Min-ling Zhang

APVR: Hour-Level Long Video Understanding with Adaptive Pivot Visual Information Retrieval AAAI 2026 Classifier-induced Reciprocal Points for Multi-label Open-set Recognition AAAI 2026 Collaborative Dual Representations for Semi-Supervised Partial Label Learning AAAI 2026 DC-Merge: Improving Model Merging with Directional Consistency CVPR 2026 EpiAgent: An Agent-Centric System for Ancient Inscription Restoration CVPR 2026 OmniGround: A Comprehensive Spatio-Temporal Grounding Benchmark for Real-World Complex Scenarios CVPR 2026 SARL-STG: A Spatially Aware Reinforcement Learning Framework for Refining MLLMs in Spatio-Temporal Video Grounding CVPR 2026 Evolutionary Classifier Chain for Multi-Dimensional Classification AAAI 2025 Fast Multi-Instance Partial-Label Learning AAAI 2025 Generalization Analysis for Controllable Learning ICML 2025 HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing Risks AISTATS 2025 Implicit Relative Labeling-Importance Aware Multi-Label Metric Learning AAAI 2025 LADA: Scalable Label-Specific CLIP Adapter for Continual Learning ICML 2025 Learnware Specification via Dual Alignment ICML 2025 Learnware Specification via Label-Aware Neural Embedding AAAI 2025 Noise Separation guided Candidate Label Reconstruction for Noisy Partial Label Learning ICLR 2025 Partial Label Causal Representation Learning for Instance-Dependent Supervision and Domain Generalization AAAI 2025 Realistic Evaluation of Deep Partial-Label Learning Algorithms ICLR 2025 Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency ICLR 2025 Tight and Fast Bounds for Multi-Label Learning ICML 2025 Towards Escaping from Class Dependency Modeling for Multi-Dimensional Classification ICML 2025 Weakly-Supervised Contrastive Learning for Imprecise Class Labels ICML 2025 Wrapped Partial Label Dimensionality Reduction via Dependence Maximization IJCAI 2025 Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning ICML 2024 Bridging the Gap: Learning Pace Synchronization for Open-World Semi-Supervised Learning IJCAI 2024 Calibration Bottleneck: Over-compressed Representations are Less Calibratable ICML 2024 Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition NeurIPS 2024 Deep Multi-Dimensional Classification with Pairwise Dimension-Specific Features IJCAI 2024 Disentangled Partial Label Learning AAAI 2024 Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning AAAI 2024 EAT: Towards Long-Tailed Out-of-Distribution Detection AAAI 2024 Efficient Model Stealing Defense with Noise Transition Matrix CVPR 2024 Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning IJCAI 2024 Generalization Analysis for Label-Specific Representation Learning NeurIPS 2024 Generalization Analysis for Multi-Label Learning ICML 2024 Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition ICML 2024 Learning Label-Specific Multiple Local Metrics for Multi-Label Classification IJCAI 2024 Long-Tailed Partial Label Learning by Head Classifier and Tail Classifier Cooperation AAAI 2024 Multi-Instance Partial-Label Learning with Margin Adjustment NeurIPS 2024 Multi-Label Open Set Recognition NeurIPS 2024 Unlearning from Weakly Supervised Learning IJCAI 2024 Vision-Language Models are Strong Noisy Label Detectors NeurIPS 2024 What Makes Partial-Label Learning Algorithms Effective? NeurIPS 2024 Binary Classification with Confidence Difference NeurIPS 2023 Can Label-Specific Features Help Partial-Label Learning? AAAI 2023 Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning NeurIPS 2023 Label Specific Multi-Semantics Metric Learning for Multi-Label Classification: Global Consideration Helps IJCAI 2023 Nearly-tight Bounds for Deep Kernel Learning ICML 2023 On the Pitfall of Mixup for Uncertainty Calibration CVPR 2023 Partial-Label Regression AAAI 2023 Partial Multi-Label Learning with Probabilistic Graphical Disambiguation NeurIPS 2023 Progressive Label Propagation for Semi-Supervised Multi-Dimensional Classification IJCAI 2023 Stochastic Feature Averaging for Learning with Long-Tailed Noisy Labels IJCAI 2023 Unbiased Risk Estimator to Multi-Labeled Complementary Label Learning IJCAI 2023 Dual Perspective of Label-Specific Feature Learning for Multi-Label Classification ICML 2022 End-to-End Probabilistic Label-Specific Feature Learning for Multi-Label Classification AAAI 2022 Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization NeurIPS 2022 One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement NeurIPS 2022 Revisiting Consistency Regularization for Deep Partial Label Learning ICML 2022 BAMBOO: A Multi-instance Multi-label Approach Towards VDI User Logon Behavior Modeling IJCAI 2021 Correlation-Guided Representation for Multi-Label Text Classification IJCAI 2021 Discriminative Complementary-Label Learning with Weighted Loss ICML 2021 Exploiting Unlabeled Data via Partial Label Assignment for Multi-Class Semi-Supervised Learning AAAI 2021 Instance-Dependent Partial Label Learning NeurIPS 2021 Learning from Complementary Labels via Partial-Output Consistency Regularization IJCAI 2021 Learning from Noisy Labels with Complementary Loss Functions AAAI 2021 Multi-Dimensional Classification via Sparse Label Encoding ICML 2021 Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence NeurIPS 2021 Maximum Margin Multi-Dimensional Classification AAAI 2020 Multi-View Partial Multi-Label Learning with Graph-Based Disambiguation AAAI 2020 Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization NeurIPS 2020 CAFE: Adaptive VDI Workload Prediction with Multi-Grained Features AAAI 2019 Multi-Dimensional Classification via kNN Feature Augmentation AAAI 2019 Multi-Label Learning with Regularization Enriched Label-Specific Features ACML 2019 Multi-View Multi-Label Learning with View-Specific Information Extraction IJCAI 2019 Partial Multi-Label Learning via Credible Label Elicitation AAAI 2019 Towards Enabling Binary Decomposition for Partial Label Learning IJCAI 2018 Binary Linear Compression for Multi-label Classification IJCAI 2017 Maximum Margin Partial Label Learning ACML 2015 Solving the Partial Label Learning Problem: An Instance-Based Approach IJCAI 2015 Towards Class-Imbalance Aware Multi-Label Learning IJCAI 2015 Multi-Label Classification with Unlabeled Data: An Inductive Approach ACML 2013 Multi-Instance Multi-Label Learning with Application to Scene Classification NeurIPS 2006