FFM-CP: Cross-Backbone Fusion of Vision-Language Foundation Models for Few-Shot Computational Pathology

arXiv:2609.27710 · cs.CV, cs.LG · Submitted 2026-09-23 · Read on arXiv

cs.CV, cs.LG

Submitted: 2026-09-23

Updated: 2026-10-03

Terminology

• Foundation Model — 36× in this paper · explained in 3 episodes
• Foundation Models — 29× in this paper · explained in 7 episodes
• Alignment — 28× in this paper · explained in 1 episode
• AUC — 27× in this paper · explained in 2 episodes
• Adaptation — 11× in this paper · explained in 1 episode
• Accuracy — 9× in this paper · explained in 1 episode
• Orthogonal Procrustes — 7× in this paper
• Benchmark — 5× in this paper · explained in 2 episodes
• Few-Shot Learning — 4× in this paper · explained in 4 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Embeddings — 3× in this paper · explained in 2 episodes
• Knowledge Graph — 3× in this paper · explained in 7 episodes
• Adjacency Matrix — 2× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 2× in this paper
• Distillation — 2× in this paper · explained in 2 episodes
• Heterogeneous Graph — 2× in this paper · explained in 2 episodes
• Ontology — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Linear Probing — 1× in this paper · explained in 2 episodes
• Nadia — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Singular Value Decomposition (SVD) — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Ensemble learning of pathology foundation models for precision oncology
• Fusion of Multi-scale Heterogeneous Pathology Foundation Models for Whole Slide Image Analysis
• Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
• Plug-and-Play Logit Fusion for Heterogeneous Pathology Foundation Models

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