Artificial Intelligence Medical Compendium

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

Showing 42,251 to 42,260 of 223,853 articles

MM-CondChain: A Programmatically Verified Benchmark for Visually Grounded Deep Compositional Reasoning

arXiv Mar 12, 2026
Multimodal Large Language Models (MLLMs) are increasingly used to carry out visual workflows such as navigating GUIs, where the next step depends on verified visual compositional conditions (e.g., "if a permission dialog appears and the color of the ... read more 
Computer Vision and Pattern Recognition

VQQA: An Agentic Approach for Video Evaluation and Quality Improvement

arXiv Mar 12, 2026
Despite rapid advancements in video generation models, aligning their outputs with complex user intent remains challenging. Existing test-time optimization methods are typically either computationally expensive or require white-box access to model in... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG cs.MA

Probabilistic Joint and Individual Variation Explained (ProJIVE) for Data Integration

arXiv Mar 12, 2026
Collecting multiple types of data on the same set of subjects is common in modern scientific applications including, genomics, metabolomics, and neuroimaging. Joint and Individual Variance Explained (JIVE) seeks a low-rank approximation of the joint ... read more 
Machine Learning cs.LG q-bio.QM stat.CO stat.ME

Optimal Experimental Design for Reliable Learning of History-Dependent Constitutive Laws

arXiv Mar 12, 2026
History-dependent constitutive models serve as macroscopic closures for the aggregated effects of micromechanics. Their parameters are typically learned from experimental data. With a limited experimental budget, eliciting the full range of responses... read more 
Materials Science cs.LG math.NA physics.comp-ph stat.CO

Human Knowledge Integrated Multi-modal Learning for Single Source Domain Generalization

arXiv Mar 12, 2026
Generalizing image classification across domains remains challenging in critical tasks such as fundus image-based diabetic retinopathy (DR) grading and resting-state fMRI seizure onset zone (SOZ) detection. When domains differ in unknown causal facto... read more 
Computer Vision and Pattern Recognition

SPARROW: Learning Spatial Precision and Temporal Referential Consistency in Pixel-Grounded Video MLLMs

arXiv Mar 12, 2026
Multimodal large language models (MLLMs) have advanced from image-level reasoning to pixel-level grounding, but extending these capabilities to videos remains challenging as models must achieve spatial precision and temporally consistent reference tr... read more 
Computer Vision and Pattern Recognition cs.AI

Deployment-Oriented Session-wise Meta-Calibration for Landmark-Based Webcam Gaze Tracking

arXiv Mar 12, 2026
Practical webcam gaze tracking is constrained not only by error, but also by calibration burden, robustness to head motion and session drift, runtime footprint, and browser use. We therefore target a deployment-oriented operating point rather than th... read more 
Computer Vision and Pattern Recognition cs.HC

ABRA: Teleporting Fine-Tuned Knowledge Across Domains for Open-Vocabulary Object Detection

arXiv Mar 12, 2026
Although recent Open-Vocabulary Object Detection architectures, such as Grounding DINO, demonstrate strong zero-shot capabilities, their performance degrades significantly under domain shifts. Moreover, many domains of practical interest, such as nig... read more 
Computer Vision and Pattern Recognition

Surg-R1: A Hierarchical Reasoning Foundation Model for Scalable and Interpretable Surgical Decision Support with Multi-Center Clinical Validation

arXiv Mar 12, 2026
Surgical scene understanding demands not only accurate predictions but also interpretable reasoning that surgeons can verify against clinical expertise. However, existing surgical vision-language models generate predictions without reasoning chains, ... read more 
Computer Vision and Pattern Recognition

Unmasking Biases and Reliability Concerns in Convolutional Neural Networks Analysis of Cancer Pathology Images

arXiv Mar 12, 2026
Convolutional Neural Networks have shown promising effectiveness in identifying different types of cancer from radiographs. However, the opaque nature of CNNs makes it difficult to fully understand the way they operate, limiting their assessment to e... read more 
Image and Video Processing cs.AI cs.CV cs.LG
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