Learning from Stochastic Labels. - Meng Wei 006; Zhongnian Li; Yong Zhou 003; Qiaoyu Guo; Xinzheng Xu (CoRR, 2023)

Class-imbalanced complementary-label learning via weighted loss. - Meng Wei 006; Yong Zhou 003; Zhongnian Li; Xinzheng Xu (Neural Networks, 2023)

Prompt Expending for Single Positive Multi-Label Learning with Global Unannotated Categories. - Zhongnian Li; Peng Ying; Meng Wei 006; Tongfeng Sun; Xinzheng Xu (ICMR, 2024)

Learning from Reduced Labels for Long-Tailed Data. - Meng Wei 006; Zhongnian Li; Yong Zhou 003; Xinzheng Xu (ICMR, 2024)

Learning from Concealed Labels. - Zhongnian Li; Meng Wei 006; Peng Ying; Tongfeng Sun; Xinzheng Xu (ACM Multimedia, 2024)

Determined Multi-Label Learning via Similarity-Based Prompt. - Meng Wei 006; Zhongnian Li; Peng Ying; Yong Zhou 003; Xinzheng Xu (CoRR, 2024)

Learning from True-False Labels via Multi-modal Prompt Retrieving. - Zhongnian Li; Jinghao Xu; Peng Ying; Meng Wei 006; Tongfeng Sun; Xinzheng Xu (CoRR, 2024)

CoA: Chain-of-Action for Generative Semantic Labels. - Meng Wei 006; Zhongnian Li; Peng Ying; Xinzheng Xu (CoRR, 2024)

ESA: Example Sieve Approach for Multi-Positive and Unlabeled Learning. - Zhongnian Li; Meng Wei 006; Peng Ying; Xinzheng Xu (WSDM, 2025)