167 citations · 397 across the 33 of their papers we have counts for
8 papers · 1 filter
AGMixup: Adaptive Graph Mixup for Semi-supervised Node Classification
Weigang Lu, Ziyu Guan, Wei Zhao +4
Mixup is a data augmentation technique that enhances model generalization by interpolating between data points using a mixing ratio in the image domain. Recently, the concept o…
Dynamic Evidence Decoupling for Trusted Multi-view Learning
Ying Liu, Lihong Liu, Cai Xu +3
Multi-view learning methods often focus on improving decision accuracy, while neglecting the decision uncertainty, limiting their suitability for safety-critical applications. To m…
Aligning Multiple Knowledge Graphs in a Single Pass
Yaming Yang, Zhe Wang, Ziyu Guan +5
Entity alignment (EA) is to identify equivalent entities across different knowledge graphs (KGs), which can help fuse these KGs into a more comprehensive one. Previous EA methods m…
Enhancing Criminal Case Matching through Diverse Legal Factors
Jie Zhao, Ziyu Guan, Wei Zhao +1
Criminal case matching endeavors to determine the relevance between different criminal cases. Conventional methods predict the relevance solely based on instance-level semantic fea…
SC2: Towards Enhancing Content Preservation and Style Consistency in Long Text Style Transfer
Jie Zhao, Ziyu Guan, Cai Xu +2
Text style transfer (TST) aims to vary the style polarity of text while preserving the semantic content. Although recent advancements have demonstrated remarkable progress in short…
AdaGMLP: AdaBoosting GNN-to-MLP Knowledge Distillation
Weigang Lu, Ziyu Guan, Wei Zhao +1
Graph Neural Networks (GNNs) have revolutionized graph-based machine learning, but their heavy computational demands pose challenges for latency-sensitive edge devices in practical…
TruthSR: Trustworthy Sequential Recommender Systems via User-generated Multimodal Content
Meng Yan, Haibin Huang, Ying Liu +5
Sequential recommender systems explore users' preferences and behavioral patterns from their historically generated data. Recently, researchers aim to improve sequential recommenda…
Trusted Multi-view Learning under Noisy Supervision
Yilin Zhang, Cai Xu, Han Jiang +4
Multi-view learning methods often focus on improving decision accuracy while neglecting the decision uncertainty, which significantly restricts their applications in safety-critica…