Cover Image

AGA: An adaptive group alignment framework for structured medical cross-modal representation learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Wei, Gong, Xun, Li, Jiao, Sun, Xiaobin
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Evaluating alignment between humans and neural network representations in image-based learning tasks
by: Demircan, Can, et al.
Published: (2023)

A self-supervised framework for learning whole slide representations
by: Hou, Xinhai, et al.
Published: (2024)

Differential privacy representation geometry for medical image analysis
by: Arasteh, Soroosh Tayebi, et al.
Published: (2026)

Human alignment of neural network representations
by: Muttenthaler, Lukas, et al.
Published: (2022)

MonoCon: A general framework for learning ultra-compact high-fidelity representations using monotonicity constraints
by: Gokhale, Shreyas
Published: (2025)

How to select slices for annotation to train best-performing deep learning segmentation models for cross-sectional medical images?
by: Zhang, Yixin, et al.
Published: (2024)

Self-supervised video pretraining yields robust and more human-aligned visual representations
by: Parthasarathy, Nikhil, et al.
Published: (2022)

Multi-modal Co-learning for Earth Observation: Enhancing single-modality models via modality collaboration
by: Mena, Francisco, et al.
Published: (2025)

Training-inference input alignment outweighs framework choice in longitudinal retinal image prediction
by: Chen, Liyin, et al.
Published: (2026)

Cross-modal Affinity-aligned Multimodal Learning Analytics for Predicting Student Collaboration Satisfaction in Game-Based Learning
by: Tsai, Wen-Hsin, et al.
Published: (2026)

Can multimodal representation learning by alignment preserve modality-specific information?
by: Thoreau, Romain, et al.
Published: (2025)

Phantom: Subject-consistent video generation via cross-modal alignment
by: Liu, Lijie, et al.
Published: (2025)

Dimensions underlying the representational alignment of deep neural networks with humans
by: Mahner, Florian P., et al.
Published: (2024)

Visual Hallucinations of Multi-modal Large Language Models
by: Huang, Wen, et al.
Published: (2024)

What to align in multimodal contrastive learning?
by: Dufumier, Benoit, et al.
Published: (2024)

Closing the gap in multimodal medical representation alignment
by: Grassucci, Eleonora, et al.
Published: (2026)

SEPS: Semantic-enhanced Patch Slimming Framework for fine-grained cross-modal alignment
by: Mao, Xinyu, et al.
Published: (2025)

LoRA Subtraction for Drift-Resistant Space in Exemplar-Free Continual Learning
by: Liu, Xuan, et al.
Published: (2025)

Elastic Weight Consolidation Done Right for Continual Learning
by: Liu, Xuan, et al.
Published: (2026)

PR3DICTR: A modular AI framework for medical 3D image-based detection and outcome prediction
by: MacRae, Daniel C., et al.
Published: (2026)

What explains the success of cross-modal fine-tuning with ORCA?
by: García-de-Herreros, Paloma, et al.
Published: (2024)

PaSE: Prototype-aligned Calibration and Shapley-based Equilibrium for Multimodal Sentiment Analysis
by: He, Kang, et al.
Published: (2025)

Mitigating Visual Forgetting via Take-along Visual Conditioning for Multi-modal Long CoT Reasoning
by: Sun, Hai-Long, et al.
Published: (2025)

REFORGE: Multi-modal Attacks Reveal Vulnerable Concept Unlearning in Image Generation Models
by: Zou, Yong, et al.
Published: (2026)

CFM: Language-aligned Concept Foundation Model for Vision
by: Wittenmayer, Kai, et al.
Published: (2026)

VaPR -- Vision-language Preference alignment for Reasoning
by: Wadhawan, Rohan, et al.
Published: (2025)

MMS-VPR: Multimodal Street-Level Visual Place Recognition Dataset and Benchmark
by: Ou, Yiwei, et al.
Published: (2025)

Explore the Limits of Omni-modal Pretraining at Scale
by: Zhang, Yiyuan, et al.
Published: (2024)

Boosting multi-demographic federated learning for chest radiograph analysis using general-purpose self-supervised representations
by: Lotfinia, Mahshad, et al.
Published: (2025)

Simultaneous Long-tailed Recognition and Multi-modal Fusion for Highly Imbalanced Multi-modal Data
by: Yoon, Heegeon, et al.
Published: (2026)

Self-learned representation-guided latent diffusion model for breast cancer classification in deep ultraviolet whole surface images
by: Afshin, Pouya, et al.
Published: (2026)

SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning
by: Zhao, Shuai, et al.
Published: (2025)

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion
by: Huang, Xun, et al.
Published: (2025)

Uni-Med: A Unified Medical Generalist Foundation Model For Multi-Task Learning Via Connector-MoE
by: Zhu, Xun, et al.
Published: (2024)

Refusing Safe Prompts for Multi-modal Large Language Models
by: Shao, Zedian, et al.
Published: (2024)

Vision Transformer attention alignment with human visual perception in aesthetic object evaluation
by: Carrasco, Miguel, et al.
Published: (2025)

R2GenKG: Hierarchical Multi-modal Knowledge Graph for LLM-based Radiology Report Generation
by: Wang, Futian, et al.
Published: (2025)

AI-based association analysis for medical imaging using latent-space geometric confounder correction
by: Liu, Xianjing, et al.
Published: (2023)

Disentangled representations of microscopy images
by: Dapueto, Jacopo, et al.
Published: (2025)

Enhancing multimodal cooperation via sample-level modality valuation
by: Wei, Yake, et al.
Published: (2023)