1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025
xTime: Extreme Event Prediction with Hierarchical Knowledge Distillation and Expert Fusion
Quan Li, Wenchao Yu, Suhang Wang +4
Extreme events frequently occur in real-world time series and often carry significant practical implications. In domains such as climate and healthcare, these events, such as flood…
cs.LG2024
Enhancing Graph Neural Networks with Limited Labeled Data by Actively Distilling Knowledge from Large Language Models
Quan Li, Tianxiang Zhao, Lingwei Chen +2
Graphs are pervasive in the real-world, such as social network analysis, bioinformatics, and knowledge graphs. Graph neural networks (GNNs) have great ability in node classificatio…
cs.CL2024★ 1 cited
Hierarchical Knowledge Distillation on Text Graph for Data-limited Attribute Inference
Quan Li, Shixiong Jing, Lingwei Chen
The popularization of social media increases user engagements and generates a large amount of user-oriented data. Among them, text data (e.g., tweets, blogs) significantly attracts…