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cs.LG2025★ 2 cited
FedSM: Robust Semantics-Guided Feature Mixup for Bias Reduction in Federated Learning with Long-Tail Data
Jingrui Zhang, Yimeng Xu, Shujie Li +5
Federated Learning (FL) enables collaborative model training across decentralized clients without sharing private data. However, FL suffers from biased global models due to non-IID…
cs.LG2025
Blend the Separated: Mixture of Synergistic Experts for Data-Scarcity Drug-Target Interaction Prediction
Xinlong Zhai, Chunchen Wang, Ruijia Wang +7
Drug-target interaction prediction (DTI) is essential in various applications including drug discovery and clinical application. There are two perspectives of input data widely use…
cs.LG2024
Exploring the Potential of Large Language Models for Heterophilic Graphs
Yuxia Wu, Shujie Li, Yuan Fang +1
Large language models (LLMs) have presented significant opportunities to enhance various machine learning applications, including graph neural networks (GNNs). By leveraging the va…