SOTAVerified

Prompt Learning

Papers

Showing 201225 of 678 papers

TitleStatusHype
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly DetectionCode1
Robust Calibration of Large Vision-Language AdaptersCode1
Lifelong Knowledge Editing for LLMs with Retrieval-Augmented Continuous Prompt LearningCode1
Say More with Less: Understanding Prompt Learning Behaviors through Gist CompressionCode1
Multi-dimensional Visual Prompt Enhanced Image Restoration via Mamba-Transformer AggregationCode1
Semantic Prompt Learning for Weakly-Supervised Semantic SegmentationCode1
Prompt to Restore, Restore to Prompt: Cyclic Prompting for Universal Adverse Weather RemovalCode1
Harmonizing Generalization and Personalization in Federated Prompt LearningCode1
S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental LearningCode1
Taming Vision-Language Models for Medical Image Analysis: A Comprehensive ReviewCode1
CPL: Counterfactual Prompt Learning for Vision and Language Models0
Automated Prompting for Non-overlapping Cross-domain Sequential Recommendation0
AutoCas: Autoregressive Cascade Predictor in Social Networks via Large Language Models0
Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging0
COOL: Comprehensive Knowledge Enhanced Prompt Learning for Domain Adaptive Few-shot Fake News Detection0
Hierarchical Prompt Learning for Multi-Task Learning0
ControlRec: Bridging the Semantic Gap between Language Model and Personalized Recommendation0
Controllable Image Captioning via Prompting0
Contrastive Prompt Learning-based Code Search based on Interaction Matrix0
A Unified Graph Selective Prompt Learning for Graph Neural Networks0
HierPromptLM: A Pure PLM-based Framework for Representation Learning on Heterogeneous Text-rich Networks0
CoPL: Contextual Prompt Learning for Vision-Language Understanding0
A Unified Generative Framework based on Prompt Learning for Various Information Extraction Tasks0
Contextual Biasing of Named-Entities with Large Language Models0
Context-Aware Prompt Tuning for Vision-Language Model with Dual-Alignment0
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