Artificial Intelligence Medical Compendium

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

Showing 49,641 to 49,650 of 224,513 articles

CT-Bench: A Benchmark for Multimodal Lesion Understanding in Computed Tomography

arXiv Feb 16, 2026
Artificial intelligence (AI) can automatically delineate lesions on computed tomography (CT) and generate radiology report content, yet progress is limited by the scarcity of publicly available CT datasets with lesion-level annotations. To bridge thi... read more 
Computer Vision and Pattern Recognition cs.AI

Web-Scale Multimodal Summarization using CLIP-Based Semantic Alignment

arXiv Feb 16, 2026
We introduce Web-Scale Multimodal Summarization, a lightweight framework for generating summaries by combining retrieved text and image data from web sources. Given a user-defined topic, the system performs parallel web, news, and image searches. Ret... read more 
Machine Learning cs.CV cs.ET cs.HC cs.NE

Picking the Right Specialist: Attentive Neural Process-based Selection of Task-Specialized Models as Tools for Agentic Healthcare Systems

arXiv Feb 16, 2026
Task-specialized models form the backbone of agentic healthcare systems, enabling the agents to answer clinical queries across tasks such as disease diagnosis, localization, and report generation. Yet, for a given task, a single "best" model rarely e... read more 
Machine Learning cs.AI cs.CV cs.MA

Wrivinder: Towards Spatial Intelligence for Geo-locating Ground Images onto Satellite Imagery

arXiv Feb 16, 2026
Aligning ground-level imagery with geo-registered satellite maps is crucial for mapping, navigation, and situational awareness, yet remains challenging under large viewpoint gaps or when GPS is unreliable. We introduce Wrivinder, a zero-shot, geometr... read more 
Computer Vision and Pattern Recognition

Activation-Space Uncertainty Quantification for Pretrained Networks

arXiv Feb 16, 2026
Reliable uncertainty estimates are crucial for deploying pretrained models; yet, many strong methods for quantifying uncertainty require retraining, Monte Carlo sampling, or expensive second-order computations and may alter a frozen backbone's predic... read more 
Machine Learning cs.LG

PAct: Part-Decomposed Single-View Articulated Object Generation

arXiv Feb 16, 2026
Articulated objects are central to interactive 3D applications, including embodied AI, robotics, and VR/AR, where functional part decomposition and kinematic motion are essential. Yet producing high-fidelity articulated assets remains difficult to sc... read more 
Computer Vision and Pattern Recognition cs.RO

ThermEval: A Structured Benchmark for Evaluation of Vision-Language Models on Thermal Imagery

arXiv Feb 16, 2026
Vision language models (VLMs) achieve strong performance on RGB imagery, but they do not generalize to thermal images. Thermal sensing plays a critical role in settings where visible light fails, including nighttime surveillance, search and rescue, a... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees

arXiv Feb 16, 2026
Diffusion models over discrete spaces have recently shown striking empirical success, yet their theoretical foundations remain incomplete. In this paper, we study the sampling efficiency of score-based discrete diffusion models under a continuous-tim... read more 
Machine Learning cs.IT math.ST stat.ML

Cold-Start Personalization via Training-Free Priors from Structured World Models

arXiv Feb 16, 2026
Cold-start personalization requires inferring user preferences through interaction when no user-specific historical data is available. The core challenge is a routing problem: each task admits dozens of preference dimensions, yet individual users car... read more 
Computation and Language cs.AI cs.LG

Image Generation with a Sphere Encoder

arXiv Feb 16, 2026
We introduce the Sphere Encoder, an efficient generative framework capable of producing images in a single forward pass and competing with many-step diffusion models using fewer than five steps. Our approach works by learning an encoder that maps nat... read more 
Computer Vision and Pattern Recognition
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