zero-shot prompting

Source The paper argues that zero-shot prompting on a instruction-tuned small language models outperform LLMs systems. Instruction-tuning actually improve zero-shot learning performance.

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publié à
12 févr. 2024
modifié à
08 mars 2025
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1 min de lecture (46 words)
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llms.txt

zero-shot prompting

Source arXiv

The paper argues that zero-shot prompting on a instruction-tuned small language models outperform LLMs systems.

Instruction-tuning actually improve zero-shot learning performance.
Mostly tested on FLAN, but show results throughout with GPT-3 and on few reading comprehension dataset.

Honorable mentions include prompt tuning or few-shots prompting

Source arXiv

The paper argues that zero-shot prompting on a instruction-tuned small language models outperform LLMs systems.

Instruction-tuning actually improve zero-shot learning performance.
Mostly tested on FLAN, but show results throughout with GPT-3 and on few reading comprehension dataset.

Honorable mentions include prompt tuning or few-shots prompting

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Prompt engineering

A constructive way to form communications with LLMs. As we improve the quality of prompts, we can expect better results from the models. Similar to linguistic, a good prompt is a good form of communication with the system.

zero-shot prompting

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