CAT: Can Trust be Predicted with Context-Awareness in Dynamic Heterogeneous Networks?

arXiv:2512.11352 · cs.LG · Submitted 2025-12-12 · Read on arXiv

cs.LG

Submitted: 2025-12-12

Updated: 2026-09-27

Code: https://github.com/Jieerbobo/CAT

Terminology

• Embeddings — 46× in this paper · explained in 2 episodes
• Robustness — 36× in this paper · explained in 5 episodes
• AUC — 25× in this paper · explained in 2 episodes
• GNNs — 25× in this paper · explained in 2 episodes
• Aggregation — 16× in this paper · explained in 1 episode
• Attention Mechanism — 16× in this paper · explained in 3 episodes
• Heterogeneous Graph — 11× in this paper · explained in 2 episodes
• Accuracy — 10× in this paper · explained in 1 episode
• Graph Construction — 7× in this paper · explained in 3 episodes
• Adversarial Attacks — 5× in this paper · explained in 1 episode
• Network and Distributed System Security — 4× in this paper
• Provenance — 4× in this paper · explained in 4 episodes
• Representation Learning — 4× in this paper · explained in 2 episodes
• Graph Neural Networks (GNNs) — 3× in this paper · explained in 7 episodes
• Semantic Understanding — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Adversarial Examples — 2× in this paper · explained in 2 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• IEEE Symposium on Security and Privacy — 2× in this paper
• Loss Function — 2× in this paper · explained in 2 episodes
• Mean Reciprocal Rank — 2× in this paper
• Over-smoothing — 2× in this paper · explained in 4 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Adversarial Robustness — 1× in this paper · explained in 3 episodes
• Adversarial Training — 1× in this paper · explained in 1 episode
• Area Under the ROC Curve — 1× in this paper
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Contextual Understanding — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Hypergraph — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Long Short-Term Memory — 1× in this paper
• Multi-Layer Perceptron — 1× in this paper
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Variational Graph Auto-Encoders
• Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness
• Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?

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