Multi-Modal Generative AI: Multi-modal LLM, Diffusion and Beyond 摘要 多模态生成人工智能在学术界和工业界都受到了越来越多的关注。特别是,两种主导技术家族是:i) 多模态大型语言模型(MLLM),例如GPT-4V,它显示了对多模态理解的出色能力;ii) 扩散模型,如Sora,它表现出令人印象深刻的各种多模态能力,尤其是在...
capital of China, Sept. 19, 2024. A geographic sciences multi-modal LLM, the first of its kind in the world, was unveiled in Beijing on Thursday. It could support the integration of geography and artificial intelligence and help accelerate geographical discoveries...
待了解的问题 什么是sequence concatenation in LLM Training Reference [1] Neural Discrete Representation Learning (VQ-VAE)) [2] ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision [3] CLIP [4] BEIT: BERT Pre-Training of Image Transformers发布...
MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?O网页链接作者关注于多模态大型语言模型(MLLM)在视觉环境下的卓越表现,但它们在视觉数学问题解决方面的能力尚未得到充分评估和理解。文章提出了MathVerse,这是一个全面的多模态数学基准,旨在对MLLM进行公平和深入的评估。Math...
基于合成的训练数据,我们开发了通用多模态嵌入器(GME),这是一种基于MLLM的密集检索器,专为UMR设计。此外,我们构建了一个全面的UMR基准(UMRB)来评估我们方法的有效性。实验结果表明,我们的方法在现有UMR方法中达到了最先进的性能。最后,我们对模型扩展、训练策略进行了深入分析,并对模型和合成数据进行了消融研究。
BEIJING, Sept. 19 (Xinhua) -- A geographic sciences multi-modal Large Language Model (LLM), the first of its kind in the world, was unveiled in Beijing on Thursday. It could support the integration of geography and artificial intelligence and help accelerate geographical discoveries. ...
MATHVERSE: Does Your Multi-modal LLM Truly See theDiagrams inVisual Math Problems?doi:10.1007/978-3-031-73242-3_10The remarkable progress of Multi-modal Large Language Models (MLLMs) has gained unparalleled attention. However, their capabilities in visual math problem-solving remain insufficiently ...
In this paper, we present a simple MLLM-based Image Restoration framework to address this gap, namely Multi-modal Large Language Model based Restoration Assistant (LLMRA). We exploit the impressive capabilities of MLLMs to obtain the degradation information for universal image restoration. By ...
MATHVERSE: Does Your Multi-modal LLM Truly See theDiagrams inVisual Math Problems? The remarkable progress of Multi-modal Large Language Models (MLLMs) has gained unparalleled attention. However, their capabilities in visual math problem-... R Zhang,D Jiang,Y Zhang,... - European Conference ...
LayoutLLM的核心在于一种布局指令调整策略，该策略专门设计用来增强模型对文档布局的理解和利用。这一策略包括布局感知预训练和布局感知监督微调两个主要组成部分，通过这些方法，LayoutLLM能够有效地捕捉和利用文档的布局信息，以提高文档理解的准确性和效率。LLMS方法 整体架构 方法分点详细说明 1.布局感知预训练（Layout...