papers.zh.mdx

论文

以下是关于提示工程的最新论文（按发布日期排序）。我们每天更新，新论文不断涌现。我们每周将这些论文的摘要整合到上面的指南中。

综述

• Nature Language Reasoning, A Survey (March 2023)
• Augmented Language Models: a Survey (Feb 2023)
• A Survey for In-context Learning (Dec 2022)
• Towards Reasoning in Large Language Models: A Survey (Dec 2022)
• Reasoning with Language Model Prompting: A Survey (Dec 2022)
• Emergent Abilities of Large Language Models (Jun 2022)
• A Taxonomy of Prompt Modifiers for Text-To-Image Generation (Apr 2022)
• Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing (Jul 2021)

方法

• Self-Refine: Iterative Refinement with Self-Feedback (Mar 2023)
• kNN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference (Mar 2023)
• Visual-Language Prompt Tuning with Knowledge-guided Context Optimization (Mar 2023)
• Fairness-guided Few-shot Prompting for Large Language Models (Mar 2023)
• Context-faithful Prompting for Large Language Models (Mar 2023)
• Is Prompt All You Need? No. A Comprehensive and Broader View of Instruction Learning (Mar 2023)
• UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation (Mar 2023)
• Model-tuning Via Prompts Makes NLP Models Adversarially Robust (Mar 2023)
• Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer (March 2023)
• CoTEVer: Chain of Thought Prompting Annotation Toolkit for Explanation Verification (March 2023)
• Larger language models do in-context learning differently (March 2023)
• OpenICL: An Open-Source Framework for In-context Learning (March 2023)
• Dynamic Prompting: A Unified Framework for Prompt Tuning (March 2023)
• Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning (March 2023)
• Effectiveness of Data Augmentation for Prefix Tuning with Limited Data (March 2023)
• Mixture of Soft Prompts for Controllable Data Generation (March 2023)
• Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners (March 2023)
• How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks (March 2023)
• Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT (Feb 2023)
• EvoPrompting: Language Models for Code-Level Neural Architecture Search (Feb 2023)
• In-Context Instruction Learning (Feb 2023)
• Chain of Hindsight Aligns Language Models with Feedback (Feb 2023)
• Language Is Not All You Need: Aligning Perception with Language Models (Feb 2023)
• Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data (Feb 2023)
• Active Prompting with Chain-of-Thought for Large Language Models (Feb 2023)
• More than you've asked for: A Comprehensive Analysis of Novel Prompt Injection Threats to Application-Integrated Large Language Models (Feb 2023)
• A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT (Feb 2023)
• Guiding Large Language Models via Directional Stimulus Prompting (Feb 2023)
• How Does In-Context Learning Help Prompt Tuning? (Feb 2023)
• Scalable Prompt Generation for Semi-supervised Learning with Language Models (Feb 2023)
• Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints (Feb 2023)
• À-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting (Feb 2023)
• GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks (Feb 2023)
• The Capacity for Moral Self-Correction in Large Language Models (Feb 2023)
• SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains (Feb 2023)
• Evaluating the Robustness of Discrete Prompts (Feb 2023)
• Compositional Exemplars for In-context Learning (Feb 2023)
• Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery (Feb 2023)
• Multimodal Chain-of-Thought Reasoning in Language Models (Feb 2023)
• Large Language Models Can Be Easily Distracted by Irrelevant Context (Feb 2023)
• Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models (Feb 2023)
• Progressive Prompts: Continual Learning for Language Models (Jan 2023)
• Batch Prompting: Efficient Inference with LLM APIs (Jan 2023)
• Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP (Dec 2022)
• On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning (Dec 2022)
• Constitutional AI: Harmlessness from AI Feedback (Dec 2022)
• Successive Prompting for Decomposing Complex Questions (Dec 2022)
• Large Language Models are reasoners with Self-Verification (Dec 2022)
• Discovering Language Model Behaviors with Model-Written Evaluations (Dec 2022)
• Structured Prompting: Scaling In-Context Learning to 1,000 Examples (Dec 2022)
• PAL: Program-aided Language Models (Nov 2022)
• Large Language Models Are Human-Level Prompt Engineers (Nov 2022)
• Ignore Previous Prompt: Attack Techniques For Language Models (Nov 2022)
• Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods (Nov 2022)
• Teaching Algorithmic Reasoning via In-context Learning (Nov 2022)
• Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference (Nov 2022)
• Ask Me Anything: A simple strategy for prompting language models (Oct 2022)
• Recitation-Augmented Language Models (Oct 2022)
• ReAct: Synergizing Reasoning and Acting in Language Models (Oct 2022)
• Prompting GPT-3 To Be Reliable (Oct 2022)
• Decomposed Prompting: A Modular Approach for Solving Complex Tasks (Oct 2022)
• Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought (Oct 2022)
• Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples (Sep 2022)
• Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning (Sep 2022)
• Promptagator: Few-shot Dense Retrieval From 8 Examples (Sep 2022)
• Atlas: Few-shot Learning with Retrieval Augmented Language Models (Nov 2022)
• DocPrompting: Generating Code by Retrieving the Docs (July 2022)
• On the Advance of Making Language Models Better Reasoners (June 2022)
• Large Language Models are Zero-Shot Reasoners (May 2022)
• Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations (May 2022)
• MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning (May 2022)
• PPT: Pre-trained Prompt Tuning for Few-shot Learning (Mqy 2022)
• Toxicity Detection with Generative Prompt-based Inference (May 2022)
• Learning to Transfer Prompts for Text Generation (May 2022)
• The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning (May 2022)
• A Taxonomy of Prompt Modifiers for Text-To-Image Generation (Apr 2022)
• PromptChainer: Chaining Large Language Model Prompts through Visual Programming (Mar 2022)
• Self-Consistency Improves Chain of Thought Reasoning in Language Models (March 2022)
• Training language models to follow instructions with human feedback
• Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? (Feb 2022)
• Chain of Thought Prompting Elicits Reasoning in Large Language Models (Jan 2022)
• Show Your Work: Scratchpads for Intermediate Computation with Language Models (Nov 2021)
• AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts (Oct 2021)
• Generated Knowledge Prompting for Commonsense Reasoning (Oct 2021)
• Multitask Prompted Training Enables Zero-Shot Task Generalization (Oct 2021)
• Reframing Instructional Prompts to GPTk's Language (Sep 2021)
• Design Guidelines for Prompt Engineering Text-to-Image Generative Models (Sep 2021)
• Making Pre-trained Language Models Better Few-shot Learners (Aug 2021)
• Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity (April 2021)
• BERTese: Learning to Speak to BERT (April 2021)
• The Power of Scale for Parameter-Efficient Prompt Tuning (April 2021)
• Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm (Feb 2021)
• Calibrate Before Use: Improving Few-Shot Performance of Language Models (Feb 2021)
• Prefix-Tuning: Optimizing Continuous Prompts for Generation (Jan 2021)
• Learning to Generate Task-Specific Adapters from Task Description (Jan 2021)
• Making Pre-trained Language Models Better Few-shot Learners (Dec 2020)
• Learning from Task Descriptions (Nov 2020)
• AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts (Oct 2020)
• Language Models are Few-Shot Learners (May 2020)
• How Can We Know What Language Models Know? (July 2020)
• Scaling Laws for Neural Language Models (Jan 2020)

应用

• BloombergGPT: A Large Language Model for Finance (March 2023)
• Medical Intervention Duration Estimation Using Language-enhanced Transformer Encoder with Medical Prompts (March 2023)
• Soft-prompt tuning to predict lung cancer using primary care free-text Dutch medical notes (March 2023)
• TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs (March 2023)
• Larger Probes Tell a Different Story: Extending Psycholinguistic Datasets Via In-Context Learning (March 2023)
• Linguistically Informed ChatGPT Prompts to Enhance Japanese-Chinese Machine Translation: A Case Study on Attributive Clauses (March 2023)
• Knowledge-augmented Frame Semantic Parsing with Hybrid Prompt-tuning (March 2023)
• Debiasing Scores and Prompts of 2D Diffusion for Robust Text-to-3D Generation (March 2023)
• Zero-shot Model Diagnosis (March 2023)
• Prompting Large Language Models to Generate Code-Mixed Texts: The Case of South East Asian Languages (March 2023)
• SPeC: A Soft Prompt-Based Calibration on Mitigating Performance Variability in Clinical Notes Summarization (March 2023)
• Large Language Models and Simple, Stupid Bugs (March 2023)
• Can Generative Pre-trained Transformers (GPT) Pass Assessments in Higher Education Programming Courses? (Mar 2023)
• SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models (Mar 2023)
• ICL-D3IE: In-Context Learning with Diverse Demonstrations Updating for Document Information Extraction (March 2023)
• MathPrompter: Mathematical Reasoning using Large Language Models (March 2023)
• Prompt-Based Learning for Thread Structure Prediction in Cybersecurity Forums (March 2023)
• Choice Over Control: How Users Write with Large Language Models using Diegetic and Non-Diegetic Prompting (March 2023)
• Prompting Large Language Models with Answer Heuristics for Knowledge-based Visual Question Answering (March 2023)
• Soft Prompt Guided Joint Learning for Cross-Domain Sentiment Analysis (March 2023)
• SpeechPrompt v2: Prompt Tuning for Speech Classification Tasks (March 2023)
• Goal Driven Discovery of Distributional Differences via Language Descriptions (Feb 2023)
• Navigating the Grey Area: Expressions of Overconfidence and Uncertainty in Language Models (Feb 2023)
• TabGenie: A Toolkit for Table-to-Text Generation (Feb 2023)
• SGL-PT: A Strong Graph Learner with Graph Prompt Tuning (Feb 2023)
• Few-Shot Table-to-Text Generation with Prompt-based Adapter (Feb 2023)
• Language Models Are Few-shot Learners for Prognostic Prediction (Feb 2023)
• STA: Self-controlled Text Augmentation for Improving Text Classifications (Feb 2023)
• Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback (Feb 2023)
• How Generative AI models such as ChatGPT can be (Mis)Used in SPC Practice, Education, and Research? An Exploratory Study (Feb 2023)
• Grimm in Wonderland: Prompt Engineering with Midjourney to Illustrate Fairytales (Feb 2023)
• LabelPrompt: Effective Prompt-based Learning for Relation Classification (Feb 2023)
• Language Model Crossover: Variation through Few-Shot Prompting (Feb 2023)
• Prompt Tuning of Deep Neural Networks for Speaker-adaptive Visual Speech Recognition (Feb 2023)
• The Capacity for Moral Self-Correction in Large Language Models (Feb 2023)
• Prompting for Multimodal Hateful Meme Classification (Feb 2023)
• PLACES: Prompting Language Models for Social Conversation Synthesis (Feb 2023)
• Commonsense-Aware Prompting for Controllable Empathetic Dialogue Generation (Feb 2023)
• Crawling the Internal Knowledge-Base of Language Models (Jan 2023)
• Legal Prompt Engineering for Multilingual Legal Judgement Prediction (Dec 2022)
• Investigating Prompt Engineering in Diffusion Models (Nov 2022)
• Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering (Sep 2022)
• Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language (Oct 2022)
• Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic? (Oct 2022)
• Plot Writing From Scratch Pre-Trained Language Models (July 2022)
• Survey of Hallucination in Natural Language Generation (Feb 2022)

收集

• Chain-of-Thought Papers
• Papers with Code
• Prompt Papers