Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 2,681 to 2,690 of 202,598 articles

FontFusion: Enhancing Generative Text in Diffusion Models with Typographic Conditioning

arXiv Jun 4, 2026
Typography generation in diffusion models faces a persistent trade-off: enabling precise font control typically degrades text legibility, while maintaining readability often sacrifices typographic fidelity. We present FontFusion, a plug-and-play cond... read more 
Computer Vision and Pattern Recognition cs.GR

Knowledge Distillation for Visual Autoregressive Models

arXiv Jun 4, 2026
Autoregressive (AR) image generation models are highly expressive but computationally intensive, motivating effective model compression. Knowledge distillation (KD) is a natural approach for model compression and has been widely studied in language m... read more 
Computer Vision and Pattern Recognition

Integrating Mechanistic and Data-Driven Models for Neurological Disorders through Differentiable Programming

arXiv Jun 4, 2026
Advances in computational modeling, neuroimaging, and artificial intelligence are revolutionizing the modeling of neurological disorders for improved diagnostics, prognosis, and treatment planning. Mechanistic models provide valuable scientific insig... read more 
Artificial Intelligence cs.LG math.DS physics.med-ph

Step-adaptive multimodal fusion network with multi-scale cloud feature learning for ultra-short-term solar irradiance forecasting

arXiv Jun 4, 2026
Ultra-short-term solar irradiance prediction is critical for photovoltaic system dispatch and power grid stability. Existing approaches suffer from three key shortcomings: single time-series models cannot capture the spatial dynamics of clouds under ... read more 
Artificial Intelligence cs.LG

MS-DKC: A Dataset Knowledge Card Framework for Designing and Adapting Medical Image Segmentation Models

arXiv Jun 4, 2026
Medical image segmentation is often framed as a search for stronger architectures, but this can obscure a more fundamental question: what does the dataset require from the model? In medical imaging, this requirement is shaped by foreground occupancy,... read more 
Computer Vision and Pattern Recognition

A Sliced-Wasserstein Framework on Correlation Matrices for EEG Decoding

arXiv Jun 4, 2026
Electroencephalography (EEG) offers noninvasive, millisecond resolution recordings of neuronal activity and is widely used in neuroscience and healthcare. Many EEG decoding pipelines rely on covariance descriptors for their robustness to noise, but s... read more 
Machine Learning

Deployed trusted-node quantum key distribution over 300 km with a multi-core fiber access link

arXiv Jun 4, 2026
Quantum key distribution (QKD) is increasingly considered for deployment in realistic communication networks, where long distances, heterogeneous fiber infrastructure, and coexistence with classical traffic present substantial challenges. Here, we de... read more 
Quantum Physics cs.IT cs.LG eess.IV physics.optics

Where, What, Why, and Importance: Structured Defect Grounding for Text-to-Image Feedback

arXiv Jun 4, 2026
Despite generating increasingly photorealistic images, text-to-image (T2I) models still exhibit localized, subtle, and structurally complex failures. Diagnosing these failures requires instance-level feedback that answers where a defect occurs, what ... read more 
Computer Vision and Pattern Recognition

$p$-adic Bi-Filtrations for Topological Machine Learning on Genomic Sequences

arXiv Jun 4, 2026
We introduce pVR, a topological machine learning framework for alignment-free genomic sequence classification that combines $p$-adic numbers with topological data analysis. Each DNA sequence is encoded along two complementary axes: a $p$-adic distanc... read more 
Quantitative Methods cs.LG math.AT q-bio.GN

Diff-CA: Separating Common and Salient Factors with Diffusion Models

arXiv Jun 4, 2026
Contrastive Analysis aims to separate factors that are common between two data distributions from those that are salient to only one of them. Existing contrastive methods are based on generative models (e.g., VAEs or GANs) that often suffer from limi... read more 
Computer Vision and Pattern Recognition
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