Artificial Intelligence Medical Compendium

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

Showing 51,981 to 51,990 of 225,279 articles

Stability and Concentration in Nonlinear Inverse Problems with Block-Structured Parameters: Lipschitz Geometry, Identifiability, and an Application to Gaussian Splatting

arXiv Feb 10, 2026
We develop an operator-theoretic framework for stability and statistical concentration in nonlinear inverse problems with block-structured parameters. Under a unified set of assumptions combining blockwise Lipschitz geometry, local identifiability, a... read more 
Computer Vision and Pattern Recognition math.NA

Bridging the Modality Gap in Roadside LiDAR: A Training-Free Vision-Language Model Framework for Vehicle Classification

arXiv Feb 10, 2026
Fine-grained truck classification is critical for intelligent transportation systems (ITS), yet current LiDAR-based methods face scalability challenges due to their reliance on supervised deep learning and labor-intensive manual annotation. Vision-La... read more 
Computer Vision and Pattern Recognition cs.LG

Understanding and Enhancing Encoder-based Adversarial Transferability against Large Vision-Language Models

arXiv Feb 10, 2026
Large vision-language models (LVLMs) have achieved impressive success across multimodal tasks, but their reliance on visual inputs exposes them to significant adversarial threats. Existing encoder-based attacks perturb the input image by optimizing s... read more 
Cryptography and Security cs.CV

Fine-T2I: An Open, Large-Scale, and Diverse Dataset for High-Quality T2I Fine-Tuning

arXiv Feb 10, 2026
High-quality and open datasets remain a major bottleneck for text-to-image (T2I) fine-tuning. Despite rapid progress in model architectures and training pipelines, most publicly available fine-tuning datasets suffer from low resolution, poor text-ima... read more 
Computer Vision and Pattern Recognition

Look-Ahead and Look-Back Flows: Training-Free Image Generation with Trajectory Smoothing

arXiv Feb 10, 2026
Recent advances have reformulated diffusion models as deterministic ordinary differential equations (ODEs) through the framework of flow matching, providing a unified formulation for the noise-to-data generative process. Various training-free flow ma... read more 
Computer Vision and Pattern Recognition

Scalable and Reliable State-Aware Inference of High-Impact N-k Contingencies

arXiv Feb 10, 2026
Increasing penetration of inverter-based resources, flexible loads, and rapidly changing operating conditions make higher-order $N\!-\!k$ contingency assessment increasingly important but computationally prohibitive. Exhaustive evaluation of all outa... read more 
Machine Learning

NOWJ @BioCreative IX ToxHabits: An Ensemble Deep Learning Approach for Detecting Substance Use and Contextual Information in Clinical Texts

arXiv Feb 10, 2026
Extracting drug use information from unstructured Electronic Health Records remains a major challenge in clinical Natural Language Processing. While Large Language Models demonstrate advancements, their use in clinical NLP is limited by concerns over... read more 
Computation and Language cs.AI

ArtifactLens: Hundreds of Labels Are Enough for Artifact Detection with VLMs

arXiv Feb 10, 2026
Modern image generators produce strikingly realistic images, where only artifacts like distorted hands or warped objects reveal their synthetic origin. Detecting these artifacts is essential: without detection, we cannot benchmark generators or train... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

FD-DB: Frequency-Decoupled Dual-Branch Network for Unpaired Synthetic-to-Real Domain Translation

arXiv Feb 10, 2026
Synthetic data provide low-cost, accurately annotated samples for geometry-sensitive vision tasks, but appearance and imaging differences between synthetic and real domains cause severe domain shift and degrade downstream performance. Unpaired synthe... read more 
Computer Vision and Pattern Recognition

FD-DB: Frequency-Decoupled Dual-Branch Network for Unpaired Synthetic-to-Real Domain Translation

arXiv Feb 10, 2026
Synthetic data provide low-cost, accurately annotated samples for geometry-sensitive vision tasks, but appearance and imaging differences between synthetic and real domains cause severe domain shift and degrade downstream performance. Unpaired synthe... read more 
Computer Vision and Pattern Recognition
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