Artificial Intelligence Medical Compendium

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

Showing 17,011 to 17,020 of 213,633 articles

Distilling Tabular Foundation Models for Structured Health Data

arXiv May 18, 2026
Tabular foundation models (TFMs) achieve strong performance on health datasets, but their inference cost and infrastructure requirements limit practical use. We study whether their predictive behavior can be transferred to lightweight tabular models ... read more 
Machine Learning cs.AI

Semantic Generative Tuning for Unified Multimodal Models

arXiv May 18, 2026
Unified multimodal models (UMMs) strive to consolidate visual understanding and visual generation within a single architecture. However, prevailing training paradigms independently optimize understanding via sparse text signals and generation through... read more 
Computer Vision and Pattern Recognition cs.AI

SafeDiffusion-R1: Online Reward Steering for Safe Diffusion Post-Training

arXiv May 18, 2026
Diffusion models have been widely studied for removing unsafe content learned during pre-training. Existing methods require expensive supervised data, either unsafe-text paired with safe-image groundtruth or negative/positive image pairs, making them... read more 
Computer Vision and Pattern Recognition

PIXLRelight: Controllable Relighting via Intrinsic Conditioning

arXiv May 18, 2026
We present PIXLRelight, a feed-forward approach for physically controllable single-image relighting. Existing methods either provide limited lighting control (e.g. through text or environment maps), accumulate errors when chaining inverse and forward... read more 
Computer Vision and Pattern Recognition cs.GR cs.LG

Spectral Progressive Diffusion for Efficient Image and Video Generation

arXiv May 18, 2026
Diffusion models have been shown to implicitly generate visual content autoregressively in the frequency domain, where low-frequency components are generated earlier in the denoising process while high-frequency details emerge only in later timesteps... read more 
Computer Vision and Pattern Recognition

Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation

arXiv May 18, 2026
Multimodal Large Language Models (MLLMs) still struggle with fine-grained visual understanding, where answers often depend on small but decisive evidence in the full image. We observe a regional-to-global perception gap: the same MLLM answers fine-gr... read more 
Computer Vision and Pattern Recognition cs.AI cs.CL cs.LG

ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop

arXiv May 18, 2026
Spatial intelligence unfolds through a perception-action loop: agents act to acquire observations, and reason about how observations vary as a function of action. Rather than passively processing what is seen, they actively uncover what is unseen - o... read more 
Computer Vision and Pattern Recognition cs.AI cs.CL cs.LG cs.RO

Aurora: Unified Video Editing with a Tool-Using Agent

arXiv May 18, 2026
Recent video editing models have converged on a unified conditioning design: a single diffusion transformer jointly consumes text, source video, and reference images, and one set of weights covers replacement, removal, style transfer, and reference-d... read more 
Computer Vision and Pattern Recognition

Can These Views Be One Scene? Evaluating Multiview 3D Consistency when 3D Foundation Models Hallucinate

arXiv May 18, 2026
Multiview 3D evaluation assumes that the images being scored are observations of one static 3D scene. This assumption can fail in NVS and sparse-view reconstruction: inputs or generated outputs may contain artifacts, outlier frames, repeated views, o... read more 
Computer Vision and Pattern Recognition

Patch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation

arXiv May 18, 2026
CNN- and Transformer-based architectures have achieved strong performance in medical image segmentation, but CNNs are limited in modeling long-range dependencies, while Transformers often suffer from quadratic computational and memory complexity. Sta... read more 
Computer Vision and Pattern Recognition
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