Artificial Intelligence Medical Compendium

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

Showing 41,601 to 41,610 of 223,853 articles

HalDec-Bench: Benchmarking Hallucination Detector in Image Captioning

arXiv Mar 16, 2026
Hallucination detection in captions (HalDec) assesses a vision-language model's ability to correctly align image content with text by identifying errors in captions that misrepresent the image. Beyond evaluation, effective hallucination detection is ... read more 
Computer Vision and Pattern Recognition

IConE: Batch Independent Collapse Prevention for Self-Supervised Representation Learning

arXiv Mar 16, 2026
Self-supervised learning (SSL) has revolutionized representation learning, with Joint-Embedding Architectures (JEAs) emerging as an effective approach for capturing semantic features. Existing JEAs rely on implicit or explicit batch interaction -- vi... read more 
Computer Vision and Pattern Recognition cs.LG

Exemplar Diffusion: Improving Medical Object Detection with Opportunistic Labels

arXiv Mar 16, 2026
We present a framework to take advantage of existing labels at inference, called \textit{exemplars}, in order to improve the performance of object detection in medical images. The method, \textit{exemplar diffusion}, leverages existing diffusion meth... read more 
Computer Vision and Pattern Recognition

Self-Supervised ImageNet Representations for In Vivo Confocal Microscopy: Tortuosity Grading without Segmentation Maps

arXiv Mar 16, 2026
The tortuosity of corneal nerve fibers are used as indication for different diseases. Current state-of-the-art methods for grading the tortuosity heavily rely on expensive segmentation maps of these nerve fibers. In this paper, we demonstrate that se... read more 
Computer Vision and Pattern Recognition

Flash-Unified: A Training-Free and Task-Aware Acceleration Framework for Native Unified Models

arXiv Mar 16, 2026
Native unified multimodal models, which integrate both generative and understanding capabilities, face substantial computational overhead that hinders their real-world deployment. Existing acceleration techniques typically employ a static, monolithic... read more 
Computer Vision and Pattern Recognition

Dataset Diversity Metrics and Impact on Classification Models

arXiv Mar 16, 2026
The diversity of training datasets is usually perceived as an important aspect to obtain a robust model. However, the definition of diversity is often not defined or differs across papers, and while some metrics exist, the quantification of this dive... read more 
Computer Vision and Pattern Recognition

Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling

arXiv Mar 16, 2026
Conditional Flow Matching (CFM), a simulation-free method for training continuous normalizing flows, provides an efficient alternative to diffusion models for key tasks like image and video generation. The performance of CFM in solving these tasks de... read more 
Machine Learning cs.CV

GATE-AD: Graph Attention Network Encoding For Few-Shot Industrial Visual Anomaly Detection

arXiv Mar 16, 2026
Few-Shot Industrial Visual Anomaly Detection (FS-IVAD) comprises a critical task in modern manufacturing settings, where automated product inspection systems need to identify rare defects using only a handful of normal/defect-free training samples. I... read more 
Computer Vision and Pattern Recognition

Data Augmentation via Causal-Residual Bootstrapping

arXiv Mar 16, 2026
Data augmentation integrates domain knowledge into a dataset by making domain-informed modifications to existing data points. For example, image data can be augmented by duplicating images in different tints or orientations, thereby incorporating the... read more 
Machine Learning

Oscillating Dispersion for Maximal Light-throughput Spectral Imaging

arXiv Mar 16, 2026
Existing computational spectral imaging systems typically rely on coded aperture and beam splitters that block a substantial fraction of incident light, degrading reconstruction quality under light-starved conditions. To address this limitation, we d... read more 
Computer Vision and Pattern Recognition
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