Revisiting Consistency Regularization for Deep Partial Label Learning. - Dong-Dong Wu; Deng-Bao Wang; Min-Ling Zhang (ICML, 2022)

Robust Representation Learning for Unreliable Partial Label Learning. - Yu Shi; Dong-Dong Wu; Xin Geng 001; Min-Ling Zhang (CoRR, 2023)

Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning. - Dong-Dong Wu; Deng-Bao Wang; Min-Ling Zhang (AAAI, 2024)

Efficient Model Stealing Defense with Noise Transition Matrix. - Dong-Dong Wu; Chilin Fu; Weichang Wu; Wenwen Xia; Xiaolu Zhang; Jun Zhou 011; Min-Ling Zhang (CVPR, 2024)

Realistic Evaluation of Deep Partial-Label Learning Algorithms. - Wei Wang 373; Dong-Dong Wu; Jindong Wang 001; Gang Niu 001; Min-Ling Zhang; Masashi Sugiyama (ICLR, 2025)

A Frustratingly Simple Yet Highly Effective Attack Baseline: Over 90% Success Rate Against the Strong Black-box Models of GPT-4.5/4o/o1. - Zhaoyi Li; Xiaohan Zhao; Dong-Dong Wu; Jiacheng Cui; Zhiqiang Shen (CoRR, 2025)

Computer-Aided Application in Medicine and Biomedicine. - Qi-Ming Liao; Wahab Hussain; Zhong-Xia Liao; Sarfraz Hussain; Zhi-Liang Jiang; Yong-Hao Zhu; Huang-Yin Luo; Xin-Ying Ji; Hong-Wei Wen; Dong-Dong Wu (Int. J. Comput. Intell. Syst., 2025)