Artificial Intelligence Medical Compendium

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

Showing 29,031 to 29,040 of 219,647 articles

An Integrated Deep-Learning Framework for Peptide-Protein Interaction Prediction and Target-Conditioned Peptide Generation with ConGA-PePPI and TC-PepGen

arXiv Apr 20, 2026
Motivation: Peptide-protein interactions (PepPIs) are central to cellular regulation and peptide therapeutics, but experimental characterization remains too slow for large-scale screening. Existing methods usually emphasize either interaction predict... read more 
Machine Learning cs.AI

Asset Harvester: Extracting 3D Assets from Autonomous Driving Logs for Simulation

arXiv Apr 20, 2026
Closed-loop simulation is a core component of autonomous vehicle (AV) development, enabling scalable testing, training, and safety validation before real-world deployment. Neural scene reconstruction converts driving logs into interactive 3D environm... read more 
Computer Vision and Pattern Recognition cs.AI cs.GR cs.LG

Multi-Scale Reversible Chaos Game Representation: A Unified Framework for Sequence Classification

arXiv Apr 20, 2026
Biological classification with interpretability remains a challenging task. For this, we introduce a novel encoding framework, Multi-Scale Reversible Chaos Game Representation (MS-RCGR), that transforms biological sequences into multi-resolution geom... read more 
Machine Learning

XEmbodied: A Foundation Model with Enhanced Geometric and Physical Cues for Large-Scale Embodied Environments

arXiv Apr 20, 2026
Vision-Language-Action (VLA) models drive next-generation autonomous systems, but training them requires scalable, high-quality annotations from complex environments. Current cloud pipelines rely on generic vision-language models (VLMs) that lack geo... read more 
Computer Vision and Pattern Recognition cs.MM cs.RO

S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models

arXiv Apr 20, 2026
Vision-Language Models (VLMs) have demonstrated remarkable progress in single-image understanding, yet effective reasoning across multiple images remains challenging. We identify a critical capability gap in existing multi-image alignment approaches:... read more 
Computer Vision and Pattern Recognition

MetaCloak-JPEG: JPEG-Robust Adversarial Perturbation for Preventing Unauthorized DreamBooth-Based Deepfake Generation

arXiv Apr 20, 2026
The rapid progress of subject-driven text-to-image synthesis, and in particular DreamBooth, has enabled a consent-free deepfake pipeline: an adversary needs only 4-8 publicly available face images to fine-tune a personalized diffusion model and produ... read more 
Computer Vision and Pattern Recognition

Advancing Vision Transformer with Enhanced Spatial Priors

arXiv Apr 20, 2026
In recent years, the Vision Transformer (ViT) has garnered significant attention within the computer vision community. However, the core component of ViT, Self-Attention, lacks explicit spatial priors and suffers from quadratic computational complexi... read more 
Computer Vision and Pattern Recognition

AnchorSeg: Language Grounded Query Banks for Reasoning Segmentation

arXiv Apr 20, 2026
Reasoning segmentation requires models to ground complex, implicit textual queries into precise pixel-level masks. Existing approaches rely on a single segmentation token $\texttt{}$, whose hidden state implicitly encodes both semantic reasoning... read more 
Computer Vision and Pattern Recognition

A multimodal and temporal foundation model for virtual patient representations at healthcare system scale

arXiv Apr 20, 2026
Modern medicine generates vast multimodal data across siloed systems, yet no existing model integrates the full breadth and temporal depth of the clinical record into a unified patient representation. We introduce Apollo, a multimodal temporal founda... read more 
Machine Learning cs.AI cs.CL

Back into Plato's Cave: Examining Cross-modal Representational Convergence at Scale

arXiv Apr 20, 2026
The Platonic Representation Hypothesis suggests that neural networks trained on different modalities (e.g., text and images) align and eventually converge toward the same representation of reality. If true, this has significant implications for wheth... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG
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