Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras. - Jun Yu; Yutong Dai 002; Xiaokang Liu; Jin Huang; Yishan Shen; Ke Zhang; Rong Zhou; Eashan Adhikarla; Wenxuan Ye; Yixin Liu 002; Zhaoming Kong; Kai Zhang 039; et al. (CoRR, 2024)

Evaluating site-of-care-related racial disparities in kidney graft failure using a novel federated learning framework. - Jiayi Tong; Yishan Shen; Alice Xu; Xing He 003; Chongliang Luo; Mackenzie J. Edmondson; Dazheng Zhang; Yiwen Lu; Chao Yan 004; Ruowang Li; Lianne Siegel; Lichao Sun 001; et al. (J. Am. Medical Informatics Assoc., 2024)

Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation. - Yuyang Ye 002; Zhi Zheng 008; Yishan Shen; Tianshu Wang 004; Hengruo Zhang; Peijun Zhu; Runlong Yu; Kai Zhang 001; Hui Xiong 001 (AAAI, 2025)

SAFER: A Calibrated Risk-Aware Multimodal Recommendation Model for Dynamic Treatment Regimes. - Yishan Shen; Yuyang Ye 002; Hui Xiong 001; Yong Chen (CoRR, 2025)