Image de couverture de livre

Dropout Prompt Learning: Towards Robust and Adaptive Vision-Language Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Chen, Biao, Zuo, Lin, Jing, Mengmeng, He, Kunbin, Wang, Yuchen
Format:	Preprint
Publié:	2025
Sujets:	Computer Vision and Pattern Recognition Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Flexible ViG: Learning the Self-Saliency for Flexible Object Recognition
par: Zuo, Lin, et autres
Publié: (2024)

Multimodal Emotion Recognition with Vision-language Prompting and Modality Dropout
par: QI, Anbin, et autres
Publié: (2024)

Towards Robust Vision Transformer via Masked Adaptive Ensemble
par: Lin, Fudong, et autres
Publié: (2024)

Adversarial Prompt Distillation for Vision-Language Models
par: Luo, Lin, et autres
Publié: (2024)

AmPLe: Supporting Vision-Language Models via Adaptive-Debiased Ensemble Multi-Prompt Learning
par: Song, Fei, et autres
Publié: (2025)

Adaptive Dropout: Unleashing Dropout across Layers for Generalizable Image Super-Resolution
par: Xu, Hang, et autres
Publié: (2025)

SWAT: Sliding Window Adversarial Training for Gradual Domain Adaptation
par: Wang, Zixi, et autres
Publié: (2025)

Enhancing Vision-Language Model Reliability with Uncertainty-Guided Dropout Decoding
par: Fang, Yixiong, et autres
Publié: (2024)

Gram-Anchored Prompt Learning for Vision-Language Models via Second-Order Statistics
par: Chen, Minglei, et autres
Publié: (2026)

Energy-Driven Adaptive Visual Token Pruning for Efficient Vision-Language Models
par: He, Jialuo, et autres
Publié: (2026)

Prompt-Aware Adapter: Towards Learning Adaptive Visual Tokens for Multimodal Large Language Models
par: Zhang, Yue, et autres
Publié: (2024)

NAP-Tuning: Neural Augmented Prompt Tuning for Adversarially Robust Vision-Language Models
par: Zhang, Jiaming, et autres
Publié: (2025)

Domain-Invariant Prompt Learning for Vision-Language Models
par: Khoee, Arsham Gholamzadeh, et autres
Publié: (2026)

LPT: Less-overfitting Prompt Tuning for Vision-Language Model
par: Ding, Chenhao, et autres
Publié: (2024)

Adversarial Prompt Tuning for Vision-Language Models
par: Zhang, Jiaming, et autres
Publié: (2023)

Towards Calibrated Robust Fine-Tuning of Vision-Language Models
par: Oh, Changdae, et autres
Publié: (2023)

Training-Free Unsupervised Prompt for Vision-Language Models
par: Long, Sifan, et autres
Publié: (2024)

Temporal Reversal Regularization for Spiking Neural Networks: Hybrid Spatio-Temporal Invariance for Generalization
par: Zuo, Lin, et autres
Publié: (2024)

Attention Prompting on Image for Large Vision-Language Models
par: Yu, Runpeng, et autres
Publié: (2024)

WildVision: Evaluating Vision-Language Models in the Wild with Human Preferences
par: Lu, Yujie, et autres
Publié: (2024)

Navigating Beyond Dropout: An Intriguing Solution Towards Generalizable Image Super Resolution
par: Wang, Hongjun, et autres
Publié: (2024)

MapGPT: Map-Guided Prompting with Adaptive Path Planning for Vision-and-Language Navigation
par: Chen, Jiaqi, et autres
Publié: (2024)

PromptEcho: Annotation-Free Reward from Vision-Language Models for Text-to-Image Reinforcement Learning
par: Liu, Jinlong, et autres
Publié: (2026)

Evolving Prompt Adaptation for Vision-Language Models
par: Zhang, Enming, et autres
Publié: (2026)

Physical Prompt Injection Attacks on Large Vision-Language Models
par: Ling, Chen, et autres
Publié: (2026)

Subspace Alignment for Vision-Language Model Test-time Adaptation
par: Zeng, Zhichen, et autres
Publié: (2026)

Towards Accurate UAV Image Perception: Guiding Vision-Language Models with Stronger Task Prompts
par: Guo, Mingning, et autres
Publié: (2025)

Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding
par: Yuan, Liping, et autres
Publié: (2025)

Unlocking Vision-Language Models for Video Anomaly Detection via Fine-Grained Prompting
par: Zou, Shu, et autres
Publié: (2025)

Towards Adversarially Robust Vision-Language Models: Insights from Design Choices and Prompt Formatting Techniques
par: Bhagwatkar, Rishika, et autres
Publié: (2024)

VLM4D: Towards Spatiotemporal Awareness in Vision Language Models
par: Zhou, Shijie, et autres
Publié: (2025)

Prompt Tuning with Soft Context Sharing for Vision-Language Models
par: Ding, Kun, et autres
Publié: (2022)

Differentiable Prompt Learning for Vision Language Models
par: Huang, Zhenhan, et autres
Publié: (2024)

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

FDBPL: Faster Distillation-Based Prompt Learning for Region-Aware Vision-Language Models Adaptation
par: Zhang, Zherui, et autres
Publié: (2025)

Target Prompting for Information Extraction with Vision Language Model
par: Medhi, Dipankar
Publié: (2024)

Prompting Large Vision-Language Models for Compositional Reasoning
par: Ossowski, Timothy, et autres
Publié: (2024)

Bayesian Principles Improve Prompt Learning In Vision-Language Models
par: Kim, Mingyu, et autres
Publié: (2025)

VLM4VLA: Revisiting Vision-Language-Models in Vision-Language-Action Models
par: Zhang, Jianke, et autres
Publié: (2026)

Vision-and-Language Navigation via Causal Learning
par: Wang, Liuyi, et autres
Publié: (2024)