Скачать с ютуб Multimodal Chain-of-Thought Reasoning in Language Models | Large langauge models capabilities в хорошем качестве

Multimodal Chain-of-Thought Reasoning in Language Models | Large langauge models capabilities

Large language models have shown impressive performance on complex reasoning by leveraging chain-of-thought prompting to generate intermediate reasoning chains as the rationale to infer the answer. However, existing CoT studies have focused on the language modality. We propose Multimodal-CoT that incorporates language and vision modalities into a two-stage framework that separates rationale generation and answer inference. In this way, answer inference can leverage better generated rationales that are based on multimodal information. With Multimodal-CoT, our model under 1 billion parameters outperforms the previous state-of-the-art LLM (GPT-3.5) by 16 percentage points on the ScienceQA benchmark and even surpasses human performance. #machinelearning #multimodal #chatgpt #neuralnetwork