1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 1 cited
AnyTaskTune: Advanced Domain-Specific Solutions through Task-Fine-Tuning
Jiaxi Cui, Wentao Zhang, Jing Tang +6
The pervasive deployment of Large Language Models-LLMs in various sectors often neglects the nuanced requirements of individuals and small organizations, who benefit more from mode…
cs.LG2024
FedGTA: Topology-aware Averaging for Federated Graph Learning
Xunkai Li, Zhengyu Wu, Wentao Zhang +3
Federated Graph Learning (FGL) is a distributed machine learning paradigm that enables collaborative training on large-scale subgraphs across multiple local systems. Existing FGL s…
cs.LG2024
AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity
Xunkai Li, Zhengyu Wu, Wentao Zhang +3
Recently, Federated Graph Learning (FGL) has attracted significant attention as a distributed framework based on graph neural networks, primarily due to its capability to break dat…