本文主要对2023一篇论文《Multimodal Chain-of-Thought Reasoning in Language Models》主要内容进行介绍。 摘要大型语言模型(LLM)通过利用思想链(CoT)提示生成中间推理链作为推断答案的基本原理,在复杂推理方面表现出了令人印象深刻的性能。然而,现有的CoT研究主要集中在语言模态上。这篇文章提出了多模态CoT,将语言(文本)...
摘要 目前一些大型语言模型(LLMs , large language model)通过利用思维链(CoT , chain-of-thought)提示来生成中间推理链,作为推断答案的基本原理,在复杂推理方面表现出了令人印象深刻的性能。然而,现有的CoT研究主要集中在语言情景方面。我们提出了多模态cot,它将语言(文本)和视觉(图像)模态合并到一个两阶段框架中,...
Researchers at Google have proposed PaLM-E, a single model that is able to control different robots in simulation and in the real world, while at the same time being quantitatively competent at general VQA and captioning tasks. The embodied language mode
Multimodal Chain-of-Thought Reasoning in Language Models "Imagine learning a textbook without figures or tables." Multimodal-CoT incorporates vision features in a decoupled training framework. The framework consists of two training stages: (i) rationale generation and (ii) answer inference. Both stages...
Multimodal reasoning is a critical component in the pursuit of artificial intelligence systems that exhibit human-like intelligence, especially when tackling complex tasks. While the chain-of-thought (CoT) technique has gained considerable attention, the existing ScienceQA dataset, primarily focused on ...
📚🔍 Feast your eyes on an assortment of datasets, techniques for tuning multimodal instructions, methods for multimodal in-context learning, approaches for multimodal chain-of-thought, visual reasoning aided by gargantuan language models, foundational models, and much more. 🌟🔥 ✨✨✨ ...
Multimodal Instruction Tuning Multimodal In-Context Learning Multimodal Chain-of-Thought LLM-Aided Visual Reasoning Fundation Models others 这6 个子方向以及相应的新开放的数据集,该链接将保持实时更新,便于研究人员跟进。 END 加入「计算机视觉」交流群?备注:CV...
这篇文章探讨了大语言模型中的链式推理(chain-of-thought reasoning)如何在训练数据具备局部统计结构时提升推理效果。作者提出,当训练数据包含相互强烈影响的局部变量簇时,通过推理中间步骤可以更准确地推断未见过的变量关系。理论证明和实验结果表明,使用局部结构化的观测数据并逐步进行推理,比直接训练所有变量的数据效率更...
In recent years, large language models have made significant advancements in the field of natural language processing, yet there are still inadequacies in specific domain knowledge and applications. This paper Proposes MaintAGT, a professional large model for intelligent operations and maintenance, aimed...
通过错误归因,发现64%的Reasoning并不make sense,且是由于视觉特征缺失导致的 例如上图的推理中,缺失视觉特征时候会假想出:磁铁的南极和另一个磁铁的南极更接近,而加上视觉特征后这个错误就被修正了。 本文对multimodal的定义局限在图文上,既然如此,对于开篇的前一个问题,思考一下最简单的方式就是对图片用caption生成...