Ming-Kun Xie

52 papers A* 18A 1Journal 32Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Are Multimodal Large Language Models Good Annotators for Image Tagging?
CoRR
Ming-Kun Xie, Jiahao Xiao, Zhiqiang Kou, Zhongnian Li, Gang Niu, Masashi Sugiyama
2026 J jnl
Positive-Unlabeled Reinforcement Learning Distillation for On-Premise Small Models.
CoRR
Zhiqiang Kou, Junyang Chen, Xin-Qiang Cai, Xiaobo Xia, Ming-Kun Xie, Dong-Dong Wu, Biao Liu, Yuheng Jia, Xin Geng, Masashi Sugiyama, Tat-Seng Chua
2026 J jnl
Tail-Aware Reconstruction of Incomplete Label Distributions With Low-Rank and Sparse Modeling.
IEEE Trans. Circuits Syst. Video Technol.
Zhiqiang Kou, Haoyuan Xuan, Jingyu Zhu, Hailin Wang, Ming-Kun Xie, Changwei Wang, Jing Wang, Yuheng Jia, Xin Geng
2025 J jnl
A Unified Open Adapter for Open-World Noisy Label Learning: Data-Centric and Learning-Based Insights.
IEEE Trans. Circuits Syst. Video Technol.
Chen-Chen Zong, Penghui Yang, Ming-Kun Xie, Sheng-Jun Huang
2025 A* conf
Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning.
CVPR
Lei-Lei Ma, Shuo Xu, Ming-Kun Xie, Lei Wang, Dengdi Sun, Haifeng Zhao
2025 J jnl
Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning.
CoRR
Leilei Ma, Shuo Xu, Ming-Kun Xie, Lei Wang, Dengdi Sun, Haifeng Zhao
2025 J jnl
Interactive Large Language Models for Reliable Answering under Incomplete Context.
Trans. Mach. Learn. Res.
Jing-Cheng Pang, Heng-Bo Fan, Pengyuan Wang, Jiahao Xiao, Nan Tang, Si-Hang Yang, Chengxing Jia, Ming-Kun Xie, Xiang Chen, Sheng-Jun Huang, Yang Yu
2025 A* conf
Label Distribution Learning with Biased Annotations Assisted by Multi-Label Learning.
IJCAI
Zhiqiang Kou, Si Qin, Hailin Wang, Jing Wang, Ming-Kun Xie, Shuo Chen, Yuheng Jia, Tongliang Liu, Masashi Sugiyama, Xin Geng
2025 J jnl
Label Distribution Learning with Biased Annotations by Learning Multi-Label Representation.
CoRR
Zhiqiang Kou, Si Qin, Hailin Wang, Ming-Kun Xie, Shuo Chen, Yuheng Jia, Tongliang Liu, Masashi Sugiyama, Xin Geng
2025 A* conf
Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL.
ICML
Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang
2025 J jnl
Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL.
CoRR
Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang
2025 J jnl
Representation-Level Counterfactual Calibration for Debiased Zero-Shot Recognition.
CoRR
Pei Peng, Ming-Kun Xie, Hang Hao, Tong Jin, Sheng-Jun Huang
2025 J jnl
Rethinking Consistent Multi-Label Classification under Inexact Supervision.
CoRR
Wei Wang, Tianhao Ma, Ming-Kun Xie, Gang Niu, Masashi Sugiyama
2025 J jnl
Rethinking Toxicity Evaluation in Large Language Models: A Multi-Label Perspective.
CoRR
Zhiqiang Kou, Junyang Chen, Xin-Qiang Cai, Ming-Kun Xie, Biao Liu, Changwei Wang, Lei Feng, Yuheng Jia, Gang Niu, Masashi Sugiyama, Xin Geng
2025 J jnl
What Makes "Good" Distractors for Object Hallucination Evaluation in Large Vision-Language Models?
CoRR
Ming-Kun Xie, Jiahao Xiao, Gang Niu, Lei Feng, Zhiqiang Kou, Min-Ling Zhang, Masashi Sugiyama
2024 J jnl
A Deep Model for Partial Multi-label Image Classification with Curriculum-based Disambiguation.
Mach. Intell. Res.
Feng Sun, Ming-Kun Xie, Sheng-Jun Huang
2024 A* conf
Asymmetric Beta Loss for Evidence-Based Safe Semi-Supervised Multi-Label Learning.
KDD
Hao-Zhe Liu, Ming-Kun Xie, Chen-Chen Zong, Sheng-Jun Huang
2024 J jnl
Context-Based Semantic-Aware Alignment for Semi-Supervised Multi-Label Learning.
CoRR
Heng-Bo Fan, Ming-Kun Xie, Jiahao Xiao, Sheng-Jun Huang
2024 A* conf
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training.
ICML
Ming-Kun Xie, Jiahao Xiao, Pei Peng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
2024 J jnl
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training.
CoRR
Ming-Kun Xie, Jiahao Xiao, Pei Peng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
2024 A conf
Dirichlet-Based Coarse-to-Fine Example Selection For Open-Set Annotation.
ICME
Ye-Wen Wang, Chen-Chen Zong, Ming-Kun Xie, Sheng-Jun Huang
2024 J jnl
Dirichlet-Based Coarse-to-Fine Example Selection For Open-Set Annotation.
CoRR
Ye-Wen Wang, Chen-Chen Zong, Ming-Kun Xie, Sheng-Jun Huang
2024 A* conf
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels.
AAAI
Chen-Chen Zong, Ye-Wen Wang, Ming-Kun Xie, Sheng-Jun Huang
2024 J jnl
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels.
CoRR
Chen-Chen Zong, Ye-Wen Wang, Ming-Kun Xie, Sheng-Jun Huang
2024 J jnl
Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-Supervised Multi-Label Learning.
CoRR
Jiahao Xiao, Ming-Kun Xie, Heng-Bo Fan, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
2024 — conf
Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-supervised Multi-label Learning.
ECCV (52)
Jiahao Xiao, Ming-Kun Xie, Heng-Bo Fan, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
2024 A* conf
Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL.
NeurIPS
Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang
2024 J jnl
Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL.
CoRR
Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang
2024 J jnl
Robust AUC maximization for classification with pairwise confidence comparisons.
Frontiers Comput. Sci.
Haochen Shi, Ming-Kun Xie, Shengjun Huang
2024 J jnl
Sequential Cooperative Distillation for Imbalanced Multi-Task Learning.
J. Comput. Sci. Technol.
Quan Feng, Jia-Yu Yao, Ming-Kun Xie, Sheng-Jun Huang, Songcan Chen
2024 J jnl
UNM: A Universal Approach for Noisy Multi-Label Learning.
IEEE Trans. Knowl. Data Eng.
Jia-Yao Chen, Shao-Yuan Li, Sheng-Jun Huang, Songcan Chen, Lei Wang, Ming-Kun Xie
2024 A* conf
Unlocking the Power of Open Set: A New Perspective for Open-Set Noisy Label Learning.
AAAI
Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shao-Yuan Li, Sheng-Jun Huang, Songcan Chen
2023 J jnl
CCMN: A General Framework for Learning With Class-Conditional Multi-Label Noise.
IEEE Trans. Pattern Anal. Mach. Intell.
Ming-Kun Xie, Sheng-Jun Huang
2023 J jnl
Class-Distribution-Aware Pseudo Labeling for Semi-Supervised Multi-Label Learning.
CoRR
Ming-Kun Xie, Jiahao Xiao, Hao-Zhe Liu, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
2023 A* conf
Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning.
NeurIPS
Ming-Kun Xie, Jiahao Xiao, Hao-Zhe Liu, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
2023 A* conf
Multi-Label Knowledge Distillation.
ICCV
Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
2023 J jnl
Multi-Label Knowledge Distillation.
CoRR
Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang
2023 J jnl
Unlocking the Power of Open Set : A New Perspective for Open-set Noisy Label Learning.
CoRR
Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shengjun Huang, Songcan Chen, Shaoyuan Li
2022 J jnl
A Deep Model for Partial Multi-Label Image Classification with Curriculum Based Disambiguation.
CoRR
Feng Sun, Ming-Kun Xie, Sheng-Jun Huang
2022 A* conf
Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels.
NeurIPS
Ming-Kun Xie, Jiahao Xiao, Sheng-Jun Huang
2022 J jnl
Meta Objective Guided Disambiguation for Partial Label Learning.
CoRR
Bo-Shi Zou, Ming-Kun Xie, Sheng-Jun Huang
2022 J jnl
Noise-Robust Bidirectional Learning with Dynamic Sample Reweighting.
CoRR
Chen-Chen Zong, Zheng-Tao Cao, Hong-Tao Guo, Yun Du, Ming-Kun Xie, Shao-Yuan Li, Sheng-Jun Huang
2022 J jnl
Partial Multi-Label Learning With Noisy Label Identification.
IEEE Trans. Pattern Anal. Mach. Intell.
Ming-Kun Xie, Sheng-Jun Huang
2021 J jnl
CCMN: A General Framework for Learning with Class-Conditional Multi-Label Noise.
CoRR
Ming-Kun Xie, Sheng-Jun Huang
2021 A* conf
Multi-Label Learning with Pairwise Relevance Ordering.
NeurIPS
Ming-Kun Xie, Sheng-Jun Huang
2021 A* conf
Partial Multi-Label Learning with Meta Disambiguation.
KDD
Ming-Kun Xie, Feng Sun, Sheng-Jun Huang
2020 A* conf
Partial Multi-Label Learning with Noisy Label Identification.
AAAI
Ming-Kun Xie, Sheng-Jun Huang
2020 A* conf
Semi-Supervised Partial Multi-Label Learning.
ICDM
Ming-Kun Xie, Sheng-Jun Huang
2019 A* conf
Learning Class-Conditional GANs with Active Sampling.
KDD
Ming-Kun Xie, Sheng-Jun Huang
2018 A* conf
Active Feature Acquisition with Supervised Matrix Completion.
KDD
Sheng-Jun Huang, Miao Xu, Ming-Kun Xie, Masashi Sugiyama, Gang Niu, Songcan Chen
2018 J jnl
Active Feature Acquisition with Supervised Matrix Completion.
CoRR
Sheng-Jun Huang, Miao Xu, Ming-Kun Xie, Masashi Sugiyama, Gang Niu, Songcan Chen
2018 A* conf
Partial Multi-Label Learning.
AAAI
Ming-Kun Xie, Sheng-Jun Huang