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92 lines
3.4 KiB
Markdown
92 lines
3.4 KiB
Markdown
# Chain-of-Thought Prompting
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import {Screenshot} from 'components/screenshot'
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import COT from '../../img/cot.png'
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import ZEROCOT from '../../img/zero-cot.png'
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## Chain-of-Thought (CoT) Prompting
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<Screenshot src={COT} alt="COT" />
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Image Source: [Wei et al. (2022)](https://arxiv.org/abs/2201.11903)
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Introduced in [Wei et al. (2022)](https://arxiv.org/abs/2201.11903), chain-of-thought (CoT) prompting enables complex reasoning capabilities through intermediate reasoning steps. You can combine it with few-shot prompting to get better results on more complex tasks that require reasoning before responding.
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*Prompt:*
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```
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The odd numbers in this group add up to an even number: 4, 8, 9, 15, 12, 2, 1.
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A: Adding all the odd numbers (9, 15, 1) gives 25. The answer is False.
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The odd numbers in this group add up to an even number: 17, 10, 19, 4, 8, 12, 24.
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A: Adding all the odd numbers (17, 19) gives 36. The answer is True.
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The odd numbers in this group add up to an even number: 16, 11, 14, 4, 8, 13, 24.
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A: Adding all the odd numbers (11, 13) gives 24. The answer is True.
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The odd numbers in this group add up to an even number: 17, 9, 10, 12, 13, 4, 2.
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A: Adding all the odd numbers (17, 9, 13) gives 39. The answer is False.
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The odd numbers in this group add up to an even number: 15, 32, 5, 13, 82, 7, 1.
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A:
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```
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*Output:*
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```
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Adding all the odd numbers (15, 5, 13, 7, 1) gives 41. The answer is False.
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```
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Wow! We can see a perfect result when we provided the reasoning step. In fact, we can solve this task by providing even fewer examples, i.e., just one example seems enough:
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*Prompt:*
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```
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The odd numbers in this group add up to an even number: 4, 8, 9, 15, 12, 2, 1.
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A: Adding all the odd numbers (9, 15, 1) gives 25. The answer is False.
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The odd numbers in this group add up to an even number: 15, 32, 5, 13, 82, 7, 1.
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A:
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```
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*Output:*
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```
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Adding all the odd numbers (15, 5, 13, 7, 1) gives 41. The answer is False.
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```
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Keep in mind that the authors claim that this is an emergent ability that arises with sufficiently large language models.
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## Zero-shot COT Prompting
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<Screenshot src={ZEROCOT} alt="Zero-shot COT" />
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Image Source: [Kojima et al. (2022)](https://arxiv.org/abs/2205.11916)
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One recent idea that came out more recently is the idea of [zero-shot CoT](https://arxiv.org/abs/2205.11916) (Kojima et al. 2022) that essentially involves adding "Let's think step by step" to the original prompt. Let's try a simple problem and see how the model performs:
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*Prompt:*
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```
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I went to the market and bought 10 apples. I gave 2 apples to the neighbor and 2 to the repairman. I then went and bought 5 more apples and ate 1. How many apples did I remain with?
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```
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*Output:*
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11 apples
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```
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The answer is incorrect! Now Let's try with the special prompt.
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*Prompt:*
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```
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I went to the market and bought 10 apples. I gave 2 apples to the neighbor and 2 to the repairman. I then went and bought 5 more apples and ate 1. How many apples did I remain with?
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Let's think step by step.
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```
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*Output:*
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```
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First, you started with 10 apples.
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You gave away 2 apples to the neighbor and 2 to the repairman, so you had 6 apples left.
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Then you bought 5 more apples, so now you had 11 apples.
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Finally, you ate 1 apple, so you would remain with 10 apples.
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```
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It's impressive that this simple prompt is effective at this task. This is particularly useful where you don't have too many examples to use in the prompt. |