Summary of The Unreasonable Effectiveness Of Eccentric Automatic Prompts, by Rick Battle and Teja Gollapudi
The Unreasonable Effectiveness of Eccentric Automatic Prompts
by Rick Battle, Teja Gollapudi
First submitted to arxiv on: 9 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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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 Large Language Models (LLMs) have impressive problem-solving and basic math abilities, but their effectiveness depends heavily on the prompt’s formulation. This study investigates the impact of incorporating “positive thinking” into the system message of prompts and compares it to systematic prompt optimization. The researchers tested 60 combinations of prompts on three models with varying parameters (7-70 billion) using the GSM8K dataset. They found that results don’t universally generalize across models, but in most cases, including “positive thinking” prompts improved model performance. However, Llama2-70B was an exception when not using Chain of Thought prompting, as the optimal system message was none at all. To reduce computation time, they compared the best “positive thinking” prompt with automated prompt optimization and found that the latter emerged as the most effective method for enhancing performance, even with smaller open-source models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large Language Models (LLMs) are super smart! They can solve problems and do math really well. But did you know their success depends on how we ask them questions? This study wanted to see if adding “positive thinking” to the question would help or hurt the answer. They tried 60 different ways of asking the same question on three different models, using a special dataset called GSM8K. The results were surprising – sometimes it helped, but not always! One model was weird and didn’t like being asked positive questions at all. To make things easier, they compared the best way to ask the question with an automatic way of asking questions that worked really well! |
Keywords
* Artificial intelligence * Optimization * Prompt * Prompting
