From Classification to Cross-Modal Understanding: Leveraging Vision-Language Models for Fine-Grained Renal Pathology
cs.CV
Submitted: 2025-11-15
Updated: 2026-10-09
Terminology
Sources
- Foundation Models in Computational Pathology: A Review of Challenges, Opportunities, and Impact
- A New Era in Computational Pathology: A Survey on Foundation and Vision-Language Models
- A Survey of Medical Vision-and-Language Applications and Their Techniques
- An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
- Glo-VLMs: Leveraging Vision-Language Models for Fine-Grained Diseased Glomerulus Classification
- Anomaly Detection and Early Warning Mechanism for Intelligent Monitoring Systems in Multi-Cloud Environments Based on LLM
- A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks
- Multimodal Alignment and Fusion: A Survey
- Improve Global Glomerulosclerosis Classification with Imbalanced Data using CircleMix Augmentation
- MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer
- FHIST: A Benchmark for Few-shot Classification of Histological Images
- Comparative Analysis of Different Efficient Fine Tuning Methods of Large Language Models (LLMs) in Low-Resource Setting
- CoCa: Contrastive Captioners are Image-Text Foundation Models
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