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Multi-Instance Learning

108 papers

Papers per year

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Papers

Learning Structure-Aware Foundational Representation of Rat Testicular Tubules Using Multiple Instance Learning MIDL 2026
Queryable Prototype Multiple Instance Learning with Vision-Language Models for Incremental Whole Slide Image Classification AAAI 2025
TAIL-MIL: Time-Aware and Instance-Learnable Multiple Instance Learning for Multivariate Time Series Anomaly Detection AAAI 2025
T-MDML: Triplet-based Multiple Distance Metric Learning for Multi-Instance Multi-Label Classification with Label Correlation AAAI 2025
Multi-Instance Multi-Label Classification from Crowdsourced Labels AAAI 2025
Fast Multi-Instance Partial-Label Learning AAAI 2025
No Pains, More Gains: Recycling Sub-Salient Patches for Efficient High-Resolution Image Recognition CVPR 2025
M3amba: Memory Mamba is All You Need for Whole Slide Image Classification CVPR 2025
Fast and Accurate Gigapixel Pathological Image Classification with Hierarchical Distillation Multi-Instance Learning CVPR 2025
Minimal Evidence Group Identification for Claim Verification NAACL 2025
Ordinal Multiple-Instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer WACV 2025
Multi-Instance Partial-Label Learning with Margin Adjustment NIPS 2024
Sm: enhanced localization in Multiple Instance Learning for medical imaging classification NIPS 2024
CaMIL: Causal Multiple Instance Learning for Whole Slide Image Classification AAAI 2024
Boosting Multiple Instance Learning Models for Whole Slide Image Classification: A Model-Agnostic Framework Based on Counterfactual Inference AAAI 2024
Transformer-Based Video-Structure Multi-Instance Learning for Whole Slide Image Classification AAAI 2024
A Label Disambiguation-Based Multimodal Massive Multiple Instance Learning Approach for Immune Repertoire Classification AAAI 2024
A Positive-Unlabeled Metric Learning Framework for Document-Level Relation Extraction with Incomplete Labeling AAAI 2024
Combating Insider Threat in the Open-World Environments: Identification, Monitoring, and Data Augmentation AAAI 2024
Mixed Models with Multiple Instance Learning AISTATS 2024
Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology CVPR 2024
Dynamic Policy-Driven Adaptive Multi-Instance Learning for Whole Slide Image Classification CVPR 2024
ViLa-MIL: Dual-scale Vision-Language Multiple Instance Learning for Whole Slide Image Classification CVPR 2024
Accurate and Data-Efficient Toxicity Prediction when Annotators Disagree EMNLP 2024
SC-MIL: Supervised Contrastive Multiple Instance Learning for Imbalanced Classification in Pathology WACV 2024