Image de couverture de livre

Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Shi, Jiang-Xin, Zhang, Chi, Wei, Tong, Li, Yu-Feng
Format:	Preprint
Publié:	2024
Sujets:	Computer Vision and Pattern Recognition Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

LIFT+: Lightweight Fine-Tuning for Long-Tail Learning
par: Shi, Jiang-Xin, et autres
Publié: (2025)

Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
par: Shi, Jiang-Xin, et autres
Publié: (2023)

Unleashing the Power of Vision-Language Models for Long-Tailed Multi-Label Visual Recognition
par: Tang, Wei, et autres
Publié: (2025)

Vision-Language Models are Strong Noisy Label Detectors
par: Wei, Tong, et autres
Publié: (2024)

Long-Tailed Object Detection Pre-training: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction
par: Duan, Chen-Long, et autres
Publié: (2024)

Learning to Rank Pre-trained Vision-Language Models for Downstream Tasks
par: Ding, Yuhe, et autres
Publié: (2024)

IMITATE: Clinical Prior Guided Hierarchical Vision-Language Pre-training
par: Liu, Che, et autres
Publié: (2023)

TiMix: Text-aware Image Mixing for Effective Vision-Language Pre-training
par: Jiang, Chaoya, et autres
Publié: (2023)

Split Adaptation for Pre-trained Vision Transformers
par: Wang, Lixu, et autres
Publié: (2025)

The Neglected Tails in Vision-Language Models
par: Parashar, Shubham, et autres
Publié: (2024)

Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models
par: Peng, Bo, et autres
Publié: (2026)

CAPT: Class-Aware Prompt Tuning for Federated Long-Tailed Learning with Vision-Language Model
par: Hou, Shihao, et autres
Publié: (2025)

Practical Continual Forgetting for Pre-trained Vision Models
par: Zhao, Hongbo, et autres
Publié: (2025)

Visual Perturbation and Adaptive Hard Negative Contrastive Learning for Compositional Reasoning in Vision-Language Models
par: Huang, Xin, et autres
Publié: (2025)

Dynamic Cluster Data Sampling for Efficient and Long-Tail-Aware Vision-Language Pre-training
par: Liang, Mingliang, et autres
Publié: (2026)

How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey
par: Qi, Yayun, et autres
Publié: (2024)

Taming the Long Tail: Rebalancing Adversarial Training via Adaptive Perturbation
par: Zhang, Lilin, et autres
Publié: (2026)

Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-training Objective
par: Verma, Sahil, et autres
Publié: (2023)

VisionTS++: Cross-Modal Time Series Foundation Model with Continual Pre-trained Vision Backbones
par: Shen, Lefei, et autres
Publié: (2025)

EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE
par: Chen, Junyi, et autres
Publié: (2023)

Multimodal Autoregressive Pre-training of Large Vision Encoders
par: Fini, Enrico, et autres
Publié: (2024)

Learning from Reduced Labels for Long-Tailed Data
par: Wei, Meng, et autres
Publié: (2024)

Feedback-based Modal Mutual Search for Attacking Vision-Language Pre-training Models
par: Ding, Renhua, et autres
Publié: (2024)

Light-weight Fine-tuning Method for Defending Adversarial Noise in Pre-trained Medical Vision-Language Models
par: Han, Xu, et autres
Publié: (2024)

NLPrompt: Noise-Label Prompt Learning for Vision-Language Models
par: Pan, Bikang, et autres
Publié: (2024)

D4C: Data-Free Quantization for Contrastive Language-Image Pre-training Models
par: Zhang, Wenlun, et autres
Publié: (2025)

Source-Free Domain Adaptation Guided by Vision and Vision-Language Pre-Training
par: Zhang, Wenyu, et autres
Publié: (2024)

Cross-Modal Adapter: Parameter-Efficient Transfer Learning Approach for Vision-Language Models
par: Yang, Juncheng, et autres
Publié: (2024)

Heavy-Tailed Class-Conditional Priors for Long-Tailed Generative Modeling
par: Bouayed, Aymene Mohammed, et autres
Publié: (2025)

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training
par: Chen, Yangyi, et autres
Publié: (2025)

VisionPAD: A Vision-Centric Pre-training Paradigm for Autonomous Driving
par: Zhang, Haiming, et autres
Publié: (2024)

Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real Images
par: Liu, Che, et autres
Publié: (2023)

One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models
par: Li, Lin, et autres
Publié: (2024)

Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey and Benchmark
par: Xin, Yi, et autres
Publié: (2024)

Long-Tailed Out-of-Distribution Detection with Refined Separate Class Learning
par: Feng, Shuai, et autres
Publié: (2025)

Pre-trained Vision-Language Models Learn Discoverable Visual Concepts
par: Zang, Yuan, et autres
Publié: (2024)

Efficient Long-Tail Learning in Latent Space by sampling Synthetic Data
par: Sharma, Nakul
Publié: (2025)

Resilient Contrastive Pre-training under Non-Stationary Drift
par: Yang, Xiaoyu, et autres
Publié: (2025)

What Makes CLIP More Robust to Long-Tailed Pre-Training Data? A Controlled Study for Transferable Insights
par: Wen, Xin, et autres
Publié: (2024)

Freeze the backbones: A Parameter-Efficient Contrastive Approach to Robust Medical Vision-Language Pre-training
par: Qin, Jiuming, et autres
Publié: (2024)