Articles 2
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Sparse Mixture-of-Experts Transformers with Dynamic Routing for Efficient Large Language Model Inference
We propose DynaMoE, a sparse Mixture-of-Experts (MoE) architecture with learned dynamic routing that achieves 2.8× inference speedup over dense Transformers of equivalent quality. Unlike conventional top-k gating,... -
Graph Neural Network-Based Drug-Target Interaction Prediction with Multi-Scale Molecular Fingerprints
Predicting drug-target interactions (DTIs) is fundamental for drug discovery but remains challenging due to the vast chemical and protein space. We present MolGraphDTI, a graph neural network framework that integrates...
Review Articles 1
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Self-Supervised Vision Transformers for Medical Image Segmentation with Limited Annotations
Annotating medical images for segmentation is expensive and requires domain expertise. We propose MedSSL-ViT, a self-supervised pre-training framework for Vision Transformers (ViT) tailored to medical imaging....