Summary of Meta-prompting: Enhancing Language Models with Task-agnostic Scaffolding, by Mirac Suzgun et al.
Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding
by Mirac Suzgun, Adam Tauman Kalai
First submitted to arxiv on: 23 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC)
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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 As machine learning educators writing for a technical audience that is not specialized in the paper’s subfield, we introduce meta-prompting, an effective scaffolding technique designed to enhance the functionality of language models (LMs). This approach transforms a single LM into a multi-faceted conductor, adept at managing and integrating multiple independent LM queries. By employing high-level instructions, meta-prompting guides the LM to break down complex tasks into smaller, more manageable subtasks. These subtasks are then handled by distinct “expert” instances of the same LM, each operating under specific, tailored instructions. Central to this process is the LM itself, in its role as the conductor, which ensures seamless communication and effective integration of the outputs from these expert models. It additionally employs its inherent critical thinking and robust verification processes to refine and authenticate the end result. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary We can help high school students or non-technical adults understand that this paper is about a new way to make language models work better. It’s like giving them a set of instructions to follow, which makes them very good at solving complex problems. This approach helps a single model do many different things, like play games or solve puzzles. It’s also easy to use because you don’t need to tell the model exactly how to do each task. |
Keywords
» Artificial intelligence » Machine learning » Prompting
