mlsanityData to 7 Oct 2026

Attention-based Deep Multiple Instance Learning

arXiv 1802.04712 ↗First posted 13 Feb 2018cs.LG stat.MLcited by 1,077

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Cited by 30 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Multiple instance learning (MIL) is a variation of supervised learning where a single class label is assigned to a bag of instances. In this paper, we state the MIL problem as learning the Bernoulli distribution of the bag label where the bag label probability is fully parameterized by neural networks. Furthermore, we propose a neural network-based permutation-invariant aggregation operator that corresponds to the attention mechanism. Notably, an application of the proposed attention-based operator provides insight into the contribution of each instance to the bag label. We show empirically that our approach achieves comparable performance to the best MIL methods on benchmark MIL datasets and it outperforms other methods on a MNIST-based MIL dataset and two real-life histopathology datasets without sacrificing interpretability.

Key facts. Cited by 1,077 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Feb 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 79; 2022: 123; 2023: 169; 2024: 207; 2025: 243; 2026: 256.

1,077 papers.

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  1. 2021TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classificationcited by 549
  2. 2022Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learningcited by 357
  3. 2022DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classificationcited by 254
  4. 2024Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathologycited by 144
  5. 2023Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Imagescited by 132
  6. 2021Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networkscited by 124
  7. 2022FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settingscited by 121
  8. 2023Artificial Intelligence for Digital and Computational Pathologycited by 106
  9. 2024HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysiscited by 104
  10. 2023Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Predictioncited by 92
  11. 2023Interventional Bag Multi-Instance Learning On Whole-Slide Pathological Imagescited by 91
  12. 2024MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathologycited by 87
38 more
  1. 2023Multimodal Optimal Transport-based Co-Attention Transformer with Global Structure Consistency for Survival Predictioncited by 86
  2. 2023Virchow: A Million-Slide Digital Pathology Foundation Modelcited by 86
  3. 2022Localizing Visual Sounds the Easy Waycited by 81
  4. 2023Quantifying & Modeling Multimodal Interactions: An Information Decomposition Frameworkcited by 81
  5. 2024PRISM: A Multi-Modal Generative Foundation Model for Slide-Level Histopathologycited by 80
  6. 2021Self-supervised learning methods and applications in medical imaging analysis: A surveycited by 76
  7. 2023Cross-Modal Translation and Alignment for Survival Analysiscited by 70
  8. 2024Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathologycited by 70
  9. 2021Differentiable Patch Selection for Image Recognitioncited by 68
  10. 2024Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathologycited by 66
  11. 2024Dynamic Graph Representation with Knowledge-aware Attention for Histopathology Whole Slide Image Analysiscited by 66
  12. 2021Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image Classificationcited by 65
  13. 2024A Clinical Benchmark of Public Self-Supervised Pathology Foundation Modelscited by 64
  14. 2023Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Reviewcited by 62
  15. 2023Attention-Challenging Multiple Instance Learning for Whole Slide Image Classificationcited by 61
  16. 2024A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Modelcited by 59
  17. 2021Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articlescited by 58
  18. 2022Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathologycited by 58
  19. 2023Multiple Instance Learning Framework with Masked Hard Instance Mining for Whole Slide Image Classificationcited by 58
  20. 2022Multiple Instance Learning for Digital Pathology: A Review on the State-of-the-Art, Limitations & Future Potentialcited by 54
  21. 2023Task-specific Fine-tuning via Variational Information Bottleneck for Weakly-supervised Pathology Whole Slide Image Classificationcited by 54
  22. 2021Deciphering antibody affinity maturation with language models and weakly supervised learningcited by 52
  23. 2023Towards a Visual-Language Foundation Model for Computational Pathologycited by 52
  24. 2024Accurate Spatial Gene Expression Prediction by integrating Multi-resolution featurescited by 52
  25. 2021Attention, please! A survey of Neural Attention Models in Deep Learningcited by 50
  26. 2024Transcriptomics-guided Slide Representation Learning in Computational Pathologycited by 50
  27. 2022Self-Supervised Vision Transformers Learn Visual Concepts in Histopathologycited by 49
  28. 2023Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learningcited by 47
  29. 2024Multimodal Prototyping for cancer survival predictioncited by 47
  30. 2022Transfer without Forgettingcited by 44
  31. 2021Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slidescited by 43
  32. 2022Differentiable Zooming for Multiple Instance Learning on Whole-Slide Imagescited by 43
  33. 2024HistGen: Histopathology Report Generation via Local-Global Feature Encoding and Cross-modal Context Interactioncited by 43
  34. 2022Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image Classificationcited by 42
  35. 2023A General-Purpose Self-Supervised Model for Computational Pathologycited by 42
  36. 2021A Survey on Graph-Based Deep Learning for Computational Histopathologycited by 41
  37. 2023The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classificationcited by 41
  38. 2023On Sparse Modern Hopfield Modelcited by 41

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