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Prompt Learning

Papers

Showing 1–25 of 678 papers

TitleStatusHype
Hierarchical Cross-modal Prompt Learning for Vision-Language ModelsCode0
MGFFD-VLM: Multi-Granularity Prompt Learning for Face Forgery Detection with VLM—0
LifelongPR: Lifelong knowledge fusion for point cloud place recognition based on replay and prompt learningCode0
A Survey on Prompt TuningCode0
Integrated Structural Prompt Learning for Vision-Language Models—0
FA: Forced Prompt Learning of Vision-Language Models for Out-of-Distribution DetectionCode0
Visual and Memory Dual Adapter for Multi-Modal Object TrackingCode0
Multimodal Prompt Alignment for Facial Expression Recognition—0
Personalized Federated Learning via Dual-Prompt Optimization and Cross Fusion—0
DiMPLe -- Disentangled Multi-Modal Prompt Learning: Enhancing Out-Of-Distribution Alignment with Invariant and Spurious Feature Separation—0
Taming Vision-Language Models for Medical Image Analysis: A Comprehensive ReviewCode1
MorphSAM: Learning the Morphological Prompts from Atlases for Spine Image Segmentation—0
Prompt-Unseen-Emotion: Zero-shot Expressive Speech Synthesis with Prompt-LLM Contextual Knowledge for Mixed Emotions—0
An Empirical Study of Federated Prompt Learning for Vision Language Model—0
Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph LanguagesCode1
ValueSim: Generating Backstories to Model Individual Value Systems—0
SIPDO: Closed-Loop Prompt Optimization via Synthetic Data Feedback—0
DiSa: Directional Saliency-Aware Prompt Learning for Generalizable Vision-Language Models—0
Semantic-enhanced Co-attention Prompt Learning for Non-overlapping Cross-Domain RecommendationCode0
ICPL-ReID: Identity-Conditional Prompt Learning for Multi-Spectral Object Re-IdentificationCode0
Efficient Motion Prompt Learning for Robust Visual TrackingCode1
PL-FGSA: A Prompt Learning Framework for Fine-Grained Sentiment Analysis Based on MindSpore—0
ReSW-VL: Representation Learning for Surgical Workflow Analysis Using Vision-Language Model—0
EpiLLM: Unlocking the Potential of Large Language Models in Epidemic Forecasting—0
Incomplete In-context Learning—0
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