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Found 3 papers, 1 papers with code
FaceBench: A Multi-View Multi-Level Facial Attribute VQA Dataset for Benchmarking Face Perception MLLMs
Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in various tasks.
{S$^3$-Mamba}: Small-Size-Sensitive Mamba for Lesion Segmentation
Specifically, an Enhanced Visual State Space block is designed to focus on small lesions through multiple residual connections to preserve local features, and selectively amplify important details while suppressing irrelevant ones through channel-wise attention.
WSI-LLaVA: A Multimodal Large Language Model for Whole Slide Image
Recent advancements in computational pathology have produced patch-level Multi-modal Large Language Models (MLLMs), but these models are limited by their inability to analyze whole slide images (WSIs) comprehensively and their tendency to bypass crucial morphological features that pathologists rely on for diagnosis.
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