K-MaT: Knowledge-Anchored Manifold Transport for Cross-Modal Prompt Learning in Medical Imaging | ScienceToStartup | ScienceToStartup

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References (16)

[1]

C-CLIP: Multimodal Continual Learning for Vision-Language Model

2025Wenzhuo Liu, Fei Zhu et al.

[2]

BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models

2024Taha Koleilat, Hojat Asgariandehkordi et al.

[3]

Multimodal Image Dataset for AI-based Skin Cancer (MIDAS) Benchmarking

Founder's Pitch

"K-MaT is a prompt-learning framework that enables zero-shot cross-modal transfer of medical VLMs, improving performance on low-end modalities without requiring retraining."

Medical AI•Score: 7•View PDF ↗

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K-MaT: Knowledge-Anchored Manifold Transport for Cross-Modal Prompt Learning in Medical Imaging

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References (16)

Founder's Pitch

"K-MaT is a prompt-learning framework that enables zero-shot cross-modal transfer of medical VLMs, improving performance on low-end modalities without requiring retraining."

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K-MaT: Knowledge-Anchored Manifold Transport for Cross-Modal Prompt Learning in Medical Imaging

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References (16)

Founder's Pitch

"K-MaT is a prompt-learning framework that enables zero-shot cross-modal transfer of medical VLMs, improving performance on low-end modalities without requiring retraining."

Commercial Viability Breakdown

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