论文简单解读:SSDesign:白话文:MLLM大模型算法-mPLUG-Owl 整体论文框架图和拆解参数图 论文整体框架图 模型模块及参数示例详解 分模块论文详细解读 1.论文中的Visual Encoder模块 MplugOwlVisionEmbeddings将图片转化成patch序列 class MplugOwlVisionEmbeddings(nn.Module): # 视觉模块的初始化Embeddings def __init_...
mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding. mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding. EMNLP2024. mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding. mPLUG-PaperOwl: Scientific Diagra...
达摩院的研究者也发布了在 Youku-mPLUG 数据上预训练的模块化视频 LLM 模型mPLUG-video,延续了 mPLUG 系列的模块化训练思想,把 LLM 升级为一个视频大模型。在 mPLUG 系列工作中,之前的 E2E-VLP 、mPLUG 、mPLUG-2、mPLUG-Owl🦉 分别被 ACL2021 、EMNLP2022、ICML2023 录用,其中 mPLUG 工作在 VQA 榜单...
延续mPLUG-DocOwl的做法,DocOwl 1.5将多个下游任务统一为指令问答的形式,在统一的结构学习之后,通过多任务联合训练的形式得到一个文档领域的通用模型(generalist)。 此外,为了使得模型具备详细解释的能力,mPLUG-DocOwl曾尝试引入纯文本指令微调数据进行联合训练,有一定效果但并不理想。 在DocOwl 1.5中,作者基于下游任务...
mPLUG-PaperOwl(ACM MM 2024) - mPLUG-PaperOwl: Scientific Diagram Analysis with the Multimodal Large Language Model UReader(EMNLP 2023) - UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model
mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding O网页链接ChatPaper综述:说明了现有的多模型大型语言模型在OCR-free文档理解方面存在的问题。这些模型在浅层无OCR文本识别方面表现出了很好的零样本能力,但是在没有领域内的训练的情况下,它们往往忽略了OCR的细粒度特征,如复杂的...
From the paper, I see learnable queries in visual abastractor. I think it may be similar to Perceiver in Flamingo or Q-Former in BLIP-2. But I don't find the implementation in your code about learnable queries (mPLUG_OwlVisualAbstractorEncoder and mPLUG_OwlVisualAbstractorModel in modeling...
Github:https://github.com/X-PLUG/mPLUG-DocOwl Paper:https://arxiv.org/abs/2307.02499 Demo:https://modelscope.cn/studios/damo/mPLUG-DocOwl/summary ModelScope Demo 体验 点击https://modelscope.cn/studios/damo/mPLUG-DocOwl/summary就可以立刻体验了。
0.基础信息paper: http://arxiv.org/abs/2311.04257 code: https://github.com/X-PLUG/mPLUG-Owl/tree/main/mPLUG-Owl2 Keywords: #MLLM #多模态学习 #多模态 #LLM #大语言模型 #AIGC #Demo TL;NR:本文引入一种多…
*🔥🔥🔥[2024.9.06]We release the arxiv paper of[mPLUG-DocOwl 2](https://arxiv.org/abs/2409.03420), a SOTA 8B Multimodal LLM on OCR-free Multipage Document Understanding, each document image is encoded with just 324 tokens!