Large language models (LLMs), such as ChatGPT and LLaMA, are creating significant
advancements in natural language processing, due to their strong text encoding/decoding …

Graph plays a significant role in representing and analyzing complex relationships in real-
world applications such as citation networks, social networks, and biological data. Recently …

Learning on Graphs has attracted immense attention due to its wide real-world applications.
The most popular pipeline for learning on graphs with textual node attributes primarily relies …

The emergence of large-scale pre-trained language models, such as ChatGPT, has
revolutionized various research fields in artificial intelligence. Transformers-based large …

Modeling customer shopping intentions is a crucial task for e-commerce, as it directly
impacts user experience and engagement. Thus, accurately understanding customer …

Graphs are a powerful tool for representing and analyzing complex relationships in real-
world applications such as social networks, recommender systems, and computational …

Emerging as fundamental building blocks for diverse artificial intelligence applications,
foundation models have achieved notable success across natural language processing and …

Representation learning on text-attributed graphs (TAGs) has become a critical research
problem in recent years. A typical example of a TAG is a paper citation graph, where the text …

In recent years, there have been remarkable advancements in node classification achieved
by Graph Neural Networks (GNNs). However, they necessitate abundant high-quality labels …

This paper studies Large Language Models (LLMs) augmented with structured data--
particularly graphs--a crucial data modality that remains underexplored in the LLM literature …