Artificial Intelligence Medical Compendium

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

Showing 44,311 to 44,320 of 224,055 articles

Artificial Intelligence for Detecting Fetal Orofacial Clefts and Advancing Medical Education

arXiv Mar 6, 2026
Orofacial clefts are among the most common congenital craniofacial abnormalities, yet accurate prenatal detection remains challenging due to the scarcity of experienced specialists and the relative rarity of the condition. Early and reliable diagnosi... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Spatial Calibration of Diffuse LiDARs

arXiv Mar 6, 2026
Diffuse direct time-of-flight LiDARs report per-pixel depth histograms formed by aggregating photon returns over a wide instantaneous field of view, violating the single-ray assumption behind standard LiDAR-RGB calibration. We present a simple spatia... read more 
Computer Vision and Pattern Recognition cs.RO

NEGATE: Constrained Semantic Guidance for Linguistic Negation in Text-to-Video Diffusion

arXiv Mar 6, 2026
Negation is a fundamental linguistic operator, yet it remains inadequately modeled in diffusion-based generative systems. In this work, we present a formal treatment of linguistic negation in diffusion-based generative models by modeling it as a stru... read more 
Computer Vision and Pattern Recognition

Modeling and Measuring Redundancy in Multisource Multimodal Data for Autonomous Driving

arXiv Mar 6, 2026
Next-generation autonomous vehicles (AVs) rely on large volumes of multisource and multimodal ($M^2$) data to support real-time decision-making. In practice, data quality (DQ) varies across sources and modalities due to environmental conditions and s... read more 
Computer Vision and Pattern Recognition

Causal Interpretation of Neural Network Computations with Contribution Decomposition

arXiv Mar 6, 2026
Understanding how neural networks transform inputs into outputs is crucial for interpreting and manipulating their behavior. Most existing approaches analyze internal representations by identifying hidden-layer activation patterns correlated with hum... read more 
Machine Learning q-bio.NC

Penguin-VL: Exploring the Efficiency Limits of VLM with LLM-based Vision Encoders

arXiv Mar 6, 2026
Vision Language Model (VLM) development has largely relied on scaling model size, which hinders deployment on compute-constrained mobile and edge devices such as smartphones and robots. In this work, we explore the performance limits of compact (e.g.... read more 
Computer Vision and Pattern Recognition

BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations

arXiv Mar 6, 2026
The integration of Large Language Models (LLMs) into autonomous driving has attracted growing interest for their strong reasoning and semantic understanding abilities, which are essential for handling complex decision-making and long-tail scenarios. ... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG cs.RO

Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion

arXiv Mar 6, 2026
While recent multimodal large language models (MLLMs) have made impressive strides, they predominantly employ a conventional autoregressive architecture as their backbone, leaving significant room to explore effective and efficient alternatives in ar... read more 
Computer Vision and Pattern Recognition

Multimodal Large Language Models as Image Classifiers

arXiv Mar 6, 2026
Multimodal Large Language Models (MLLM) classification performance depends critically on evaluation protocol and ground truth quality. Studies comparing MLLMs with supervised and vision-language models report conflicting conclusions, and we show thes... read more 
Computer Vision and Pattern Recognition

Layer-wise Instance Binding for Regional and Occlusion Control in Text-to-Image Diffusion Transformers

arXiv Mar 6, 2026
Region-instructed layout control in text-to-image generation is highly practical, yet existing methods suffer from limitations: (i) training-based approaches inherit data bias and often degrade image quality, and (ii) current techniques struggle with... read more 
Computer Vision and Pattern Recognition
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