4 papers
SE-GCL: An Event-Based Simple and Effective Graph Contrastive Learning for Text Representation
Tao Meng, Wei Ai, Jianbin Li +3
Text representation learning is significant as the cornerstone of natural language processing. In recent years, graph contrastive learning (GCL) has been widely used in text repres…
Contrastive Multi-graph Learning with Neighbor Hierarchical Sifting for Semi-supervised Text Classification
Wei Ai, Jianbin Li, Ze Wang +4
Graph contrastive learning has been successfully applied in text classification due to its remarkable ability for self-supervised node representation learning. However, explicit gr…
SEG:Seeds-Enhanced Iterative Refinement Graph Neural Network for Entity Alignment
Wei Ai, Yinghui Gao, Jianbin Li +4
Entity alignment is crucial for merging knowledge across knowledge graphs, as it matches entities with identical semantics. The standard method matches these entities based on thei…
Graph Contrastive Learning via Cluster-refined Negative Sampling for Semi-supervised Text Classification
Wei Ai, Jianbin Li, Ze Wang +4
Graph contrastive learning (GCL) has been widely applied to text classification tasks due to its ability to generate self-supervised signals from unlabeled data, thus facilitating…