4 papers
FGATT: A Robust Framework for Wireless Data Imputation Using Fuzzy Graph Attention Networks and Transformer Encoders
Jinming Xing, Chang Xue, Dongwen Luo +1
Missing data is a pervasive challenge in wireless networks and many other domains, often compromising the performance of machine learning and deep learning models. To address this,…
Comparative Analysis of Pooling Mechanisms in LLMs: A Sentiment Analysis Perspective
Jinming Xing, Dongwen Luo, Chang Xue +1
Large Language Models (LLMs) have revolutionized natural language processing (NLP) by delivering state-of-the-art performance across a variety of tasks. Among these, Transformer-ba…
Enhancing Link Prediction with Fuzzy Graph Attention Networks and Dynamic Negative Sampling
Jinming Xing, Ruilin Xing, Chang Xue +1
Link prediction is crucial for understanding complex networks but traditional Graph Neural Networks (GNNs) often rely on random negative sampling, leading to suboptimal performance…
Multi-view Fuzzy Graph Attention Networks for Enhanced Graph Learning
Jinming Xing, Dongwen Luo, Qisen Cheng +2
Fuzzy Graph Attention Network (FGAT), which combines Fuzzy Rough Sets and Graph Attention Networks, has shown promise in tasks requiring robust graph-based learning. However, exist…