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Prompt Learning

Papers

Showing 526550 of 678 papers

TitleStatusHype
Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging0
Consistency-guided Prompt Learning for Vision-Language ModelsCode1
Multilingual Multi-Figurative Language DetectionCode1
Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement LearningCode1
Trompt: Towards a Better Deep Neural Network for Tabular Data0
Deeply Coupled Cross-Modal Prompt LearningCode1
The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image ClassificationCode1
PromptNER: Prompt Locating and Typing for Named Entity RecognitionCode1
Consistent Optimal Transport with Empirical Conditional MeasuresCode0
On the Robustness of Segment Anything0
Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models0
Federated Prompt Learning for Weather Foundation Models on DevicesCode1
Enhancing Cross-lingual Natural Language Inference by Soft Prompting with Multilingual VerbalizerCode0
SCP: Soft Conditional Prompt Learning for Aerial Video Action Recognition0
Bi-VLGM : Bi-Level Class-Severity-Aware Vision-Language Graph Matching for Text Guided Medical Image Segmentation0
Deep Learning Approaches to Lexical Simplification: A Survey0
TEPrompt: Task Enlightenment Prompt Learning for Implicit Discourse Relation RecognitionCode0
Discffusion: Discriminative Diffusion Models as Few-shot Vision and Language LearnersCode1
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt0
MsPrompt: Multi-step Prompt Learning for Debiasing Few-shot Event Detection0
Prompt-Tuning Decision Transformer with Preference Ranking0
Prompt Learning to Mitigate Catastrophic Forgetting in Cross-lingual Transfer for Open-domain Dialogue GenerationCode0
Multi-Prompt with Depth Partitioned Cross-Modal LearningCode0
Low-Resource Multi-Granularity Academic Function Recognition Based on Multiple Prompt Knowledge0
How to Unleash the Power of Large Language Models for Few-shot Relation Extraction?Code0
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