A Medical Data-Effective Learning Benchmark for Highly Efficient Pre-training of Foundation Models
Fuente:
arXiv
Saved in:
| Main Authors: | Yang, Wenxuan, Tan, Weimin, Sun, Yuqi, Yan, Bo |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MM-Skin: Enhancing Dermatology Vision-Language Model with an Image-Text Dataset Derived from Textbooks
by: Zeng, Wenqi, et al.
Published: (2025)
by: Zeng, Wenqi, et al.
Published: (2025)
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
by: Lai, Zhengfeng, et al.
Published: (2024)
by: Lai, Zhengfeng, et al.
Published: (2024)
CXPMRG-Bench: Pre-training and Benchmarking for X-ray Medical Report Generation on CheXpert Plus Dataset
by: Wang, Xiao, et al.
Published: (2024)
by: Wang, Xiao, et al.
Published: (2024)
Addressing Imbalance for Class Incremental Learning in Medical Image Classification
by: Hao, Xuze, et al.
Published: (2024)
by: Hao, Xuze, et al.
Published: (2024)
Pre-trained Vision-Language Models Learn Discoverable Visual Concepts
by: Zang, Yuan, et al.
Published: (2024)
by: Zang, Yuan, et al.
Published: (2024)
Benchmark Analysis of Various Pre-trained Deep Learning Models on ASSIRA Cats and Dogs Dataset
by: Himel, Galib Muhammad Shahriar, et al.
Published: (2024)
by: Himel, Galib Muhammad Shahriar, et al.
Published: (2024)
Region-Aware Reconstruction Strategy for Pre-training fMRI Foundation Model
by: Doodipala, Ruthwik Reddy, et al.
Published: (2025)
by: Doodipala, Ruthwik Reddy, et al.
Published: (2025)
A Self-Supervised Paradigm for Data-Efficient Medical Foundation Model Pre-training: V-information Optimization Framework
by: Yang, Wenxuan, et al.
Published: (2024)
by: Yang, Wenxuan, et al.
Published: (2024)
Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-training Objective
by: Verma, Sahil, et al.
Published: (2023)
by: Verma, Sahil, et al.
Published: (2023)
Navigating Data Scarcity using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging
by: Woerner, Stefano, et al.
Published: (2024)
by: Woerner, Stefano, et al.
Published: (2024)
Freeze the backbones: A Parameter-Efficient Contrastive Approach to Robust Medical Vision-Language Pre-training
by: Qin, Jiuming, et al.
Published: (2024)
by: Qin, Jiuming, et al.
Published: (2024)
Multi-modal Vision Pre-training for Medical Image Analysis
by: Rui, Shaohao, et al.
Published: (2024)
by: Rui, Shaohao, et al.
Published: (2024)
Boosting Omnidirectional Stereo Matching with a Pre-trained Depth Foundation Model
by: Endres, Jannik, et al.
Published: (2025)
by: Endres, Jannik, et al.
Published: (2025)
Slight Corruption in Pre-training Data Makes Better Diffusion Models
by: Chen, Hao, et al.
Published: (2024)
by: Chen, Hao, et al.
Published: (2024)
Retrieval-augmented Prompt Learning for Pre-trained Foundation Models
by: Chen, Xiang, et al.
Published: (2025)
by: Chen, Xiang, et al.
Published: (2025)
A Foundation Model for General Moving Object Segmentation in Medical Images
by: Yan, Zhongnuo, et al.
Published: (2023)
by: Yan, Zhongnuo, et al.
Published: (2023)
Benchmarking the Influence of Pre-training on Explanation Performance in MR Image Classification
by: Oliveira, Marta, et al.
Published: (2023)
by: Oliveira, Marta, et al.
Published: (2023)
Multimodal Medical Image Classification via Synergistic Learning Pre-training
by: Lin, Qinghua, et al.
Published: (2025)
by: Lin, Qinghua, et al.
Published: (2025)
Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation
by: Dong, Wei, et al.
Published: (2024)
by: Dong, Wei, et al.
Published: (2024)
Point-PEFT: Parameter-Efficient Fine-Tuning for 3D Pre-trained Models
by: Tang, Yiwen, et al.
Published: (2023)
by: Tang, Yiwen, et al.
Published: (2023)
Dataset Ownership Verification in Contrastive Pre-trained Models
by: Xie, Yuechen, et al.
Published: (2025)
by: Xie, Yuechen, et al.
Published: (2025)
Practical Continual Forgetting for Pre-trained Vision Models
by: Zhao, Hongbo, et al.
Published: (2025)
by: Zhao, Hongbo, et al.
Published: (2025)
Pre-training with Random Orthogonal Projection Image Modeling
by: Haghighat, Maryam, et al.
Published: (2023)
by: Haghighat, Maryam, et al.
Published: (2023)
Exploring the Efficacy of Meta-Learning: Unveiling Superior Data Diversity Utilization of MAML Over Pre-training
by: Selva, Kavita, et al.
Published: (2025)
by: Selva, Kavita, et al.
Published: (2025)
Benchmarking Foundation Models and Parameter-Efficient Fine-Tuning for Prognosis Prediction in Medical Imaging
by: Ruffini, Filippo, et al.
Published: (2025)
by: Ruffini, Filippo, et al.
Published: (2025)
Enhancing Multi-task Learning Capability of Medical Generalist Foundation Model via Image-centric Multi-annotation Data
by: Zhu, Xun, et al.
Published: (2025)
by: Zhu, Xun, et al.
Published: (2025)
Pre-training Vision Transformers with Formula-driven Supervised Learning
by: Kataoka, Hirokatsu, et al.
Published: (2022)
by: Kataoka, Hirokatsu, et al.
Published: (2022)
Can Medical Vision-Language Pre-training Succeed with Purely Synthetic Data?
by: Liu, Che, et al.
Published: (2024)
by: Liu, Che, et al.
Published: (2024)
Feedback-based Modal Mutual Search for Attacking Vision-Language Pre-training Models
by: Ding, Renhua, et al.
Published: (2024)
by: Ding, Renhua, et al.
Published: (2024)
Intra-Cluster Mixup: An Effective Data Augmentation Technique for Complementary-Label Learning
by: Mai, Tan-Ha, et al.
Published: (2025)
by: Mai, Tan-Ha, et al.
Published: (2025)
RGB-Event HyperGraph Prompt for Kilometer Marker Recognition based on Pre-trained Foundation Models
by: Xian, Xiaoyu, et al.
Published: (2026)
by: Xian, Xiaoyu, et al.
Published: (2026)
Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy
by: Yang, Yiting, et al.
Published: (2025)
by: Yang, Yiting, et al.
Published: (2025)
FacialFlowNet: Advancing Facial Optical Flow Estimation with a Diverse Dataset and a Decomposed Model
by: Lu, Jianzhi, et al.
Published: (2024)
by: Lu, Jianzhi, et al.
Published: (2024)
Fly-CL: A Fly-Inspired Framework for Enhancing Efficient Decorrelation and Reduced Training Time in Pre-trained Model-based Continual Representation Learning
by: Zou, Heming, et al.
Published: (2025)
by: Zou, Heming, et al.
Published: (2025)
LightFair: Towards an Efficient Alternative for Fair T2I Diffusion via Debiasing Pre-trained Text Encoders
by: Han, Boyu, et al.
Published: (2025)
by: Han, Boyu, et al.
Published: (2025)
NIL: No-data Imitation Learning by Leveraging Pre-trained Video Diffusion Models
by: Albaba, Mert, et al.
Published: (2025)
by: Albaba, Mert, et al.
Published: (2025)
Preserving Pre-trained Representation Space: On Effectiveness of Prefix-tuning for Large Multi-modal Models
by: Kim, Donghoon, et al.
Published: (2024)
by: Kim, Donghoon, et al.
Published: (2024)
Gradient-based Fine-Tuning through Pre-trained Model Regularization
by: Liu, Xuanbo, et al.
Published: (2025)
by: Liu, Xuanbo, et al.
Published: (2025)
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
by: Chu, Tianzhe, et al.
Published: (2025)
by: Chu, Tianzhe, et al.
Published: (2025)
Towards Efficient Benchmarking of Foundation Models in Remote Sensing: A Capabilities Encoding Approach
by: Adorni, Pierre, et al.
Published: (2025)
by: Adorni, Pierre, et al.
Published: (2025)
Similar Items
-
MM-Skin: Enhancing Dermatology Vision-Language Model with an Image-Text Dataset Derived from Textbooks
by: Zeng, Wenqi, et al.
Published: (2025) -
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
by: Lai, Zhengfeng, et al.
Published: (2024) -
CXPMRG-Bench: Pre-training and Benchmarking for X-ray Medical Report Generation on CheXpert Plus Dataset
by: Wang, Xiao, et al.
Published: (2024) -
Addressing Imbalance for Class Incremental Learning in Medical Image Classification
by: Hao, Xuze, et al.
Published: (2024) -
Pre-trained Vision-Language Models Learn Discoverable Visual Concepts
by: Zang, Yuan, et al.
Published: (2024)