activity
20202026
most citedA Macro- and Micro-Hierarchical Transfer Learning Framework for Cross-Domain Fake News Detection

7 citations · 15 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

RES-MR: Risk-Aware Reasoning for Explainable and Safe Medication Recommendation

Cong Wang, Jin Li, Shoujin Wang +3

Medication recommendations seek to deliver personalized drug combinations based on patients' clinical information, where ensuring transparent decision-making and personalized safet…

cs.SI2025★ 7 cited

A Macro- and Micro-Hierarchical Transfer Learning Framework for Cross-Domain Fake News Detection

Xuankai Yang, Yan Wang, Xiuzhen Zhang +3

Cross-domain fake news detection aims to mitigate domain shift and improve detection performance by transferring knowledge across domains. Existing approaches transfer knowledge ba…

cs.IR2024

Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation

Li Wang, Shoujin Wang, Quangui Zhang +2

Cross-domain recommendation (CDR) aims to address the data-sparsity problem by transferring knowledge across domains. Existing CDR methods generally assume that the user-item inter…

cs.CV2024★ 5 cited

RU-AI: A Large Multimodal Dataset for Machine-Generated Content Detection

Liting Huang, Zhihao Zhang, Yiran Zhang +2

The recent generative AI models' capability of creating realistic and human-like content is significantly transforming the ways in which people communicate, create and work. The ma…

eess.IV2020★ 3 cited

Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Images for Segmentation

Shuchao Pang, Anan Du, Mehmet A. Orgun +5

Automatic tumor segmentation is a crucial step in medical image analysis for computer-aided diagnosis. Although the existing methods based on convolutional neural networks (CNNs) h…