5 papers
HiSem: Hierarchical Semantic Disentangling for Remote Sensing Image Change Captioning
Man Wang, Chenyang Liu, Wenjun Li +5
Remote sensing image change captioning (RSICC) aims to achieve high-level semantic understanding of genuine changes occurring between bi-temporal images. Despite notable progress,…
Multimodal-enhanced Federated Recommendation: A Group-wise Fusion Approach
Chunxu Zhang, Weipeng Zhang, Guodong Long +3
Federated Recommendation (FR) is a new learning paradigm to tackle the learn-to-rank problem in a privacy-preservation manner. How to integrate multi-modality features into federat…
When Noisy Labels Meet Class Imbalance on Graphs: A Graph Augmentation Method with LLM and Pseudo Label
Riting Xia, Rucong Wang, Yulin Liu +3
Class-imbalanced graph node classification is a practical yet underexplored research problem. Although recent studies have attempted to address this issue, they typically assume cl…
Distilling A Universal Expert from Clustered Federated Learning
Zeqi Leng, Chunxu Zhang, Guodong Long +2
Clustered Federated Learning (CFL) addresses the challenges posed by non-IID data by training multiple group- or cluster-specific expert models. However, existing methods often ove…
Incomplete Graph Learning: A Comprehensive Survey
Riting Xia, Huibo Liu, Anchen Li +4
Graph learning is a prevalent field that operates on ubiquitous graph data. Effective graph learning methods can extract valuable information from graphs. However, these methods ar…