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Prompt-Engineering-Guide

Damon Kost
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dair-ai/Prompt-Engineering-Guide
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Guides
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Prompting Introduction
5
Basic Prompting
7
Prompt Engineering
4
Miscellaneous Topics
5
Adversarial Prompting
4
Advanced Prompting
7
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Datasets
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Papers
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survey/overview
6
Approach/Technique
63
Applications
15
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Lectures
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Tools & Libraries
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Guides
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3 Principles for prompt engineering with GPT-3
A beginner-friendly guide to generative language models - LaMBDA guide
A Complete Introduction to Prompt Engineering for Large Language Models
A Generic Framework for ChatGPT Prompt Engineering
AI Content Generation
AI's rise generates new job title: Prompt engineer
Awesome ChatGPT Prompts
Best 100+ Stable Diffusion Prompts
Best practices for prompt engineering with OpenAI API
Building GPT-3 applications — beyond the prompt
ChatGPT, AI and GPT-3 Apps and use cases
CMU Advanced NLP 2022: Prompting
Curtis64's set of prompt gists
DALL·E 2 Prompt Engineering Guide
DALL·E 2 Preview - Risks and Limitations
DALLE Prompt Book
DALL-E, Make Me Another Picasso, Please
Diffusion Models: A Practical Guide
Exploiting GPT-3 Prompts
Exploring Prompt Injection Attacks
Extrapolating to Unnatural Language Processing with GPT-3's In-context Learning: The Good, the Bad, and the Mysterious
Generative AI with Cohere: Part 1 - Model Prompting
Giving GPT-3 a Turing Test
GPT3 and Prompts: A quick primer
How to Draw Anything
How to get images that don't suck
How to make LLMs say true things
How to write good prompts
Introduction to Reinforcement Learning with Human Feedback
In defense of prompt engineering
Language Models and Prompt Engineering: Systematic Survey of Prompting Methods in NLP
Learn Prompting
Methods of prompt programming
Mysteries of mode collapse
NLP for Text-to-Image Generators: Prompt Analysis
NLP with Deep Learning CS224N/Ling284 - Lecture 11: Promting, Instruction Tuning, and RLHF
Notes for Prompt Engineering by sw-yx
OpenAI Cookbook
OpenAI Prompt Examples for several applications
Pretrain, Prompt, Predict - A New Paradigm for NLP
Prompt Engineering 101 - Introduction and resources
Prompt Engineering 101: Autocomplete, Zero-shot, One-shot, and Few-shot prompting
Prompt Engineering 101
Prompt Engineering - A new profession ?
Prompt Engineering by co:here
Prompt Engineering by Microsoft
Prompt Engineering: The Career of Future
Prompt engineering davinci-003 on our own docs for automated support (Part I)
Prompt Engineering Guide: How to Engineer the Perfect Prompts
Prompt Engineering in GPT-3
Prompt Engineering Template
Prompt Engineering Topic by GitHub
Prompt Engineering: From Words to Art
Prompt Engineering with OpenAI's GPT-3 and other LLMs
Prompt injection attacks against GPT-3
Prompt injection to read out the secret OpenAI API key
Prompting in NLP: Prompt-based zero-shot learning
Prompting Methods with Language Models and Their Applications to Weak Supervision
Prompts as Programming by Gwern
Reverse Prompt Engineering for Fun and (no) Profit
So you want to be a prompt engineer: Critical careers of the future
Simulators
Start with an Instruction
Talking to machines: prompt engineering & injection
The Book - Fed Honeypot
The ChatGPT Prompt Book
The Mirror of Language
Using GPT-Eliezer against ChatGPT Jailbreaking
What Is ChatGPT Doing … and Why Does It Work?
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Papers
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Search
survey/overview
6
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)
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)
Approach/Technique
63
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)
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)
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)
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)
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)
Promptagator: Few-shot Dense Retrieval From 8 Examples (Sep 2022)
On the Advance of Making Language Models Better Reasoners (June 2022)
Large Language Models are Zero-Shot Reasoners (May 2022)
MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning (May 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)
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)
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)
Applications
15
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)
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)
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