Summary of Does Prompt Formatting Have Any Impact on Llm Performance?, by Jia He et al.
Does Prompt Formatting Have Any Impact on LLM Performance?
by Jia He, Mukund Rungta, David Koleczek, Arshdeep Sekhon, Franklin X Wang, Sadid Hasan
First submitted to arxiv on: 15 Nov 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: 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 This research paper investigates the impact of various prompt templates on the performance of Large Language Models (LLMs), specifically OpenAI’s GPT models. The study examines how different formatting styles, such as plain text, Markdown, JSON, and YAML, affect the accuracy of LLMs in tasks like natural language reasoning, code generation, and translation. The results show that GPT-3.5-turbo’s performance varies significantly depending on the prompt template, with up to a 40% difference in a code translation task. In contrast, larger models like GPT-4 are more robust to these variations. The study highlights the importance of reconsidering the use of fixed prompt templates and suggests that different formatting styles can have a substantial impact on LLM performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how different ways of writing prompts affect Large Language Models (LLMs). Researchers used the same ideas but wrote them in different formats like plain text, Markdown, JSON, or YAML. They tested these different prompts on tasks such as understanding language, generating code, and translating texts using GPT models from OpenAI. The results show that how you write a prompt can make a big difference – up to 40% better or worse – depending on the task and even the size of the model. This study suggests we should think carefully about how we write prompts and not just use one way all the time. |
Keywords
» Artificial intelligence » Gpt » Prompt » Translation
