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Prompt Learning

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Showing 1–50 of 678 papers

TitleStatusHype
DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset CurationCode5
Awesome Multi-modal Object TrackingCode5
Do LLMs Possess a Personality? Making the MBTI Test an Amazing Evaluation for Large Language ModelsCode4
Conditional Prompt Learning for Vision-Language ModelsCode4
ATPrompt: Textual Prompt Learning with Embedded AttributesCode3
Cascade Prompt Learning for Vision-Language Model AdaptationCode3
Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing CommunityCode3
ControlMLLM: Training-Free Visual Prompt Learning for Multimodal Large Language ModelsCode3
Low-Rank Few-Shot Adaptation of Vision-Language ModelsCode3
PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly DetectionCode3
PromptKD: Unsupervised Prompt Distillation for Vision-Language ModelsCode3
MotionGPT: Human Motion as a Foreign LanguageCode3
CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive SurveyCode2
Rethinking Vision-Language Model in Face Forensics: Multi-Modal Interpretable Forged Face DetectorCode2
NLPrompt: Noise-Label Prompt Learning for Vision-Language ModelsCode2
Forensics Adapter: Unleashing CLIP for Generalizable Face Forgery DetectionCode2
BiomedCoOp: Learning to Prompt for Biomedical Vision-Language ModelsCode2
Contourlet Refinement Gate Framework for Thermal Spectrum Distribution Regularized Infrared Image Super-ResolutionCode2
Golden Noise for Diffusion Models: A Learning FrameworkCode2
Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational PathologyCode2
Perceive-IR: Learning to Perceive Degradation Better for All-in-One Image RestorationCode2
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure ModelingCode2
LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token EmbeddingsCode2
BAPLe: Backdoor Attacks on Medical Foundational Models using Prompt LearningCode2
ColorPeel: Color Prompt Learning with Diffusion Models via Color and Shape DisentanglementCode2
Multimodal Prompt Learning with Missing Modalities for Sentiment Analysis and Emotion RecognitionCode2
Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge DistillationCode2
GalLoP: Learning Global and Local Prompts for Vision-Language ModelsCode2
FinePOSE: Fine-Grained Prompt-Driven 3D Human Pose Estimation via Diffusion ModelsCode2
On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?Code2
Learning Transferable Negative Prompts for Out-of-Distribution DetectionCode2
S^2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series ForecastingCode2
Global and Local Prompts Cooperation via Optimal Transport for Federated LearningCode2
A Hard-to-Beat Baseline for Training-free CLIP-based AdaptationCode2
Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning StrategyCode2
Unsupervised Continual Anomaly Detection with Contrastively-learned PromptCode2
Graph Prompt Learning: A Comprehensive Survey and BeyondCode2
Source-Free Domain Adaptation with Frozen Multimodal Foundation ModelCode2
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly DetectionCode2
MVDream: Multi-view Diffusion for 3D GenerationCode2
Turning a CLIP Model into a Scene Text SpotterCode2
Self-regulating Prompts: Foundational Model Adaptation without ForgettingCode2
RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation ModelCode2
Visual Prompt Multi-Modal TrackingCode2
Decoupling Knowledge from Memorization: Retrieval-augmented Prompt LearningCode2
PromptDet: Towards Open-vocabulary Detection using Uncurated ImagesCode2
OpenPrompt: An Open-source Framework for Prompt-learningCode2
Learning to Prompt for Vision-Language ModelsCode2
Taming Vision-Language Models for Medical Image Analysis: A Comprehensive ReviewCode1
Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph LanguagesCode1
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