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https://github.com/dair-ai/Prompt-Engineering-Guide
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15 lines
951 B
Plaintext
15 lines
951 B
Plaintext
# Multimodal CoT Prompting
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import { Callout, FileTree } from 'nextra-theme-docs'
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import {Screenshot} from 'components/screenshot'
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import MCOT from '../../img/multimodal-cot.png'
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[Zhang et al. (2023)](https://arxiv.org/abs/2302.00923) recently proposed a multimodal chain-of-thought prompting approach. Traditional CoT focuses on the language modality. In contrast, Multimodal CoT incorporates text and vision into a two-stage framework. The first step involves rationale generation based on multimodal information. This is followed by the second phase, answer inference, which leverages the informative generated rationales.
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The multimodal CoT model (1B) outperforms GPT-3.5 on the ScienceQA benchmark.
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<Screenshot src={MCOT} alt="MCOT" />
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Image Source: [Zhang et al. (2023)](https://arxiv.org/abs/2302.00923)
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Further reading:
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- [Language Is Not All You Need: Aligning Perception with Language Models](https://arxiv.org/abs/2302.14045) (Feb 2023) |