1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CL2024
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…
cs.LG2023
Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns
Yifei Sun, Qi Zhu, Yang Yang +4
Recently, the paradigm of pre-training and fine-tuning graph neural networks has been intensively studied and applied in a wide range of graph mining tasks. Its success is generall…
cs.SI2023★ 1 cited
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…