Artificial Intelligence Medical Compendium

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

Showing 55,251 to 55,260 of 226,647 articles

Tiled Prompts: Overcoming Prompt Underspecification in Image and Video Super-Resolution

arXiv Feb 3, 2026
Text-conditioned diffusion models have advanced image and video super-resolution by using prompts as semantic priors, but modern super-resolution pipelines typically rely on latent tiling to scale to high resolutions, where a single global caption ca... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Z3D: Zero-Shot 3D Visual Grounding from Images

arXiv Feb 3, 2026
3D visual grounding (3DVG) aims to localize objects in a 3D scene based on natural language queries. In this work, we explore zero-shot 3DVG from multi-view images alone, without requiring any geometric supervision or object priors. We introduce Z3D,... read more 
Computer Vision and Pattern Recognition

Multi-Resolution Alignment for Voxel Sparsity in Camera-Based 3D Semantic Scene Completion

arXiv Feb 3, 2026
Camera-based 3D semantic scene completion (SSC) offers a cost-effective solution for assessing the geometric occupancy and semantic labels of each voxel in the surrounding 3D scene with image inputs, providing a voxel-level scene perception foundatio... read more 
Computer Vision and Pattern Recognition

SLIM-Diff: Shared Latent Image-Mask Diffusion with Lp loss for Data-Scarce Epilepsy FLAIR MRI

arXiv Feb 3, 2026
Focal cortical dysplasia (FCD) lesions in epilepsy FLAIR MRI are subtle and scarce, making joint image--mask generative modeling prone to instability and memorization. We propose SLIM-Diff, a compact joint diffusion model whose main contributions are... read more 
Computer Vision and Pattern Recognition cs.AI

Enhancing Quantum Diffusion Models for Complex Image Generation

arXiv Feb 3, 2026
Quantum generative models offer a novel approach to exploring high-dimensional Hilbert spaces but face significant challenges in scalability and expressibility when applied to multi-modal distributions. In this study, we explore a Hybrid Quantum-Clas... read more 
Quantum Physics cs.LG

UnHype: CLIP-Guided Hypernetworks for Dynamic LoRA Unlearning

arXiv Feb 3, 2026
Recent advances in large-scale diffusion models have intensified concerns about their potential misuse, particularly in generating realistic yet harmful or socially disruptive content. This challenge has spurred growing interest in effective machine ... read more 
Computer Vision and Pattern Recognition

Socratic-Geo: Synthetic Data Generation and Geometric Reasoning via Multi-Agent Interaction

arXiv Feb 3, 2026
Multimodal Large Language Models (MLLMs) have significantly advanced vision-language understanding. However, even state-of-the-art models struggle with geometric reasoning, revealing a critical bottleneck: the extreme scarcity of high-quality image-t... read more 
Computer Vision and Pattern Recognition cs.AI

Origin Lens: A Privacy-First Mobile Framework for Cryptographic Image Provenance and AI Detection

arXiv Feb 3, 2026
The proliferation of generative AI poses challenges for information integrity assurance, requiring systems that connect model governance with end-user verification. We present Origin Lens, a privacy-first mobile framework that targets visual disinfor... read more 
Cryptography and Security cs.CV cs.CY cs.HC

Hierarchical Concept-to-Appearance Guidance for Multi-Subject Image Generation

arXiv Feb 3, 2026
Multi-subject image generation aims to synthesize images that faithfully preserve the identities of multiple reference subjects while following textual instructions. However, existing methods often suffer from identity inconsistency and limited compo... read more 
Computer Vision and Pattern Recognition cs.AI

Score-based diffusion models for diffuse optical tomography with uncertainty quantification

arXiv Feb 3, 2026
Score-based diffusion models are a recently developed framework for posterior sampling in Bayesian inverse problems with a state-of-the-art performance for severely ill-posed problems by leveraging a powerful prior distribution learned from empirical... read more 
Machine Learning cs.LG stat.AP
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