Lumen: Parameter-Efficient Alignment of Pretrained Vision and Language Encoders for Zero-Shot Computational Pathology

arXiv:2609.17868 · cs.CV · Submitted 2026-09-15 · Read on arXiv

cs.CV

Submitted: 2026-09-15

Updated: 2026-09-15

Code: https://github.com/HiLab-git/WSI4LUAD

Project page: https://bmirds.github.io/MHIST

Terminology

• Accuracy — 49× in this paper · explained in 1 episode
• Benchmark — 41× in this paper · explained in 2 episodes
• Alignment — 32× in this paper · explained in 1 episode
• Linear probe — 17× in this paper · explained in 2 episodes
• Fine-Tuning — 14× in this paper · explained in 5 episodes
• Foundation Model — 11× in this paper · explained in 3 episodes
• Adaptation — 9× in this paper · explained in 1 episode
• Embeddings — 9× in this paper · explained in 2 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Calibration — 7× in this paper · explained in 7 episodes
• Cosine Similarity — 7× in this paper · explained in 3 episodes
• Foundation Models — 5× in this paper · explained in 7 episodes
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Distribution Shift — 2× in this paper · explained in 5 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Alignment Methods — 1× in this paper · explained in 1 episode
• Catastrophic Forgetting — 1× in this paper · explained in 5 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Multi-agent Collaboration — 1× in this paper · explained in 2 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Parameter-Efficient Fine-Tuning — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology
• Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity
• Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning
• Lung and Colon Cancer Histopathological Image Dataset (LC25000)
• HISTAI: An Open-Source, Large-Scale Whole Slide Image Dataset for Computational Pathology

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