Papers with LLM-driven discrete prompt optimization framework PROMST

1 papers
PRompt Optimization in Multi-Step Tasks (PROMST): Integrating Human Feedback and Heuristic-based Sampling (2024.emnlp-main)

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Challenge: Prompt optimization aims to find the best prompt to a large language model (LLM) for a given task.
Approach: They propose a method to optimize prompts for LLM-driven multi-step tasks using a human-designed feedback rule.
Outcome: The proposed method outperforms human-engineered prompts and several other prompt optimization methods on 11 representative multi-step tasks.

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