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Summary of Are Large Language Models Good Prompt Optimizers?, by Ruotian Ma et al.


Are Large Language Models Good Prompt Optimizers?

by Ruotian Ma, Xiaolei Wang, Xin Zhou, Jian Li, Nan Du, Tao Gui, Qi Zhang, Xuanjing Huang

First submitted to arxiv on: 3 Feb 2024

Categories

  • Main: Computation and Language (cs.CL)
  • Secondary: Artificial Intelligence (cs.AI)

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Summary difficulty Written by Summary
High Paper authors High Difficulty Summary
Read the original abstract here
Medium GrooveSquid.com (original content) Medium Difficulty Summary
LLM-based Automatic Prompt Optimization has shown promising results in recent studies, but its underlying mechanism remains unclear. This paper investigates the actual process of LLM-based Prompt Optimization and finds that LLM optimizers tend to be biased by their own prior knowledge rather than genuinely reflecting on errors. Furthermore, even when reflection is semantically valid, LLM optimizers often fail to generate appropriate prompts for target models with a single prompt refinement step. The study introduces the “Automatic Behavior Optimization” paradigm, which directly optimizes the target model’s behavior in a more controllable manner. This development has the potential to inspire new directions for automatic prompt optimization.
Low GrooveSquid.com (original content) Low Difficulty Summary
A recent way to make computers learn better uses something called LLM-based Automatic Prompt Optimization. But nobody really knows how it works. In this study, scientists looked deeper into this method and found that it’s not as perfect as we thought. The computer is too influenced by what it already knows and can’t always come up with the right prompts to help other computers learn. To fix this problem, the researchers came up with a new idea called “Automatic Behavior Optimization”. This approach helps the target computer behave better in a more controlled way. This discovery could lead to new ways for computers to learn and get smarter.

Keywords

» Artificial intelligence  » Optimization  » Prompt