2 papers
cs.LG2026
A Closer Look at the Application of Causal Inference in Graph Representation Learning
Hang Gao, Kunyu Li, Huang Hong +2
Modeling causal relationships in graph representation learning remains a fundamental challenge. Existing approaches often draw on theories and methods from causal inference to iden…
cs.AI2025
GraphInstruct: Empowering Large Language Models with Graph Understanding and Reasoning Capability
Zihan Luo, Xiran Song, Hong Huang +5
Improving the general capabilities of large language models (LLMs) is an active research topic. As a common data structure in many real-world domains, understanding graph data is a…