45 citations · 56 across the 8 of their papers we have counts for
8 papers
Efficient Multi-modal Large Language Models via Visual Token Grouping
Minbin Huang, Runhui Huang, Han Shi +6
The development of Multi-modal Large Language Models (MLLMs) enhances Large Language Models (LLMs) with the ability to perceive data formats beyond text, significantly advancing a…
When LLM Meets Hypergraph: A Sociological Analysis on Personality via Online Social Networks
Zhiyao Shu, Xiangguo Sun, Hong Cheng
Individual personalities significantly influence our perceptions, decisions, and social interactions, which is particularly crucial for gaining insights into human behavior pattern…
ProG: A Graph Prompt Learning Benchmark
Chenyi Zi, Haihong Zhao, Xiangguo Sun +3
Artificial general intelligence on graphs has shown significant advancements across various applications, yet the traditional 'Pre-train & Fine-tune' paradigm faces inefficiencies…
Graph Condensation for Open-World Graph Learning
Xinyi Gao, Tong Chen, Wentao Zhang +3
The burgeoning volume of graph data presents significant computational challenges in training graph neural networks (GNNs), critically impeding their efficiency in various applicat…
All in One: Multi-Task Prompting for Graph Neural Networks (Extended Abstract)
Xiangguo Sun, Hong Cheng, Jia Li +2
This paper is an extended abstract of our original work published in KDD23, where we won the best research paper award (Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, and Jihong Guan. A…
Prompt Learning on Temporal Interaction Graphs
Xi Chen, Siwei Zhang, Yun Xiong +6
Temporal Interaction Graphs (TIGs) are widely utilized to represent real-world systems. To facilitate representation learning on TIGs, researchers have proposed a series of TIG mod…