5 papers
Conformal Path Reasoning: Trustworthy Knowledge Graph Question Answering via Path-Level Calibration
Shuhang Lin, Chuhao Zhou, Xiao Lin +5
Knowledge Graph Question Answering (KGQA) offers grounded, interpretable reasoning, but existing methods often fail to provide reliable coverage guarantees over retrieved answers.…
MoEMeta: Mixture-of-Experts Meta Learning for Few-Shot Relational Learning
Han Wu, Jie Yin
Few-shot knowledge graph relational learning seeks to perform reasoning over relations given only a limited number of training examples. While existing approaches largely adopt a m…
Meta-Semantics Augmented Few-Shot Relational Learning
Han Wu, Jie Yin
Few-shot relational learning on knowledge graph (KGs) aims to perform reasoning over relations with only a few training examples. While current methods have focused primarily on le…
Unbiased Online Curvature Approximation for Regularized Graph Continual Learning
Jie Yin, Ke Sun, Han Wu
Graph continual learning (GCL) aims to learn from a continuous sequence of graph-based tasks. Regularization methods are vital for preventing catastrophic forgetting in GCL, partic…
Multi-Granular Attention based Heterogeneous Hypergraph Neural Network
Hong Jin, Kaicheng Zhou, Jie Yin +2
Heterogeneous graph neural networks (HeteGNNs) have demonstrated strong abilities to learn node representations by effectively extracting complex structural and semantic informatio…