The aim of the project is to survey various automated prompt optimisation approaches and conduct a comparative analysis with respect to their applicability on code generation tasks that are performed by LLMs. It seeks to assess the effectiveness of approaches such as Reinforcement Learning (RL), Genetic Algorithms (GA) and Bayesian Optimisation in improving LLM-produced code both with respect to quality and speed, sans manual prompt engineering.
Dorijan9/Prompt_optimisation_project
Folders and files
| Name | Name | Last commit date | ||
|---|---|---|---|---|