5 citations · 6 across the 5 of their papers we have counts for
5 papers
Exploring Correlations of Self-Supervised Tasks for Graphs
Taoran Fang, Wei Zhou, Yifei Sun +3
Graph self-supervised learning has sparked a research surge in training informative representations without accessing any labeled data. However, our understanding of graph self-sup…
Can GNN be Good Adapter for LLMs?
Xuanwen Huang, Kaiqiao Han, Yang Yang +4
Recently, large language models (LLMs) have demonstrated superior capabilities in understanding and zero-shot learning on textual data, promising significant advances for many text…
GraphLLM: Boosting Graph Reasoning Ability of Large Language Model
Ziwei Chai, Tianjie Zhang, Liang Wu +4
The advancement of Large Language Models (LLMs) has remarkably pushed the boundaries towards artificial general intelligence (AGI), with their exceptional ability on understanding…
How to Generate Popular Post Headlines on Social Media?
Zhouxiang Fang, Min Yu, Zhendong Fu +4
Posts, as important containers of user-generated-content pieces on social media, are of tremendous social influence and commercial value. As an integral components of a post, the h…
Prompt-based Node Feature Extractor for Few-shot Learning on Text-Attributed Graphs
Xuanwen Huang, Kaiqiao Han, Dezheng Bao +4
Text-attributed Graphs (TAGs) are commonly found in the real world, such as social networks and citation networks, and consist of nodes represented by textual descriptions. Current…