Artificial Intelligence Medical Compendium

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

Showing 18,691 to 18,700 of 214,544 articles

Angel or Demon: Investigating the Plasticity Interventions' Impact on Backdoor Threats in Deep Reinforcement Learning

arXiv May 14, 2026
Extensive research has highlighted the severe threats posed by backdoor attacks to deep reinforcement learning (DRL). However, prior studies primarily focus on vanilla scenarios, while plasticity interventions have emerged as indispensable built-in c... read more 
Machine Learning cs.AI cs.CR

FedStain: Modeling Higher-Order Stain Statistics for Federated Domain Generalization in Computational Pathology

arXiv May 14, 2026
Robust whole-slide image (WSI) analysis under strict data-governance remains challenging due to substantial cross-institutional stain heterogeneity. Domain generalization (DG) mitigates these shifts but typically requires centralized data, conflictin... read more 
Computer Vision and Pattern Recognition

TOPOS: High-Fidelity and Efficient Industry-Grade 3D Head Generation

arXiv May 14, 2026
High-fidelity 3D head generation plays a crucial role in the film, animation and video game industries. In industrial pipelines, studios typically enforce a fixed reference topology across all head assets, as such a clean and uniform topology is a pr... read more 
Computer Vision and Pattern Recognition cs.GR

ViMU: Benchmarking Video Metaphorical Understanding

arXiv May 14, 2026
Any new medium, once it emerges, is used for more than the transmission of overt content alone. The information it carries typically operates on two levels: one is the content directly presented, while the other is the subtext beneath it-the implicit... read more 
Computer Vision and Pattern Recognition cs.CY

Deep Image Segmentation via Discriminant Feature Learning

arXiv May 14, 2026
Accurate image segmentation remains challenging, particularly in generating sharp, confident boundaries. While modern architectures have advanced the field, many of them still rely on standard loss functions like Cross-Entropy and Dice, which often n... read more 
Computer Vision and Pattern Recognition cs.LG

Do We Really Need External Tools to Mitigate Hallucinations? SIRA: Shared-Prefix Internal Reconstruction of Attribution

arXiv May 14, 2026
Large vision-language models (LVLMs) often hallucinate when language priors dominate weak or ambiguous visual evidence. Existing contrastive decoding methods mitigate this problem by comparing predictions from the original image with those from exter... read more 
Computer Vision and Pattern Recognition cs.AI cs.CL

UniTriGen: Unified Triplet Generation of Aligned Visible-Infrared-Label for Few-Shot RGB-T Semantic Segmentation

arXiv May 14, 2026
RGB-T semantic segmentation requires strictly aligned VIS-IR-Label triplets; however, such aligned triplet data are often scarce in real-world scenarios. Existing generative augmentation methods usually adopt cascaded generation paradigms, decomposin... read more 
Computer Vision and Pattern Recognition

MultiEmo-Bench: Multi-label Visual Emotion Analysis for Multi-modal Large Language Models

arXiv May 14, 2026
This paper introduces a multi-label visual emotion analysis benchmark dataset for comprehensively evaluating the ability of multimodal large language models (MLLMs) to predict the emotions evoked by images. Recent user studies report an unintuitive f... read more 
Computer Vision and Pattern Recognition cs.AI

TERRA-CD: Multi-Temporal Framework for Multi-class and Semantic Change Detection

arXiv May 14, 2026
Urban vegetation monitoring plays a vital role in understanding environmental changes, yet comprehensive datasets for this purpose remain limited. To address this gap, we present the Temporal Remote-sensing Repository for Analyzing Change Detection (... read more 
Computer Vision and Pattern Recognition

Beyond Instance-Level Self-Supervision in 3D Multi-Modal Medical Imaging

arXiv May 14, 2026
Self-supervised pre-training methods in medical imaging typically treat each individual as an isolated instance, learning representations through augmentation-based objectives or masked reconstruction. They often do not adequately capitalize on a key... read more 
Computer Vision and Pattern Recognition
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