Multi Model CoT

This research paper 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 generating a rationale based on multimodal information. This is followed by the second phase, answer inference, which leverages the informative generated rationales.

The multimodal CoT model (1B) outperforms GPT-3.5 on the ScienceQA benchmark.