Prompt Optimization Paper List

😆 Must-read papers on prompt optimization.

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Survey

• Efficient Prompting Methods for Large Language Models: A Survey. 2024.03. [Paper] 

Prompt Optimization

• GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models. 2022.03. [Paper] [Project]
• RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning. 2022.05. [Paper] [Project]
• TEMPERA: Test-Time Prompting via Reinforcement Learning.  2022.11. [Paper] [Project]
• Large Language Models Are Human-Level Prompt Engineers. 2022.11. [Paper] [Project] 
• Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery.  2023.02. [Paper] [Project]
• RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs.  2023.05. [Paper] [Project]
• Discrete Prompt Optimization via Constrained Generation for Zero-shot Re-ranker. 2023.05. [Paper] [Project]
• Automatic Prompt Optimization with "Gradient Descent" and Beam Search. 2023.05. [Paper] [Project]
• AutoHint: Automatic Prompt Optimization with Hint Generation. 2023.07. [Paper] 
• PACE: Improving Prompt with Actor-Critic Editing for Large Language Model.  2023.08. [Paper]
• Dialogue for Prompting: a Policy-Gradient-Based Discrete Prompt Generation for Few-shot Learning.  2023.08. [Paper] [Project]
• Large Language Models as Optimizers.  2023.09. [Paper] [Project]
• Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution.  2023.09. [Paper] [Project]
• Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers.  2023.09. [Paper] [Project]
• MultiPrompter: Cooperative Prompt Optimization with Multi-Agent Reinforcement Learning.  2023.10. [Paper] 
• Black-Box Prompt Optimization: Aligning Large Language Models without Model Training.  2023.11. [Paper] [Project] 
• Prompt Engineering a Prompt Engineer.  2023.11. [Paper]
• Automatic Engineering of Long Prompts.  2023.11. [Paper] [Project]
• A Universal Prompt Generator for Large Language Models.  2023.11. [Paper] 
• Prompt Optimization via Adversarial In-Context Learning.  2023.12. [Paper] [Project]
• MAPO: Boosting Large Language Model Performance with Model-Adaptive Prompt Optimization. 2023.12. [Paper]
• Intent-based Prompt Calibration: Enhancing prompt optimization with synthetic boundary cases.  2024.02. [Paper] [Project]
• Are Large Language Models Good Prompt Optimizers?  2024.02. [Paper]
• Unleashing the Potential of Large Language Models as Prompt Optimizers: An Analogical Analysis with Gradient-based Model Optimizers. 2024.02. [Paper] [Project]
• PhaseEvo: Towards Unified In-Context Prompt Optimization for Large Language Models,  2024.02. [Paper]
• A User-Friendly Framework for Generating Model-Preferred Prompts in Text-to-Image Synthesis. 2024.02. [Paper] [Project]
• MORL-Prompt: An Empirical Analysis of Multi-Objective Reinforcement Learning for Discrete Prompt Optimization. 2024.02. [Paper]
• GLaPE: Gold Label-agnostic Prompt Evaluation and Optimization for Large Language Models.  2024.02. [Paper] [Project]
• CrossTune: Black-Box Few-Shot Classification with Label Enhancement.  2024.03. [Paper]
• Automatic Prompt Selection for Large Language Models. 2024.04. [Paper]
• Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. 2024.04. [Paper]