15 citations · 32 across the 11 of their papers we have counts for
4 papers · 1 filter
Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation
Meihan Liu, Zhen Zhang, Jiachen Tang +3
Unsupervised Graph Domain Adaptation (UGDA) involves the transfer of knowledge from a label-rich source graph to an unlabeled target graph under domain discrepancies. Despite the p…
A Reflective LLM-based Agent to Guide Zero-shot Cryptocurrency Trading
Yuan Li, Bingqiao Luo, Qian Wang +3
The utilization of Large Language Models (LLMs) in financial trading has primarily been concentrated within the stock market, aiding in economic and financial decisions. Yet, the u…
Collaborate to Adapt: Source-Free Graph Domain Adaptation via Bi-directional Adaptation
Zhen Zhang, Meihan Liu, Anhui Wang +4
Unsupervised Graph Domain Adaptation (UGDA) has emerged as a practical solution to transfer knowledge from a label-rich source graph to a completely unlabelled target graph. Howeve…
BuffGraph: Enhancing Class-Imbalanced Node Classification via Buffer Nodes
Qian Wang, Zemin Liu, Zhen Zhang +1
Class imbalance in graph-structured data, where minor classes are significantly underrepresented, poses a critical challenge for Graph Neural Networks (GNNs). To address this chall…