Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Graph machine learning in the era of large language models (llms)
Graphs play an important role in representing complex relationships in various domains like
social networks, knowledge graphs, and molecular discovery. With the advent of deep …
social networks, knowledge graphs, and molecular discovery. With the advent of deep …
Generalized graph prompt: Toward a unification of pre-training and downstream tasks on graphs
Graphs can model complex relationships between objects, enabling a myriad of Web
applications such as online page/article classification and social recommendation. While …
applications such as online page/article classification and social recommendation. While …
[HTML][HTML] A Survey of Information Dissemination Model, Datasets, and Insight
Information dissemination refers to how information spreads among users on social
networks. With the widespread application of mobile communication and internet …
networks. With the widespread application of mobile communication and internet …
Grass: learning spatial–temporal properties from chainlike cascade data for microscopic diffusion prediction
Information diffusion prediction captures diffusion dynamics of online messages in social
networks. Thus, it is the basis of many essential tasks such as popularity prediction and viral …
networks. Thus, it is the basis of many essential tasks such as popularity prediction and viral …
Retrieval-augmented hypergraph for multimodal social media popularity prediction
Accurately predicting the popularity of multimodal user-generated content (UGC) is
fundamental for many real-world applications such as online advertising and …
fundamental for many real-world applications such as online advertising and …
Counterfactual data augmentation with denoising diffusion for graph anomaly detection
A critical aspect of graph neural networks (GNNs) is to enhance the node representations by
aggregating node neighborhood information. However, when detecting anomalies, the …
aggregating node neighborhood information. However, when detecting anomalies, the …
Transformer-enhanced Hawkes process with decoupling training for information cascade prediction
The ability to model the information diffusion process and predict its size is crucial to
understanding information propagation mechanism and is useful for many applications such …
understanding information propagation mechanism and is useful for many applications such …
Measuring and classifying IP usage scenarios: a continuous neural trees approach
Understanding user behavior via IP addresses is a crucial measure towards numerous
pragmatic IP-based applications, including online content delivery, fraud prevention …
pragmatic IP-based applications, including online content delivery, fraud prevention …
A teacher-free graph knowledge distillation framework with dual self-distillation
Recent years have witnessed great success in handling graph-related tasks with Graph
Neural Networks (GNNs). Despite their great academic success, Multi-Layer Perceptrons …
Neural Networks (GNNs). Despite their great academic success, Multi-Layer Perceptrons …
PGSL: A probabilistic graph diffusion model for source localization
Source localization, as a reverse problem of the graph diffusion, bears paramount
significance for a multitude of applications, such as tracking social rumors, detecting …
significance for a multitude of applications, such as tracking social rumors, detecting …