mlsanityData to 14 Oct 2026

Welcome New Doctor: Continual Learning with Expert Consultation and Autoregressive Inference for Whole Slide Image Analysis

arXiv 2508.02220 ↗First posted 4 Aug 2025cs.CVcited by 1

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Abstract (arXiv)

Whole Slide Image (WSI) analysis, with its ability to reveal detailed tissue structures in magnified views, plays a crucial role in cancer diagnosis and prognosis. Due to their giga-sized nature, WSIs require substantial storage and computational resources for processing and training predictive models. With the rapid increase in WSIs used in clinics and hospitals, there is a growing need for a continual learning system that can efficiently process and adapt existing models to new tasks without retraining or fine-tuning on previous tasks. Such a system must balance resource efficiency with high performance. In this study, we introduce COSFormer, a Transformer-based continual learning framework tailored for multi-task WSI analysis. COSFormer is designed to learn sequentially from new tasks wile avoiding the need to revisit full historical datasets. We evaluate COSFormer on a sequence of seven WSI datasets covering seven organs and six WSI-related tasks under both class-incremental and task-incremental settings. The results demonstrate COSFormer's superior generalizability and effectiveness compared to existing continual learning frameworks, establishing it as a robust solution for continual WSI analysis in clinical applications.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 27 of its 45 references that are in the map. First posted on arXiv 4 Aug 2025.

Builds on

27 of 45 references.

References · 27

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2016Overcoming catastrophic forgetting in neural networkscited by 4,787
  4. 2016iCaRL: Incremental Classifier and Representation Learningcited by 2,333
  5. 2022Editing Models with Task Arithmeticcited by 1,120
  6. 2018Attention-based Deep Multiple Instance Learningcited by 1,095
  7. 2018Efficient Lifelong Learning with A-GEMcited by 1,058
  8. 2020Domain-Specific Language Model Pretraining for Biomedical Natural Language Processingcited by 1,009
  9. 2020Dark Experience for General Continual Learning: a Strong, Simple Baselinecited by 911
  10. 2020Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Imagescited by 745
  11. 2021TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classificationcited by 555
  12. 2021Nystr"omformer: A Nystr"om-Based Algorithm for Approximating Self-Attentioncited by 471
15 more
  1. 2019Lookahead Optimizer: k steps forward, 1 step backcited by 336
  2. 2019Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgettingcited by 302
  3. 2022DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classificationcited by 256
  4. 2021New Insights on Reducing Abrupt Representation Change in Online Continual Learningcited by 219
  5. 2023Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Imagescited by 134
  6. 2024Merging Multi-Task Models via Weight-Ensembling Mixture of Expertscited by 85
  7. 2019Deep Learning for Whole Slide Image Analysis: An Overviewcited by 51
  8. 2023TaskExpert: Dynamically Assembling Multi-Task Representations with Memorial Mixture-of-Expertscited by 45
  9. 2022AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Imagescited by 24
  10. 2024Queryable Prototype Multiple Instance Learning with Vision-Language Models for Incremental Whole Slide Image Classificationcited by 10
  11. 2023MoMA: Momentum Contrastive Learning with Multi-head Attention-based Knowledge Distillation for Histopathology Image Analysiscited by 6
  12. 2024Lifelong Histopathology Whole Slide Image Retrieval via Distance Consistency Rehearsalcited by 5
  13. 2024CAMP: Continuous and Adaptive Learning Model in Pathologycited by 4
  14. 2024FALFormer: Feature-aware Landmarks self-attention for Whole-slide Image Classificationcited by 3
  15. 2024MECFormer: Multi-task Whole Slide Image Classification with Expert Consultation Networkcited by 2

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Citing papers per year: 2026: 1.

1 paper.

  1. 2026STAIL: Semantic Text-Anchored Incremental Learning for Medical Imaging via Large Language Modelscited by 0