According to TII’s technical report, the hybrid approach allows Falcon H1R 7B to maintain high throughput even as response ...

By transferring temporal knowledge from complex time-series models to a compact model through knowledge distillation and attention mechanisms, the ...

Machine learning is quietly rewriting the rules of the cosmic hunt for company. Instead of waiting to recognize familiar ...

Insilico Medicine (3696.HK), a clinical-stage drug discovery and development company driven by generative artificial ...

For decades, Uranus and Neptune have been filed neatly into the “ice giant” drawer, shorthand for worlds built mostly from ...

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...

Motif-2-12.7B-Reasoning is positioned as competitive with much larger models, but its real value lies in the transparency of ...

📋 Project Overview This project presents a novel CBAM-guided channel pruning framework for efficient osteoporosis classification using knee X-ray images. The methodology achieves 55.9% parameter ...

Abstract: Deep learning models perform exceptionally well in time series classification, but their lack of interpretability remains a significant challenge. Although explainable AI (XAI) techniques ...

In large public multi-site fMRI datasets, the sample characteristics, data acquisition methods, and MRI scanner models vary across sites and datasets. This non-neural variability obscures neural ...