Prompt Tuning Papers

• Exploring Prompt-based Few-shot Learning for Grounded Dialog Generation
• Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
• Few-Shot Bot: Prompt-Based Learning for Dialogue Systems
• Language Models are Few-Shot Learners
• Surface Form Competition: Why the Highest Probability Answer Isn't Always Right
• KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction
• Text Generation with Efficient (Soft) Q-Learning
• Multitask Prompted Training Enables Zero-shot Task Generalization
• Pre-Trained Models: Past, Present and Future
• Learning To Prompt For Vision-language Models
• Towards A Unified View Of Parameter-efficient Transfer Learning
• Cross-Task Generalization via Natural Language Crowdsourcing Instructions
• WARP: Word-level Adversarial ReProgramming
• GPT Understands, Too
• Prefix-Tuning: Optimizing Continuous Prompts for Generation
• Prompt-Learning for Fine-Grained Entity Typing
• Noisy Channel Language Model Prompting for Few-Shot Text Classification
• Making Pre-trained Language Models Better Few-shot Learners
• Exploring Low-dimensional Intrinsic Task Subspace via Prompt Tuning
• Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
• P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
• Finetuned Language Models Are Zero-shot Learners
• Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
• How Many Data Points is a PromptWorth?
• Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
• Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning
• CPT: Colorful Prompt Tuning For Pre-trained Vision-language Models
• Thinking Aloud: Dynamic Context Generation Improves Zero-Shot Reasoning Performance of GPT-2
• A Good Prompt Is Worth Millions of Parameters? Low-resource Prompt-based Learning for Vision-Language Models
• CONTROL PREFIXES for Text Generation
• Factual Probing Is [MASK]: Learning vs. Learning to Recall
• True Few-Shot Learning with Language Models
• Paradigm Shift in Natural Language Processing
• SentiPrompt: Sentiment Knowledge Enhanced Prompt-Tuning for Aspect-Based Sentiment Analysis
• Constrained Language Models Yield Few-Shot Semantic Parsers
• PTR: Prompt Tuning with Rules for Text Classification
• The Power of Prompt Tuning for Low-Resource Semantic Parsing
• Parameter-Efficient Transfer Learning for NLP
• Calibrate Before Use: Improving Few-Shot Performance of Language Models
• NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction
• Do Prompt-Based Models Really Understand the Meaning of their Prompts?
• AUTOPROMPT: Eliciting Knowledge from Language Models with Automatically Generated Prompts
• Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models
• Label Verbalization and Entailment for Effective Zero- and Few-Shot Relation Extraction
• Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning
• Revisiting Self-Training for Few-Shot Learning of Language Model
• The Power of Scale for Parameter-Efficient Prompt Tuning
• PPT: Pre-trained Prompt Tuning for Few-shot Learning
• Improving and Simplifying Pattern Exploiting Training
• Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
• GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation
• PADA: A Prompt-based Autoregressive Approach for Adaptation to Unseen Domains
• Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference
• How Can We Know What Language Models Know?
• It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners
• Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification
• MSP: Multi-Stage Prompting for Making Pre-trained Language Models Better Translators
• Template-free Prompt Tuning for Few-shot NER
• Learning How to Ask: Querying LMs with Mixtures of Soft Prompts
• What Makes Good In-Context Examples for GPT-3?
• Language Models as Knowledge Bases?
• Automatically IdentifyingWords That Can Serve as Labels for Few-Shot Text Classification
• Prompt Tuning or Fine-Tuning - Investigating Relational Knowledge in Pre-Trained Language Models
• Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm