Artificial Intelligence Medical Compendium

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

Showing 56,891 to 56,900 of 227,153 articles

Towards Geometry-Aware and Motion-Guided Video Human Mesh Recovery

arXiv Jan 29, 2026
Existing video-based 3D Human Mesh Recovery (HMR) methods often produce physically implausible results, stemming from their reliance on flawed intermediate 3D pose anchors and their inability to effectively model complex spatiotemporal dynamics. To o... read more 
Computer Vision and Pattern Recognition

Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation

arXiv Jan 29, 2026
Unified Multimodal Models (UMMs) integrate both visual understanding and generation within a single framework. Their ultimate aspiration is to create a cycle where understanding and generation mutually reinforce each other. While recent post-training... read more 
Computer Vision and Pattern Recognition cs.LG

Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation

arXiv Jan 29, 2026
Unified Multimodal Models (UMMs) integrate both visual understanding and generation within a single framework. Their ultimate aspiration is to create a cycle where understanding and generation mutually reinforce each other. While recent post-training... read more 
Computer Vision and Pattern Recognition cs.LG

Revisiting Diffusion Model Predictions Through Dimensionality

arXiv Jan 29, 2026
Recent advances in diffusion and flow matching models have highlighted a shift in the preferred prediction target -- moving from noise ($\varepsilon$) and velocity (v) to direct data (x) prediction -- particularly in high-dimensional settings. Howeve... read more 
Machine Learning cs.CV

MultiModal Fine-tuning with Synthetic Captions

arXiv Jan 29, 2026
In this paper, we address a fundamental gap between pre-training and fine-tuning of deep neural networks: while pre-training has shifted from unimodal to multimodal learning with enhanced visual understanding, fine-tuning predominantly remains unimod... read more 
Computer Vision and Pattern Recognition

Accurate Network Traffic Matrix Prediction via LEAD: an LLM-Enhanced Adapter-Based Conditional Diffusion Model

arXiv Jan 29, 2026
Driven by the evolution toward 6G and AI-native edge intelligence, network operations increasingly require predictive and risk-aware adaptation under stringent computation and latency constraints. Network Traffic Matrix (TM), which characterizes flow... read more 
Machine Learning

Variance & Greediness: A comparative study of metric-learning losses

arXiv Jan 29, 2026
Metric learning is central to retrieval, yet its effects on embedding geometry and optimization dynamics are not well understood. We introduce a diagnostic framework, VARIANCE (intra-/inter-class variance) and GREEDINESS (active ratio and gradient no... read more 
Computer Vision and Pattern Recognition

Hypernetwork-Based Adaptive Aggregation for Multimodal Multiple-Instance Learning in Predicting Coronary Calcium Debulking

arXiv Jan 29, 2026
In this paper, we present the first attempt to estimate the necessity of debulking coronary artery calcifications from computed tomography (CT) images. We formulate this task as a Multiple-instance Learning (MIL) problem. The difficulty of this task ... read more 
Computer Vision and Pattern Recognition

SimGraph: A Unified Framework for Scene Graph-Based Image Generation and Editing

arXiv Jan 29, 2026
Recent advancements in Generative Artificial Intelligence (GenAI) have significantly enhanced the capabilities of both image generation and editing. However, current approaches often treat these tasks separately, leading to inefficiencies and challen... read more 
Computer Vision and Pattern Recognition cs.AI

HERS: Hidden-Pattern Expert Learning for Risk-Specific Vehicle Damage Adaptation in Diffusion Models

arXiv Jan 29, 2026
Recent advances in text-to-image (T2I) diffusion models have enabled increasingly realistic synthesis of vehicle damage, raising concerns about their reliability in automated insurance workflows. The ability to generate crash-like imagery challenges ... read more 
Computer Vision and Pattern Recognition
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