Artificial Intelligence Medical Compendium

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

Showing 28,111 to 28,120 of 219,064 articles

Improving clinical interpretability of linear neuroimaging models through feature whitening

arXiv Apr 22, 2026
Linear models are widely used in computational neuroimaging to identify biomarkers associated with brain pathologies. However, interpreting the learned weights remains challenging, as they do not always yield clinically meaningful insights. This diff... read more 
Machine Learning

R-CoV: Region-Aware Chain-of-Verification for Alleviating Object Hallucinations in LVLMs

arXiv Apr 22, 2026
Large vision-language models (LVLMs) have demonstrated impressive performance in various multimodal understanding and reasoning tasks. However, they still struggle with object hallucinations, i.e., the claim of nonexistent objects in the visual input... read more 
Computer Vision and Pattern Recognition

Auto-ART: Structured Literature Synthesis and Automated Adversarial Robustness Testing

arXiv Apr 22, 2026
Adversarial robustness evaluation underpins every claim of trustworthy ML deployment, yet the field suffers from fragmented protocols and undetected gradient masking. We make two contributions. (1) Structured synthesis. We analyze nine peer-reviewed ... read more 
Cryptography and Security cs.LG

SSL-R1: Self-Supervised Visual Reinforcement Post-Training for Multimodal Large Language Models

arXiv Apr 22, 2026
Reinforcement learning (RL) with verifiable rewards (RLVR) has demonstrated the great potential of enhancing the reasoning abilities in multimodal large language models (MLLMs). However, the reliance on language-centric priors and expensive manual an... read more 
Computer Vision and Pattern Recognition

GeoRelight: Learning Joint Geometrical Relighting and Reconstruction with Flexible Multi-Modal Diffusion Transformers

arXiv Apr 22, 2026
Relighting a person from a single photo is an attractive but ill-posed task, as a 2D image ambiguously entangles 3D geometry, intrinsic appearance, and illumination. Current methods either use sequential pipelines that suffer from error accumulation,... read more 
Computer Vision and Pattern Recognition

Render-in-the-Loop: Vector Graphics Generation via Visual Self-Feedback

arXiv Apr 22, 2026
Multimodal Large Language Models (MLLMs) have shown promising capabilities in generating Scalable Vector Graphics (SVG) via direct code synthesis. However, existing paradigms typically adopt an open-loop "blind drawing" approach, where models generat... read more 
Computer Vision and Pattern Recognition

Render-in-the-Loop: Vector Graphics Generation via Visual Self-Feedback

arXiv Apr 22, 2026
Multimodal Large Language Models (MLLMs) have shown promising capabilities in generating Scalable Vector Graphics (SVG) via direct code synthesis. However, existing paradigms typically adopt an open-loop "blind drawing" approach, where models generat... read more 
Computer Vision and Pattern Recognition

Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health

arXiv Apr 22, 2026
Accurate condition monitoring of industrial equipment requires inferring latent degradation parameters from indirect sensor measurements under uncertainty. While traditional Bayesian methods like Markov Chain Monte Carlo (MCMC) provide rigorous uncer... read more 
Machine Learning eess.SY physics.comp-ph

Amodal SAM: A Unified Amodal Segmentation Framework with Generalization

arXiv Apr 22, 2026
Amodal segmentation is a challenging task that aims to predict the complete geometric shape of objects, including their occluded regions. Although existing methods primarily focus on amodal segmentation within the training domain, these approaches of... read more 
Computer Vision and Pattern Recognition

Relative Entropy Estimation in Function Space: Theory and Applications to Trajectory Inference

arXiv Apr 22, 2026
Trajectory Inference (TI) seeks to recover latent dynamical processes from snapshot data, where only independent samples from time-indexed marginals are observed. In applications such as single-cell genomics, destructive measurements make path-space ... read more 
Machine Learning
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