Artificial Intelligence Medical Compendium

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

Showing 45,111 to 45,120 of 224,055 articles

From Shallow to Deep: Pinning Semantic Intent via Causal GRPO

arXiv Mar 3, 2026
Large Language Models remain vulnerable to adversarial prefix attacks (e.g., ``Sure, here is'') despite robust standard safety. We diagnose this vulnerability as Shallow Safety Alignment, stemming from a pathology we term semantic representation deca... read more 
Machine Learning

ReCo-Diff: Residual-Conditioned Deterministic Sampling for Cold Diffusion in Sparse-View CT

arXiv Mar 3, 2026
Cold and generalized diffusion models have recently shown strong potential for sparse-view CT reconstruction by explicitly modeling deterministic degradation processes. However, existing sampling strategies often rely on ad hoc sampling controls or f... read more 
Computer Vision and Pattern Recognition

FiDeSR: High-Fidelity and Detail-Preserving One-Step Diffusion Super-Resolution

arXiv Mar 3, 2026
Diffusion-based approaches have recently driven remarkable progress in real-world image super-resolution (SR). However, existing methods still struggle to simultaneously preserve fine details and ensure high-fidelity reconstruction, often resulting i... read more 
Computer Vision and Pattern Recognition

Intelligent Pathological Diagnosis of Gestational Trophoblastic Diseases via Visual-Language Deep Learning Model

arXiv Mar 3, 2026
The pathological diagnosis of gestational trophoblastic disease(GTD) takes a long time, relies heavily on the experience of pathologists, and the consistency of initial diagnosis is low, which seriously threatens maternal health and reproductive outc... read more 
Computer Vision and Pattern Recognition cs.AI

MiM-DiT: MoE in MoE with Diffusion Transformers for All-in-One Image Restoration

arXiv Mar 3, 2026
All-in-one image restoration is challenging because different degradation types, such as haze, blur, noise, and low-light, impose diverse requirements on restoration strategies, making it difficult for a single model to handle them effectively. In th... read more 
Computer Vision and Pattern Recognition

From "What" to "How": Constrained Reasoning for Autoregressive Image Generation

arXiv Mar 3, 2026
Autoregressive image generation has seen recent improvements with the introduction of chain-of-thought and reinforcement learning. However, current methods merely specify "What" details to depict by rewriting the input prompt, yet fundamentally fail ... read more 
Computer Vision and Pattern Recognition cs.MM eess.IV

An Empirical Analysis of Calibration and Selective Prediction in Multimodal Clinical Condition Classification

arXiv Mar 3, 2026
As artificial intelligence systems move toward clinical deployment, ensuring reliable prediction behavior is fundamental for safety-critical decision-making tasks. One proposed safeguard is selective prediction, where models can defer uncertain predi... read more 
Machine Learning

Cross-view geo-localization, Image retrieval, Multiscale geometric modeling, Frequency domain enhancement

arXiv Mar 3, 2026
Cross-view geo-localization (CVGL) aims to establish spatial correspondences between images captured from significantly different viewpoints and constitutes a fundamental technique for visual localization in GNSS-denied environments. Nevertheless, CV... read more 
Computer Vision and Pattern Recognition

Gated Differential Linear Attention: A Linear-Time Decoder for High-Fidelity Medical Segmentation

arXiv Mar 3, 2026
Medical image segmentation requires models that preserve fine anatomical boundaries while remaining efficient for clinical deployment. While transformers capture long-range dependencies, they suffer from quadratic attention cost and large data requir... read more 
Computer Vision and Pattern Recognition

CoShadow: Multi-Object Shadow Generation for Image Compositing via Diffusion Model

arXiv Mar 3, 2026
Realistic shadow generation is crucial for achieving seamless image compositing, yet existing methods primarily focus on single-object insertion and often fail to generalize when multiple foreground objects are composited into a background scene. In ... read more 
Computer Vision and Pattern Recognition
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