mlsanityData to 14 Oct 2026

Accelerating Data Processing and Benchmarking of AI Models for Pathology

arXiv 2502.06750 ↗First posted 10 Feb 2025cs.CVcited by 65

Not on the map. Why?

Abstract (arXiv)

Advances in foundation modeling have reshaped computational pathology. However, the increasing number of available models and lack of standardized benchmarks make it increasingly complex to assess their strengths, limitations, and potential for further development. To address these challenges, we introduce a new suite of software tools for whole-slide image processing, foundation model benchmarking, and curated publicly available tasks. We anticipate that these resources will promote transparency, reproducibility, and continued progress in the field.

Key facts. Cited by 65 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Feb 2025.

Builds on

0 of 0 references.

No references here yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 28; 2026: 37.

65 papers.

Sort:

By area:

  1. 2025Evidence-based diagnostic reasoning with multi-agent copilot for human pathologycited by 27
  2. 2025PathAgent: Toward Interpretable Analysis of Whole-slide Pathology Images via Large Language Model-based Agentic Reasoningcited by 19
  3. 2025PixCell: A generative foundation model for digital histopathology imagescited by 11
  4. 2025Foundation Models in Medical Imaging: A Review and Outlookcited by 8
  5. 2025A Large-Scale Benchmark of Cross-Modal Learning for Histology and Gene Expression in Spatial Transcriptomicscited by 8
  6. 2025TICON: A Slide-Level Tile Contextualizer for Histopathology Representation Learningcited by 6
  7. 2025Fusion of Multi-scale Heterogeneous Pathology Foundation Models for Whole Slide Image Analysiscited by 5
  8. 2025Beyond Pixel Simulation: Pathology Image Generation via Diagnostic Semantic Tokens and Prototype Controlcited by 4
  9. 2026AtlasPatch: Scalable Foundation Model-based Tissue Detection and Patch Extraction for Computational Pathologycited by 3
  10. 2026MOOZY: A Patient-First Foundation Model for Computational Pathologycited by 3
  11. 2025SGPMIL: Sparse Gaussian Process Multiple Instance Learningcited by 2
  12. 2025Learning the Language of Histopathology Images reveals Prognostic Subgroups in Invasive Lung Adenocarcinoma Patientscited by 2
38 more
  1. 2025Leveraging Foundation Models for Histological Grading in Cutaneous Squamous Cell Carcinoma using PathFMToolscited by 2
  2. 2025Democratising Pathology Co-Pilots: An Open Pipeline and Dataset for Whole-Slide Vision-Language Modellingcited by 2
  3. 2026Computational Pathology in the Era of Emerging Foundation and Agentic AI -- International Expert Perspectives on Clinical Integration and Translational Readinesscited by 2
  4. 2025MVHybrid: Improving Spatial Transcriptomics Prediction with Hybrid State Space-Vision Transformer Backbone in Pathology Vision Foundation Modelscited by 1
  5. 2025Morphology-Aware Prognostic model for Five-Year Survival Prediction in Colorectal Cancer from H&E Whole Slide Imagescited by 1
  6. 2025MPath: Multimodal Pathology Report Generation from Whole Slide Imagescited by 1
  7. 2025A Multicenter Benchmark of Multiple Instance Learning Models for Lymphoma Subtyping from HE-stained Whole Slide Imagescited by 1
  8. 2026PathMoE: Interpretable Multimodal Interaction Experts for Pediatric Brain Tumor Classificationcited by 1
  9. 2026Clinically-Informed Modeling for Pediatric Brain Tumor Classification from Whole-Slide Histopathology Imagescited by 1
  10. 2026Semantic Context-aware mOdality fUsion Transformer (SCOUT): A Context-Aware Multimodal Transformer for Concept-Grounded Pathology Report Generationcited by 1
  11. 2026Benchmarking Pathology Foundation Models for Spatial Domain Understandingcited by 1
  12. 2025Cascade Detector Analysis and Application to Biomedical Microscopycited by 0
  13. 2025The Butterfly Effect in Pathology: Exploring Security in Pathology Foundation Modelscited by 0
  14. 2025Predicting EGFR Mutation in LUAD from Histopathological Whole-Slide Images Using Pretrained Foundation Model and Transfer Learning: An Indian Cohort Studycited by 0
  15. 2025AdaFusion: Prompt-Guided Inference with Adaptive Fusion of Pathology Foundation Modelscited by 0
  16. 2025Integrating Pathology and CT Imaging for Personalized Recurrence Risk Prediction in Renal Cancercited by 0
  17. 2025ModalSurv: Investigating opportunities and limitations of multimodal deep survival learning in prostate and bladder cancercited by 0
  18. 2025Hierarchical Generalized Category Discovery for Brain Tumor Classification in Digital Pathologycited by 0
  19. 2025Synergy vs. Noise: Performance-Guided Multimodal Fusion For Biochemical Recurrence-Free Survival in Prostate Cancercited by 0
  20. 2025Information-driven Fusion of Pathology Foundation Models for Enhanced Disease Characterizationcited by 0
  21. 2025DA-SSL: self-supervised domain adaptor to leverage foundational models in turbt histopathology slidescited by 0
  22. 2025CAPRMIL: Context-Aware Patch Representations for Multiple Instance Learningcited by 0
  23. 2025PathBench-MIL: A Comprehensive AutoML and Benchmarking Framework for Multiple Instance Learning in Histopathologycited by 0
  24. 2026Semi-Supervised Domain Adaptation with Latent Diffusion for Pathology Image Classificationcited by 0
  25. 2026Efficient Special Stain Classificationcited by 0
  26. 2026A Contrastive Variational AutoEncoder for NSCLC Survival Prediction with Missing Modalitiescited by 0
  27. 2026PC-MIL: Decoupling Feature Resolution from Supervision Scale in Whole-Slide Learningcited by 0
  28. 2026Unified Multi-Foundation-Model Slide Representation for Pan-Cancer Recognition and Text-Guided Tumor Localizationcited by 0
  29. 2026Validation of Whole-Slide Foundation Models for Image Retrieval in TCGA Datacited by 0
  30. 2026Isotonic Survival Regression: Calibrated Survival Distributions from Deep Cox Modelscited by 0
  31. 2026Discrepancy Minimization Improves Cross-Hospital Robustness in Digital Pathologycited by 0
  32. 2026Pathway-Structured Privileged Distillation for Deployable Computational Pathologycited by 0
  33. 2026From Patches to Patients: A study of the tile-to-slide performance transferability in Digital Pathologycited by 0
  34. 2026How Seemingly Inconsequential Design Choices Dictate Performance of LLMs in Pathologycited by 0
  35. 2026Vision-Language Models as Zero-Annotation Oracles in Histopathologycited by 0
  36. 2026Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncologycited by 0
  37. 2026Uncertainty Estimation in Pathology Foundation Models via Deep Mutual Learningcited by 0
  38. 2026PathReportEval: A Systematic Benchmark for Pathology Report Generationcited by 0

50 most cited of 65 All 65 (JSON)