Multimodal graph neural network with large language models for node and link prediction

IntroductionGraph data representation is widely applicable in numerous real-world scenarios, and recent advances in graph neural networks (GNNs) have enabled effective modeling of complex associations in graph-structured data. However, GNNs are often constrained by the over-smoothing problem, which reduces their ability to distinguish node representations. In contrast, large language models (LLMs) are effective at capturing semantic contexts from textual data but are inherently limited in encodi