Ming-Kun Xie

According to our database, Ming-Kun Xie authored at least 36 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Representation-Level Counterfactual Calibration for Debiased Zero-Shot Recognition.

Pei Peng, Ming-Kun Xie, Hang Hao, Tong Jin, Sheng-Jun Huang

CoRR, October, 2025

Rethinking Toxicity Evaluation in Large Language Models: A Multi-Label Perspective.

Zhiqiang Kou, Junyang Chen, Xin-Qiang Cai, Ming-Kun Xie, Biao Liu, Changwei Wang, Lei Feng, Yuheng Jia, Gang Niu, Masashi Sugiyama, Xin Geng

CoRR, October, 2025

Rethinking Consistent Multi-Label Classification under Inexact Supervision.

Wei Wang, Tianhao Ma, Ming-Kun Xie, Gang Niu, Masashi Sugiyama

CoRR, October, 2025

A Unified Open Adapter for Open-World Noisy Label Learning: Data-Centric and Learning-Based Insights.

Chen-Chen Zong, Penghui Yang, Ming-Kun Xie, Sheng-Jun Huang

IEEE Trans. Circuits Syst. Video Technol., August, 2025

What Makes "Good" Distractors for Object Hallucination Evaluation in Large Vision-Language Models?

Ming-Kun Xie, Jiahao Xiao, Gang Niu, Lei Feng, Zhiqiang Kou, Min-Ling Zhang, Masashi Sugiyama

CoRR, August, 2025

Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL.

Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang

CoRR, May, 2025

Label Distribution Learning with Biased Annotations by Learning Multi-Label Representation.

Zhiqiang Kou, Si Qin, Hailin Wang, Ming-Kun Xie, Shuo Chen, Yuheng Jia, Tongliang Liu, Masashi Sugiyama, Xin Geng

CoRR, February, 2025

Interactive Large Language Models for Reliable Answering under Incomplete Context.

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

Trans. Mach. Learn. Res., 2025

Label Distribution Learning with Biased Annotations Assisted by Multi-Label Learning.

Zhiqiang Kou, Si Qin, Hailin Wang, Jing Wang, Ming-Kun Xie, Shuo Chen, Yuheng Jia, Tongliang Liu, Masashi Sugiyama, Xin Geng

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning.

Lei-Lei Ma, Shuo Xu, Ming-Kun Xie, Lei Wang, Dengdi Sun, Haifeng Zhao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

UNM: A Universal Approach for Noisy Multi-Label Learning.

Jia-Yao Chen, Shao-Yuan Li, Sheng-Jun Huang, Songcan Chen, Lei Wang, Ming-Kun Xie

IEEE Trans. Knowl. Data Eng., September, 2024

Sequential Cooperative Distillation for Imbalanced Multi-Task Learning.

Quan Feng, Jia-Yu Yao, Ming-Kun Xie, Sheng-Jun Huang, Songcan Chen

J. Comput. Sci. Technol., September, 2024

A Deep Model for Partial Multi-label Image Classification with Curriculum-based Disambiguation.

Feng Sun, Ming-Kun Xie, Sheng-Jun Huang

Mach. Intell. Res., August, 2024

Robust AUC maximization for classification with pairwise confidence comparisons.

Haochen Shi, Ming-Kun Xie, Shengjun Huang

Frontiers Comput. Sci., August, 2024

Context-Based Semantic-Aware Alignment for Semi-Supervised Multi-Label Learning.

Heng-Bo Fan, Ming-Kun Xie, Jiahao Xiao, Sheng-Jun Huang

CoRR, 2024

Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL.

Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-Jun Huang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Asymmetric Beta Loss for Evidence-Based Safe Semi-Supervised Multi-Label Learning.

Hao-Zhe Liu, Ming-Kun Xie, Chen-Chen Zong, Sheng-Jun Huang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training.

Ming-Kun Xie, Jiahao Xiao, Pei Peng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Dirichlet-Based Coarse-to-Fine Example Selection For Open-Set Annotation.

Ye-Wen Wang, Chen-Chen Zong, Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-supervised Multi-label Learning.

Jiahao Xiao, Ming-Kun Xie, Heng-Bo Fan, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

Proceedings of the Computer Vision - ECCV 2024, 2024

Dirichlet-Based Prediction Calibration for Learning with Noisy Labels.

Chen-Chen Zong, Ye-Wen Wang, Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Unlocking the Power of Open Set: A New Perspective for Open-Set Noisy Label Learning.

Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shao-Yuan Li, Sheng-Jun Huang, Songcan Chen

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

CCMN: A General Framework for Learning With Class-Conditional Multi-Label Noise.

Ming-Kun Xie, Sheng-Jun Huang

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Unlocking the Power of Open Set : A New Perspective for Open-set Noisy Label Learning.

Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shengjun Huang, Songcan Chen, Shaoyuan Li

CoRR, 2023

Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning.

Ming-Kun Xie, Jiahao Xiao, Hao-Zhe Liu, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-Label Knowledge Distillation.

Penghui Yang, Ming-Kun Xie, Chen-Chen Zong, Lei Feng, Gang Niu, Masashi Sugiyama, Sheng-Jun Huang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Noise-Robust Bidirectional Learning with Dynamic Sample Reweighting.

Chen-Chen Zong, Zheng-Tao Cao, Hong-Tao Guo, Yun Du, Ming-Kun Xie, Shao-Yuan Li, Sheng-Jun Huang

CoRR, 2022

Meta Objective Guided Disambiguation for Partial Label Learning.

Bo-Shi Zou, Ming-Kun Xie, Sheng-Jun Huang

CoRR, 2022

Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels.

Ming-Kun Xie, Jiahao Xiao, Sheng-Jun Huang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Multi-Label Learning with Pairwise Relevance Ordering.

Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Partial Multi-Label Learning with Meta Disambiguation.

Ming-Kun Xie, Feng Sun, Sheng-Jun Huang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Semi-Supervised Partial Multi-Label Learning.

Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Partial Multi-Label Learning with Noisy Label Identification.

Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Learning Class-Conditional GANs with Active Sampling.

Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Active Feature Acquisition with Supervised Matrix Completion.

Sheng-Jun Huang, Miao Xu, Ming-Kun Xie, Masashi Sugiyama, Gang Niu, Songcan Chen

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Partial Multi-Label Learning.

Ming-Kun Xie, Sheng-Jun Huang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018