Artificial Intelligence Medical Compendium

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

Showing 52,991 to 53,000 of 225,341 articles

FloorplanVLM: A Vision-Language Model for Floorplan Vectorization

arXiv Feb 6, 2026
Converting raster floorplans into engineering-grade vector graphics is challenging due to complex topology and strict geometric constraints. To address this, we present FloorplanVLM, a unified framework that reformulates floorplan vectorization as an... read more 
Computer Vision and Pattern Recognition

Universal Anti-forensics Attack against Image Forgery Detection via Multi-modal Guidance

arXiv Feb 6, 2026
The rapid advancement of AI-Generated Content (AIGC) technologies poses significant challenges for authenticity assessment. However, existing evaluation protocols largely overlook anti-forensics attack, failing to ensure the comprehensive robustness ... read more 
Computer Vision and Pattern Recognition cs.CR

Evolving Ranking Functions for Canonical Blow-Ups in Positive Characteristic

arXiv Feb 6, 2026
Resolution of singularities in positive characteristic remains a long-standing open problem in algebraic geometry. In characteristic zero, the problem was solved by Hironaka in 1964, work for which he was awarded the Fields Medal. Modern proofs proce... read more 
Algebraic Geometry cs.LG

SPARC: Separating Perception And Reasoning Circuits for Test-time Scaling of VLMs

arXiv Feb 6, 2026
Despite recent successes, test-time scaling - i.e., dynamically expanding the token budget during inference as needed - remains brittle for vision-language models (VLMs): unstructured chains-of-thought about images entangle perception and reasoning, ... read more 
Computer Vision and Pattern Recognition cs.AI cs.CL

Transformer-based Parameter Fitting of Models derived from Bloch-McConnell Equations for CEST MRI Analysis

arXiv Feb 6, 2026
Chemical exchange saturation transfer (CEST) MRI is a non-invasive imaging modality for detecting metabolites. It offers higher resolution and sensitivity compared to conventional magnetic resonance spectroscopy (MRS). However, quantification of CEST... read more 
Machine Learning cs.AI

Exploring Sparsity and Smoothness of Arbitrary $\ell_p$ Norms in Adversarial Attacks

arXiv Feb 6, 2026
Adversarial attacks against deep neural networks are commonly constructed under $\ell_p$ norm constraints, most often using $p=1$, $p=2$ or $p=\infty$, and potentially regularized for specific demands such as sparsity or smoothness. These choices are... read more 
Machine Learning cs.AI

Target noise: A pre-training based neural network initialization for efficient high resolution learning

arXiv Feb 6, 2026
Weight initialization plays a crucial role in the optimization behavior and convergence efficiency of neural networks. Most existing initialization methods, such as Xavier and Kaiming initializations, rely on random sampling and do not exploit inform... read more 
Machine Learning cs.AI

ProtoQuant: Quantization of Prototypical Parts For General and Fine-Grained Image Classification

arXiv Feb 6, 2026
Prototypical parts-based models offer a "this looks like that" paradigm for intrinsic interpretability, yet they typically struggle with ImageNet-scale generalization and often require computationally expensive backbone finetuning. Furthermore, exist... read more 
Computer Vision and Pattern Recognition cs.AI

DiTS: Multimodal Diffusion Transformers Are Time Series Forecasters

arXiv Feb 6, 2026
While generative modeling on time series facilitates more capable and flexible probabilistic forecasting, existing generative time series models do not address the multi-dimensional properties of time series data well. The prevalent architecture of D... read more 
Machine Learning

The hidden risks of temporal resampling in clinical reinforcement learning

arXiv Feb 6, 2026
Offline reinforcement learning (ORL) has shown potential for improving decision-making in healthcare. However, contemporary research typically aggregates patient data into fixed time intervals, simplifying their mapping to standard ORL frameworks. Th... read more 
Machine Learning
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