Artificial Intelligence Medical Compendium

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

Showing 20,081 to 20,090 of 215,962 articles

AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in UMMs via Decompositional Verifiable Reward

arXiv May 12, 2026
In this paper, we propose AlphaGRPO, a novel framework that applies Group Relative Policy Optimization (GRPO) to AR-Diffusion Unified Multimodal Models (UMMs) to enhance multimodal generation capabilities without an additional cold-start stage. Our a... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

From Web to Pixels: Bringing Agentic Search into Visual Perception

arXiv May 12, 2026
Visual perception connects high-level semantic understanding to pixel-level perception, but most existing settings assume that the decisive evidence for identifying a target is already in the image or frozen model knowledge. We study a more practical... read more 
Computer Vision and Pattern Recognition

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

arXiv May 12, 2026
Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fragmented architectures, cascaded pipelines, and misaligned representati... read more 
Computer Vision and Pattern Recognition

Covering Human Action Space for Computer Use: Data Synthesis and Benchmark

arXiv May 12, 2026
Computer-use agents (CUAs) automate on-screen work, as illustrated by GPT-5.4 and Claude. Yet their reliability on complex, low-frequency interactions is still poor, limiting user trust. Our analysis of failure cases from advanced models suggests a l... read more 
Computer Vision and Pattern Recognition

Uncovering Latent Pathological Signatures in Pulmonary CT via Cross-Window Knowledge Distillation

arXiv May 12, 2026
Multi-window CT imaging captures complementary pathological information across anatomical structures of differing densities, yet existing deep learning methods fuse representations only at later stages, missing cross-density interactions. We propose ... read more 
Image and Video Processing cs.AI cs.CV

On Privacy-Preserving Image Transmission in Low-Altitude Networks: A Swin Transformer-Based Framework with Federated Learning

arXiv May 12, 2026
The rapid development of low-altitude economy has driven the proliferation of Unmanned Aerial Vehicle (UAV) applications, including logistics, inspection, and emergency response. However, transmitting high-volume image data from UAVs to ground statio... read more 
Image and Video Processing cs.LG

Pyramid Self-contrastive Learning Framework for Test-time Ultrasound Image Denoising

arXiv May 12, 2026
The inherent electronic and speckle noise complicates clinical interpretation of ultrasound images. Conventional denoising methods rely on explicit noise assumptions whose validity diminishes under composite noise conditions. Learning-based methods r... read more 
Computer Vision and Pattern Recognition cs.AI

M3Net: A Macro-to-Meso-to-Micro Clinical-inspired Hierarchical 3D Network for Pulmonary Nodule Classification

arXiv May 12, 2026
The accurate classification of benign and malignant pulmonary nodules in CT scans is critical for early lung cancer screening, yet remains challenging due to the multi-scale and heterogeneous nature of pulmonary nodules. While deep learning offers po... read more 
Computer Vision and Pattern Recognition

Improving Diffusion Posterior Samplers with Lagged Temporal Corrections for Image Restoration

arXiv May 12, 2026
Diffusion-based posterior sampling (PS) is a leading framework for imaging inverse problems, combining learned priors with measurement constraints. Yet, its standard formulations rely on instantaneous data-consistent estimates, which induce temporal ... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

DistractMIA: Black-Box Membership Inference on Vision-Language Models via Semantic Distraction

arXiv May 12, 2026
Vision-language models (VLMs) are trained on large-scale image-text corpora that may contain private, copyrighted, or otherwise sensitive data, motivating membership inference as a tool for training-data auditing. This is especially challenging for d... read more 
Computer Vision and Pattern Recognition cs.AI
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