jxzhangjhu/Awesome-LLM-Prompt-Optimization
An awesome-style curated collection of papers on advanced prompt optimization and tuning methods for large language models.
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This repository aggregates academic papers and resources on LLM prompt tuning and automatic optimization techniques published after 2022. It organizes content across multiple categories including fine-tuning methods, reinforcement learning approaches, gradient-free optimization, in-context learning, and Bayesian optimization for prompts. The collection serves as a reference bibliography for researchers working on improving LLM performance through prompt engineering.
Frequently asked
- What is jxzhangjhu/Awesome-LLM-Prompt-Optimization?
- An awesome-style curated collection of papers on advanced prompt optimization and tuning methods for large language models.
- Is Awesome-LLM-Prompt-Optimization open source?
- Yes — jxzhangjhu/Awesome-LLM-Prompt-Optimization is an open-source project tracked on heatdrop.
- How popular is Awesome-LLM-Prompt-Optimization?
- jxzhangjhu/Awesome-LLM-Prompt-Optimization has 412 stars on GitHub.
- Where can I find Awesome-LLM-Prompt-Optimization?
- jxzhangjhu/Awesome-LLM-Prompt-Optimization is on GitHub at https://github.com/jxzhangjhu/Awesome-LLM-Prompt-Optimization.