequential Hypergraphs
Le Cheng, Peican Zhu, Yangming Guo +3
Source detection on graphs has demonstrated high efficacy in identifying rumor origins. Despite advances in machine learning-based methods, many fail to capture intrinsic dynamics…
HyperDet: Source Detection in Hypergraphs via Interactive Relationship Construction and Feature-rich Attention Fusion
Le Cheng, Peican Zhu, Yangming Guo +3
Hypergraphs offer superior modeling capabilities for social networks, particularly in capturing group phenomena that extend beyond pairwise interactions in rumor propagation. Exist…
EOOD: Entropy-based Out-of-distribution Detection
Guide Yang, Chao Hou, Weilong Peng +4
Deep neural networks (DNNs) often exhibit overconfidence when encountering out-of-distribution (OOD) samples, posing significant challenges for deployment. Since DNNs are trained o…